ICoSET 2019 - proceeding.uir.ac.id

ICoSET 2019Proceedings of the

Second International Conference onScience, Engineering and Technology

Riau - Indonesia

September 5 - 7, 2019

Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda.All rights reserved

Edited by Arbi Haza Nasution, Evizal Abdul Kadir and Luiz Moutinho

Printed in Portugal

ISBN: 978-989-758-463-3

Depósito Legal: 473348/20

http://icoset.uir.ac.id

BRIEF CONTENTS

INVITED SPEAKERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV

ORGANIZING COMMITTEES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V

PROGRAM COMMITTEE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI

FOREWORD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII

CONTENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IX

III

INVITED SPEAKERSProf. EE-Peng Lim

Singapore Management UniversitySingapore

Assoc. Prof. Yuichi SugaiKyushu University

Japan

Prof. Ir. Dr Sharul Kamal Abdul RahimUniversiti Teknologi Malaysia

Malaysia

Assoc. Prof. Dr. Norma binti AliasUniversiti Teknologi Malaysia

Malaysia

IV

ORGANIZING COMMITTEES

GENERAL CHAIR

Dr. Arbi Haza Nasution, M.IT, Universitas Islam Riau, Indonesia

TECHNICAL PROGRAM CHAIR

Dr. Evizal Abdul Kadir, ST., M.Eng, Universitas Islam Riau, Indonesia

GENERAL CO-CHAIR

Dr. Eng. Muslim, ST., MT, Universitas Islam Riau, Indonesia

EDITORIAL CHAIR

Yudhi Arta, S.Kom., M.Kom, Universitas Islam Riau, Indonesia

STEERING COMMITTEE

Prof. Josaphat Tetuko Sri Sumantyo, Ph.D, Chiba University, JapanProf. Ir. Dr. Sharul Kamal Abdul Rahim, Universiti Teknologi Malaysia, Malaysia

Prof. Toru Ishida, Kyoto University, JapanProf. Ee-Peng Lim, Singapore Management University, Singapore

Prof. Dr. H Syafrinaldi SH, MCL, Universitas Islam Riau, Indonesia

PUBLICATION AND RELATIONSHIP CHAIR

Dr. Syafriadi, S.H., M.H., Universitas Islam Riau, Indonesia

FINANCIAL CHAIR

Ause Labellapansa, ST., M.Cs., M.Kom., Universitas Islam Riau, Indonesia

EDITORIAL BOARD

Putra Efri Rahman, S.Kom, Universitas Islam Riau, IndonesiaKhairul Umam Syaliman, S.T., M.Kom., Politeknik Caltex Riau, Indonesia

Winda Monika, S.Pd., M.Sc., Universitas Lancang Kuning, IndonesiaPanji Rachmat Setiawan, S.Kom., M.M.S.I., Universitas Islam Riau, IndonesiaRizdqi Akbar Ramadhan, S.Kom., M.Kom., Universitas Islam Riau, Indonesia

Anggiat, Universitas Islam Riau, IndonesiaArif Lukman Hakim, Universitas Riau, Indonesia

V

PROGRAM COMMITTEEProf. Dr. Tengku Dahril, M.Sc, Universitas IslamRiau, Indonesia

Prof. Dr. Hasan Basri Jumin, M.Sc, UniversitasIslam Riau, Indonesia

Prof. Dr. Sugeng Wiyono, MMT, UniversitasIslam Riau, Indonesia

Prof. Zainal A. Hasibuan, MLS., Ph.D,University of Indonesia, Indonesia

Prof. Josaphat Tetuko Sri Sumantyo, Ph.D,Chiba University, Japan

Prof. Dr. Eko Supriyanto, Universiti TeknologiMalaysia, Malaysia

Prof. Dr. Zailuddin Arifin, Universiti TeknologiMARA, Malaysia

Prof. Jhon Lee, B.Sc, M.Sc., Ph.D, KyungdongUniversity, Korea

Prof. Ahmed A. Al Absi, Kyungdong University,KoreaProf. Wisup Bae, Ph.D, Sejong University, Korea

Prof. Kyuro Sasaki, Kyushu University, Japan

Prof. Adiwijaya, Telkom University, Indonesia

Prof. Ir. Asep Kurnia Permadi, M. Sc, Ph.D,Institut Teknologi Bandung, Indonesia

Assoc. Prof. Dr. Azhan Hashim Ismail, UniversitiTeknologi MARA, Malaysia

Assoc. Prof. Yuichi Sugai, Kyushu University,Japan

Assoc. Prof. Dr. Sonny Irawan, UniversitiTeknologi Petronas, Malaysia

Assoc. Prof. Hussein Hoteit, King AbdullahUniversity of Science and Technology, Saudi Arabia

Assoc. Prof. Dr. Anas Puri, ST., MT, UniversitasIslam Riau, Indonesia

Kuen-Song Lin, Ph.D, Yuan Ze University, Taiwan

Dr. Shukor Sanim Mohd Fauzi, UniversitiTeknologi MARA, Malaysia

Dr. Inkyo Cheong, Inha University, Korea

Ahn, Young Mee, Ph.D, Inha University, Korea

Hitoshi Irie, Ph.D, Chiba University, Japan

Julie Yu-Chih Liu, Ph.D, Yuan Ze University,TaiwanLiang Chih Yu, Ph.D, Yuan Ze University, Taiwan

Chia-Yu Hsu, Ph.D, Yuan Ze University, Taiwan

Dr. Amit Pariyar, University Malaysia Sarawak,Malaysia

Dr. Madi Abdullah Naser, Sebha University,Libya

Dr. Nguyen Xuan Huy, Ho Chi Minh CityUniversity of Technology, Vietnam

Dr. Chunqiu Li, Beijing Normal University, China

Dr. Goh Thian Lai, Universiti KebangsaanMalaysia, Malaysia

Dr. Syahrir Ridha, Universiti Teknologi Petronas,Malaysia

Dr. Kemas Muslim L., Telkom University,IndonesiaDr. Moch. Arif Bijaksana, Telkom University,IndonesiaDr. Satria Mandala, Telkom University, Indonesia

Dr. Wahyudi Sutopo, Solo State University,IndonesiaDr. Zulfatman, University of MuhammadyahMalang, Indonesia

Dr. Suranto AM, UPN Veteran Yogyakarta,IndonesiaDr. Eng. Husnul Kausarian, B.Sc (Hons)., M.Sc,Universitas Islam Riau, Indonesia

VI

FOREWORD

In the name of Allah, Most Gracious, Most MercifulAssalamu’alaikum Wr. Wb.,

Welcome to the Second International Conference on Science Engineering and Technology (ICoSET 2019).The advancement of today’s computing technology, science, engineering and industrial revolution 4.0 playa big role in the sustainable development of social, economic, education, and humanity in developing coun-tries. Institute of higher education is one of many parties that need to be involved in the process. Academi-cians and researchers should promote the concept of sustainable development. The Second InternationalConference on Science, Engineering and Technology (ICoSET 2019) is organized to gather researchers todisseminate their relevant work on science, engineering and technology. The conference is co-located withThe Second International Conference on Social, Economy, Education, and Humanity (ICoSEEH 2019) atSKA Co-EX Pekanbaru Riau.

I would like to express my hearty gratitude to all participants for coming, sharing, and presenting yourresearch at this joint conference. There is a total of 84 manuscripts submitted to ICoSET 2019. Howeveronly high-quality selected papers are accepted to be presented in this event, with the acceptance rates ofICoSET 2019 is 70%. We are very grateful to all steering committees and both international and localreviewers for their valuable work. I would like to give a compliment to all co-organizers, publisher, andsponsors for their incredible supports.

Organizing such prestigious conferences was very challenging and it would be impossible to be held with-out the hard work of the program committee and organizing committee members. I would like to expressmy sincere gratitude to all committees and volunteers from Singapore Management University, Kyoto Uni-versity, Kyushu University, University of Tsukuba, Khon Kaen University, Ho Chi Minh City University ofTechnology, University of Suffolk, Universiti Teknologi Malaysia, Infrastructure University Kuala Lumpur,Universiti Malaya, Universiti Kebangsaan Malaysia, Universiti Utara Malaysia, Universiti Teknologi Mara,and Universiti Pendidikan Indonesia for providing us with so much support, advice, and assistance on allaspects of the conference. We do hope that this event will encourage collaboration among us now and in thefuture.

We wish you all find the opportunity to get rewarding technical programs, intellectual inspiration, and ex-tended networking.

Pekanbaru, 27th August 2019Dr. Arbi Haza Nasution, M.ITChair of ICoSET 2019

VII

CONTENTS

PAPERS

FULL PAPERS

Design of Community-based Ecotourism at Cengkehan and Giriloyo, Wukirsari Village, ImogiriDistrict, Bantul Regency, Special Region of YogyakartaSuhartono, Sri Mulyaningsih, Desi Kiswiranti, Sukirman, Nurwidi A. A. T. Heriyadi, Muchlis andIva Mindhayani

5

Prototype Storage Locker Security System based on Fingerprint and RFID TechnologyApri Siswanto, Hendra Gunawan and Rafiq Sanjaya 11

Feasibility Study of CO2 Flooding under Gross-split Mechanism: Simulation ApproachMuslim Abdurrahman, Wisup Bae, Adi Novriansyah, Dadan Damayandri and Bop Duana Afrireksa 15

Online Classroom Attendance System based on Cloud ComputingSri Listia Rosa and Evizal Abdul Kadir

20

Analysis of Porosity and Permeability on Channel Deposit Sandstone using Pore-gas Injection andPoint Counting in Sarilamak Area, West SumatraBayu Defitra, Tiggi Choanji and Yuniarti Yuskar

26

A Simulation Study of Downhole Water Sink Guidelines Plot Application using Real Field DataPraditya Nugraha 31

Groundwater Exploration using 2D Electrical Resistivity Imaging (ERI) at Kulim, Kedah, MalaysiaAdi Suryadi, Muhammad Habibi, Batara, Dewandra Bagus Eka Putra and Husnul Kausarian 35

Risk Identification in Management System Process Integration Which Have Impact on the Goal ofManagement System ComponentsNastasia Ester Siahaan, Leni Sagita and Yusuf Latief

41

The Performance of 3D Multi-slice Branched Surface Reconstruction on CPU-GPU PlatformNormi Abdul Hadi and Norma Alias

49

Tile-based Game Plugin for Unity EngineSalhazan Nasution, Arbi Haza Nasution and Arif Lukman Hakim 55

Image Segmentation of Nucleus Breast Cancer using Digital Image ProcessingAna Yulianti, Ause Labellapansa, Evizal Abdul Kadir, Mohana Sundaram and Mahmod Othman 64

An Integrated Framework for Social Contribution of Diabetes Self-care Management ApplicationZul Indra, Liza Trisnawati and Luluk Elvitaria 68

Spatiotemporal Analysis of Urban Land Cover: Case Study - Pekanbaru City, IndonesiaIdham Nugraha, Faizan Dalilla, Mira Hafizhah Tanjung, Rizky Ardiansyah and M. Iqbal Hisyam 74

The Effectiveness of Rice Husk Biochar Application to Metsulfuron Methyl PersistenceSubhan Arridho, Saripah Ulpah and Tengku Edy Sabli 80

Digital Forensics: Acquisition and Analysis on CCTV Digital Evidence using Static Forensic Methodbased on ISO /IEC 27037:2014Rizdqi Akbar Ramadhan, Desti Mualfah and Dedy Hariyadi

85

IX

Testing the Role of Fish Consumption Intention as MediatorJunaidi, Desi Ilona, Zaitul and Harfiandri Damanhuri 90

Segmentation of Palm Oil Leaf Disease using Zoning Feature ExtractionAuse Labellapansa, Ana Yulianti and Agus Yuliani 98

Analysis of Economy in the Improvement of Oil Production using Hydraulic Pumping Unit in X FieldMuhammad Ariyon, Novia Rita and Tribowo Setiawan 102

Construction Design and Performance of Dry Leaf Shredder with Vertical Rotation for CompostFertilizerSyawaldi

109

The Impact of Additively Coal Fly Ash toward Compressive Strength and Shear Bond Strength inDrilling Cement G ClassNovrianti, Dori Winaldi and Muhammad Ridho Efras

114

Impact of Vibration of Piling Hammer on Soil Deformation: Study Case in Highway ConstructionSection 5 Pekanbaru-DumaiFirman Syarif, Husnul Kausarian and Dewandra Bagus Eka Putra

120

Combination Playfair Cipher Algorithm and LSB Steganography for Data Text ProtectionApri Siswanto, Sri Wahyuni and Yudhi Arta 125

Fire Detection System in Peatland Area using LoRa WAN CommunicationEvizal Abdul Kadir, Hitoshi Irie and Sri Listia Rosa 130

Forest Fire Monitoring System using WSNs TechnologyEvizal Abdul Kadir, Sri Listia Rosa and Mahmod Othman 135

Multi Parameter of WSNs Sensor Node for River Water Pollution Monitoring System (Siak River,Riau-Indonesia)Evizal Abdul Kadir, Abdul Syukur, Bahruddin Saad and Sri Listia Rosa

140

Analysis for Gerund Entity Anomalies in Data ModelingDes Suryani, Yudhi Arta and Erdisna 146

The Incidence of Rhinoceros Beetle Outbreak in Public Coconut Plantation in Tanjung SimpangVillage, Indragiri Hilir, Riau ProvinceSaripah Ulpah, Nana Sutrisna, Fahroji, Suhendri Saputra and Sri Swastika

151

Mobile Application of Religious Activities for the Great Mosque Islamic Center Rokan Hulu withPush NotificationSalhazan Nasution, Arbi Haza Nasution and Fitra Yamita

155

An Augmented Reality Machine Translation AgentArbi Haza Nasution, Yoze Rizki, Salhazan Nasution and Rafi Muhammad 163

The Community Perception of Traditional Market Services in Pekanbaru City, Riau ProvincePuji Astuti, Syaifullah Rosadi, Febby Asteriani, Eka Surya Pratiwi and Thalia Amanda Putri 169

Separation of Crude Oil and Its Derivatives Spilled in Seawater by using Cobalt Ferrite OxideMohammed A, Samba, Ibrahim Ali Amar, Musa Abuadabba, Mohammed A. Alfroji, Zainab M. Salihand Tomi Erfando

175

X

Study of Open Space Utilization in Pekanbaru City, Riau ProvinceMira Hafizhah T., Febby Asteriani, Mardianto and Angelina Rulan S. 182

Application of Augmented Reality as a Multimedia Learning Media: Case Study of VideographyAhmad Zamsuri, Fadli Suandi and Rizki Novendra 188

Green Building Performance Analysis in the Stimi Campus BuildingDian Febrianti and Samsunan

194

Towing Service Ordering System based on Android: Study Case - Department of Transportation,PekanbaruPanji Rachmat Setiawan, Yudhi Arta and Rendi Sutisna

200

Biosurvey of Mercury (Hg), Cadmium (Cd), and Lead (Pb) Contamination in ReclamationIsland-Jakarta BaySalmita Salman, Achmad Sjarmidi and Salman

205

Expert System to Detect Early Depression in Adolescents using DASS 42Nesi Syafitri, Yudhi Arta, Apri Siswanto and Sonya Parlina Rizki 211

Geotechnics Analysis: Soil Hardness on Stability of Davit Kecil’s Weir in Ulu Maras, KepulauanAnambas, Kepulauan RiauMiftahul Jannah, Dewandra Bagus Eka Putra, Firman Syarif, Joni Tripardi, Nopiyanto andHusnul Kausarian

219

Support for Heritage Tourism Development: The Case of Ombilin Coal Mining Heritage ofSawahlunto, IndonesiaJonny Wongso, Desi Ilona, Zaitul and Bahrul Anif

229

Aerial Photogrammetry and Object-based Image Analysis for Bridge Mapping: A Case Study onBintan Bridge, Riau Islands, IndonesiaHusnul Kausarian, Muhammad Zainuddin Lubis, Primawati, Dewandra Bagus Eka Putra, Adi Suryadiand Batara

237

Monitoring Single Site Verification (SSV) System and Optimization BTS Network based on AndroidAbdul Syukur, Siti Rahmadhani Sabri and Yudhi Arta 243

Characterization of the Ethnobotany of Riau Province Mascot Flora (Oncosperma tigillarium (Jack)Ridl.)Desti, Fitmawati, Putri Ade Rahma Yulis and Mayta Novaliza Isda

250

Effect Stocking Density on Growth and Survival rate of Larval Selais Fish (Kryptopterus lais) Culturedin Recirculation SystemAgusnimar Muchtar and Rosyadi

254

Development of Safety Plan to Improve OHS (Occupational Health and Safety) Performance forConstruction of Dam Supporting Infrastructure based on WBS (Work Breakdown Structure)Aprilia Dhiya Ulhaq, Yusuf Latief and Rossy Armyn Machfudiyanto

258

Design of Web Login Security System using ElGamal CryptographyYudhi Arta, Hendra Pratama, Apri Siswanto, Abdul Syukur and Panji Rachmat Setiawan 268

Standard Operational Procedures Development for Government Building’s Care and MaintenanceWork of Outer Spatial and Housekeeping Component to Improve Work Effectiveness and Efficiencyusing Risk-based ApproachLasita Khaerani, Yusuf Latief and Rossy Armyn Machfudiyanto

274

XI

A Novel Correlation on MMP Prediction in CO2-LPG Injection System: A Case Study of Field X inIndonesiaPrasandi Abdul Aziz, Hendra Dwimax, Tutuka Ariadji, Steven Chandra, Wijoyo Niti Daton andRessi Bonti

285

Productivity Analysis of Frac-pack Completion in M Well with Sand Problem Indication and HighPermeability FormationHerianto, Prasandi Abdul Aziz, Wijoyo Niti Daton and Steven Chandra

291

Emulsion Treatment using Local Demulsifier from Palm OilTomi Erfando and Emre Fathan 299

Designing an IoT Framework for High Valued Crops FarmingDomingo Junior P. Ngipol and Thelma D. Palaoag 304

Consideration of the Different Pile Length Due to Soil Stress and Inner Forces of the Nailed-slabPavement System under Concentric LoadAnas Puri, Roza Mildawati and Muhammad Solihin

311

Utilization of Agricultural Waste to Be Bioethanol Sources as a Solvent on Paraffin Wax Crude OilIssuesM. K. Afdhol, F. Hidayat, M. Abdurrahman, H. Z. Lubis, R. K. Wijaya and N. P. Sari

315

The Effect of Regeneration Time of Biomass Activated Carbon using Low Temperature to ReduceFiltration Loss in Water-based Drilling FluidNur Hadziqoh, Mursyidah, Arif Rahmadani, Idham Khalid and Hasnah Binti Mohd Zaid

322

Improving the Accuracy of Features Weighted k-Nearest Neighbor using Distance WeightK. U. Syaliman, Ause Labellapansa and Ana Yulianti 326

Predicting of Oil Water Contact Level using Material Balance Modeling of a Multi-tank ReservoirMuslim Abdurrahman, Bop Duana Afrireksa, Hyundon Shin and Adi Novriansyah 331

Chip Formation and Shear Plane Angle Analysis on Carbon Steel Drilling using Solid Carbide ToolsRieza Zulrian Aldio

337

A Solution to Increase Natuna D Alpha’s Resource Utilization by Cryogenic Distillation: ConceptualDesign & Sensitivity StudyWijoyo Niti Daton, Ezra Revolin, Siptian Nugrahawan, Prasandi Abdul Aziz, Tutuka Ariadji,Steven Chandra and J. A. Nainggolan

342

Design of Volcanic Educational-based Natural Tourism at Giriloyo, Wukirsari Village, ImogiriDistrict, Bantul Regency, Yogyakarta-IndonesiaSri Mulyaningsih

349

Four Types of Moral Holistic Values for Revolutionizing the Big Data Analytics in IoT-basedApplicationsNorma Alias

357

AUTHOR INDEX 363

XII

PAPERS

FULL PAPERS

Design of Community-based Ecotourism at Cengkehan and Giriloyo,Wukirsari Village, Imogiri District, Bantul Regency, Special Region of

Yogyakarta

Suhartono1, Sri Mulyaningsih2, Desi Kiswiranti2, Sukirman1, Nurwidi A. A. T. Heriyadi2, Muchlis2

and Iva Mindhayani11Geological Engineering of FTM-IST AKPRIND Yogyakarta,Jl. Kalisahak No. 28 Yogyakarta

2Industrial Engineering, Faculty of Engiineering, Universitas Widya Mataram, Komplek Mangkubumen, Yogyakartasri m, nurwidi, [email protected], desikiswiranti, ivamindhayani, sukirman.ars, [email protected]

Keywords: Design, Community-Based, Ecotourism, Correlation and Cengkehan-Giriloyo.

Abstract: Ecotourism at study area is a tourism concept that presents unspoiled tourism and preserves to improving itssustainability. This ecotourism was defined by the local people contribution to the conservation of the landby mass movements potential in study area. People live in Cengkehan and Giriloyo are very concerned to theenvironmental preservation around them. The aim of this paper is to obtain the conservation in developingCommunity-Based Ecotourism (CBE) enterprises, supported by the partnerships of communities with thegovernment, non-government and the private sectors. This study attempts to evaluate those partners most ableto support various initiatives. The Giriloyo-Cengkehan CBE purposes to create a local ecotourism and itsinfluence to the CBE marketing development. The study exposed that the nature of Cengkehan-Giriloyo’sCBE has positive correlations between the community capacity carrying and the role of the developingCBS, includes its management and sustainability. The high expectation for the Giriloyo-Cengkehan CBEcan perceive much more positive impacts than the negative impacts into the environmental, economic, andsocio-cultural as a result of the ecotourism. They can manage all of activities and attraction they offer, andprovide lodgistic, ccomodation and amenities supported by the goverment policy as well as accessibilities andother facilities within the destination area.

1 INTRODUCTION

Ecotourism has grown in the last decade in Indonesia;in hamlets to inland and former mining areas. Duringthis period, discussions in ecotourism to thegeoconservation and environmental sustainabilitycontribution, have been deeply wide-reaching.Indonesian Guides Association (HPI: HimpunanPramuwisata Indonesia) has considered and usedecotourism principles in developing itineraries,training guides, and marketing products. In the lastfive years, the guidelines have been formulated bylegal organizations of HPI. Many ecotourism businessowners and travel agents were also already practicingthese standards to obtain consumers not only locallybut also worldwide organizations (Sproule, 1996;Aczel et al., 2006; Arce et al., 2014). This has beenan important step in setting standards within the fieldof ecotourism.

An ancient volcano supported by field ofecotourism in the form of traditional market,

cruising river and batik craft were identified atGiriloyo and Cengkehan, Wukirsari Village, ImogiriDistrict, Bantul Regency (Figure 1). Geoparks,as an advance protection of natural and geologicalheritages, governing the important role in developinggeotourism (Bray and Rodriguez-Marek, 2004;Budayana, 2017; Edwards, 1997). Together withecotourism and geotourism, the establishment ofgeoparks can generate new job opportunities, neweconomic activities and additional sources of income,especially in rural regions. Study area is coveredby Gunung Sewu Geopark in the Southern Mountainarea, it encourages in constructing the local productsand local handicrafts involved within the geo-andeco-tourism and other geo- and eco-products.

Previous study identified Tertiary superimposedvolcanism, depositing basaltic volcanic rocks ofKebo-Butak Formation and andesitic volcanicrocks of Nglanggeran Formation (Mulyaningsihand Suhartono, ) Inflation and deflation intensivelycontrolled the study area; normal and shear faults as

Suhartono, Mulyaningsih, S., Kiswiranti, D., Sukirman, Heriyadi, N., Muchlis and Mindhayani, I.Design of Community-based Ecotourism at Cengkehan and Giriloyo, Wukirsari Village, Imogiri District, Bantul Regency, Special Region of Yogyakarta.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 5-10ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

5

products of the volcanism are potentially resultinglandslide and other mass movements. The aim ofstudy is to obtain the conservation in developingcommunity-based ecotourism, geotourism andgeoconservation supported by the partnerships ofcommunities with government, non-government andprivate sectors. This study attempts to evaluate thosepartners most able to support various initiatives.

Figure 1: Situation map of study area.

2 METHOD

The study was constricted to design, develop, andanalyze parameters, variables, tools and methods thatused to be applied in managing the compliance of eco-and geo-tourism guidelines. Questionnaires weredesigned with the respondents as a manner comingfrom the consumers and the tourists that visited toGiriloyo-Cengkehan. Those were completed withinapproximately five-ten minutes. It consisted of thefollowing six sections with the relevant numbers ofthe questions per section listed as follow:

• the accessibility facilities to Cengkehan (the endthe tour)

• activity offered, visitor information and itseducation provided during the trip

• the available local accomodation (guest house,hotel, homestay and restaurants)

• the guide tours and the management (touroperator contributions to conservation and localdevelopment programs)

• the amenity (ATM, Parking area, shop, market, et.al.)

• socio-demographic information about ecotourists(Hermawan and Brahmanto, 2017).

The questionnaire was designed that at list sixor seven of the ten guide-lines proffered by themanagement could be evaluated by the consumer.

Questionnaires were also provided to the localecotourism; i.e for the manager, guide toursand the community who manages this ecotourism.These questionnaires aim to evaluate the successof the running management. Those consistof the perceptions of environmental, economicand socio-cultural impacts between residents ofa traditional tourism area and a recently createdecotourism area.

All data resulted during the research were analizedusing statistic method; including correlation test andlinear regresion.

3 THEORY

Ecotourism Society defines it as responsible travelto natural areas which conserves the environmentand sustains the well-being of local people. Inthe basic concept, ecotourism enterprises thatowned and managed by the community is calledas Community-Based Ecotourism (CBE). In thiscase, CBE responsibles to conserve, enterprise, anddevelop the community. (Wang et al., 2002) definedtwo kinds of community, i.e. direct and indirectcomunities with direct and indirect beneficiaries.Direct community included members of the managingcommittee and workers. Indirect community includedthe broader community who selected the managementcommittee, namely interconnection service providers,travel agents, lodging and restaurant entrepreneurs,market traders and others. Direct beneficiariesincluded employees, craft producers, guides, andcommittee members, while indirect beneficiariesincluded the wider community as recipients ofcommunity development projects funded by tourismrevenues.

People or groups of people can be defined asecotourism community, by the role of the groups.There are local comunities and broadband comunities.The most successful CBE projects have startedin the success of the information system; by thedissemination of information, that was chain fromone community to another. Industry 4.0 involvesthat chain. Most activity, such as marketingecotourism, are required to develop the needs ofinternet. For this reason, Kozinets (1999) proposed’virtual communities’ that able to push the growthof quantity, interests, and influence transformingtraditional tourism into ecotourism. First of all,”virtual community” is considering to the unique

ICoSET 2019 - Second International Conference on Science, Engineering and Technology

6

characteristics of community in cyberspace, it’san abstraction and empirical application virtualcommunity as place, as symbol, and as virtual. Thiscommunity is groups of people who interact withspecific purposes, under the governance of certainpolicies, and with the certain facilitation (Figure 2).

Figure 2: A conceptual model for the definition of virtualcommunity (Wang et al., 2002).

4 RESULTS

4.1 Secondary Data

Assessment of the Giriloyo ancient volcano analyzedgently to undulated topography sloping to 5-10oat distance areas, undulated to steeply hills atCengkehan to Nogosari sloping to 10-30, roughyelevated hills near Watulumbung that sloping around30-60 and very steeply scarpments with 60-70 onupper cliffes (Figure 3). Creeps are recognizedalong Watulumbung and the cliff of Mount Makbul.Those were influenced by the ancient superimposedvolcanism happened during Early to Middle Miocene(Mulyaningsih and Suhartono, ).

Landslides and others mass movements at studyareas can result in enormous casualties and hugeeconomic losses, such as hapenned on 17 March 2019(Mulyaningsih and Suhartono, ). So that it necesarryto mitigate. Mulyaningsih at al. (2019a in thisvolume) proposed that design to the geoconservationof the potential mass movements can be package tobe eco- and geo-tourism destination. The geotourismaplication is supported by the presence of volcanic

rocks exposed along Cengkehan River. It can bedefined as central facies volcano.

Figure 3: Digital Elevation Model (DEM) at study area.

(Mulyaningsih and Suhartono, ) mapped anddescribed volcanic sequences of Kebo-Butak andNglanggeran Formations. Kebo-Butak Formationwas exposed at Giriloyo, consists of black tuffintersects with brecciated and compacted basalt lava,then covered by less calcareous sedimentarry rockshaving an age of N5-6 (Early Miocene)(Eliezer et al.,2019; Farsani et al., 2011; Hadian et al., 2016). LowerNglanggeran Formation exposed at Cengkehan,it lie on the Kebo-Butak Formation, consist ofcreammy color of coarse tuff and lapillistone thatcoarsening upward and replaced with intersectingsof thick layers of breccia, lava and lapillistonein pyroxene-rich basalt composition. Those werecovered by Younger Nglanggeran Formation, thatconsists of agglomerate, andesitic lava and dike,in unconformably relationship. The YoungerNglanggeran was exposed at Watulumbung. Theoutcrops of the volcanic rocks are ilustrated in Figure4.

(Mulyaningsih and Suhartono, ) argued that thosevolcanic rocks strongly supported the geologicalconditions, but the inflation and deflation duringthe volcanism in it had already deformed them.Those resulted south-west-northeast normal faults(N290-320E), north-south shear faults (0-15E), andoblique normal faults (northwest-southeast). thatall of them have potential landslides. Accordingto (Mulyaningsih and Suhartono, ), the potentiallandslides and other mass movements could beminimized using terracing technics collaborate withbamboo park.

Design of Community-based Ecotourism at Cengkehan and Giriloyo, Wukirsari Village, Imogiri District, Bantul Regency, Special Region ofYogyakarta

7

4.2 Field Data Record

Tools used to comprehensive sustainabilityassessments consist of correlation test to thecurrent ecotourism destinations (i.e. BrecciaCliff-Prambanan, Nglanggeran Ancient VolcanoGeotourism, Mangunan Ecotourism, and DlingoEcotourism), covering sociocultural, economic andenvironmental issues. It considers to their strengths,weaknesses, threats and opportunities of thesite-specific applicability. Those intended to facilitateGiriloyo-Cengkehan’s ecotourism that coveredsustainability indicators, environmental impactassessment, life cycle assessment, environmentalaudits, ecological footprints, multi-criteria analysisand adaptive environmental assessment (Schianetzet al., 2007).

The implementation of sustainability at Giriloyoecotourism destination is particularly significant forits viable target; the important of sustainability issuesare scope and responsibility of its organisation andmanagement. Hotels at study area are in minimized;

4.2.1 Correlation Analyses

In CBE, relationship between managers, owners,local community and consmers characteristics withtheir effort in the comunity capacity for tourismdevelopment is very important. It was identified bycompleting quistionnaire, as a primary data by 149respondents. Table 1 shows details of descriptivestatistics for 149 people arriving Giriloyo-CengkehanEcotourism, consist of workers, manager, tour guides,local community and consumers. They were atTraditional Market Tour Community, CengkehanCruising River Community, and Batik Craft. Outof the 149 people community, 40% were female and60% were male, with an average age of 29 years. Theyoungest participant was 16 years and the eldest onewas 67 years. Table 1 is frequency distribution of theresponden coming from the comitee community.

Table 1: Frequency distributions of Respondents’Demographic Profiles (N=149)

No Education Σ % Age(years) Σ %

1 Student/S1 25 16.78 <20 25 16.782 S1 38 25.5 21-25 26 17.453 S2 27 18.12 26-35 22 14.774 Others 22 14.77 35-50 27 18.125 High School 37 24.83 >50 49 32.89

This content information writen in thequestionarry provides to introduce the futureecotourism development activities. To identify therelationships between tourism variables under studied

used Pearson coefficient correlation and Spearmanrho coefficient correlation. The utilization of Pearsonmoment coefficient is attended to the variablescorrelated that expressed as interval data.

Table 2: Frequency distributions of infrastructuredevelopments (N=149)

No Variable Category Freq. %

1. Respondent

Students/S1 45 30.2S1 58 38.93S2 47 31.54Others 42 28.19

2.

<20 45 30.221-25 46 30.8726-35 42 28.1935 - 50 47 31.54>50 69 46.31

3.

Internet Agree 65 43.62Disagree 24 16.11

Wifi Agree 53 35.57Disagree 36 24.16

Large Bandwith Agree 65 43.62Disagree 24 16.11

4.

Activity Outing track 40 26.85Education 35 23.49Exhibition 29 19.46Crafting 25 16.78

5. Attraction

Outbond 50 33.56Culture 24 16.11Museum 28 18.79Batik Craft 27 18.12

6. Lodging

Hotel 30 20.13Guesthouse 40 26.85Inn 30 20.13Caffee / Bar 22 14.77Saloon 22 14.77Restaurant 65 43.62

7. Ammenity

Parking Area 64 42.95ATM 61 40.94Supermarket 27 18.12Traditional market 57 38.26Shop 25 16.78

8. Accessibility Require roadwork 43 28.86Lane setting 46 30.87

9. Management Improving ecotourism 59 39.6Traditional tourism 30 20.13

10. Sustainability CBE 57 38.26Outside Investment 32 21.48

As depicted in Table 2 and 3 there weresignificant positive correlation between age andbackground education and the sustainability of theGiriloyo-Cengkehan’s ecotourism development (r =0.416, N = 149, p = 0.000, two-tailed). Positivecorrelation also occured between age the communitycapacity carrying (improving CBE and sustainability;r = 0.402, N = 149, p = 0.001, two-tailed); positivecorrelation between the community capacity carryingand the improvements of CBE (r = 0.462, N = 149, p= 0.000, two-tailed); and positive correlation betweenthe further involving CBE and the sustainability (r =0.601, N = 149, p = 0.000, two-tailed).

The Spearman rho was applied during theanalyses, expressed as a rank to determine the


8

Figure 4: The volcanic rocks exposed at study area; a. Agglomerate; b. Dike; c. Altered rocks with sulphid minerals, d.Volcanic neck; and e. Lava with collumnar joints. Those are used to deposited very close to the crater or within the crater.

Table 3: Pearsonn Correlation between respondent’sdemographic profile and intending infrastructuredevelopments (N= 149)

1 2 3 4 5

1 Age 1

2 Background Education **0.416 1

3 Improving CBE **0.727 **0.803 1

4 Management 0.281** 0.109 0.177 1

5 Sustainbility 0.416** 0.402** 0.462** 0.601** 1**p<0.05

relationship between education, tourism activity,improving management and sustainability in term ofcarrying community capacity. Because the variableswere on a rank scale, Spearman rank correlationcoefficients were computed between the variables(Aczel et al., 2006). The relationship of eachvariable was statistically significant, there were somepositive correlations between age, education, activityoffered in CBT management, sustainability and theinfrastructure developments (rs = 0.401,N = 149,p < 0.000, two-tailed). There was also significantcorrelation between offering tourism activity andcommunity capacity carrying (rs = 0.644, N = 149,p < 0.000, two-tailed). Table 3 also illustrates thatthere was a negative correlation between background

education and its management (rs = -0.214, N = 149,p < 0.004, two-tailed), a tourism sustainability (rs =0.546, N = 2, p < 0.000, two-tailed). Table 4 showsthe result of Spearman correlation.

Table 4: Spearman Correlation between background ofeducation and community capacity carrying(N= 149)

r p1 Background Education 0.401** 0.0002 Tourisme offered 0.644** 0.0003 Management -0.214** -.0004 Infrastructure 0.546** 0.0005 Sustainability .0.356** 0.000

**p<.05

The result of the rs showed that there werecorrelations between the educational background ofthe respondent, tourism activity offered, desiredmanagement system, infrastructure development,and the expected sustainability within the carryingcommunity capacity. Although, community resourceswere identified as uneffective elements in buildingcapacity for tourism development, the findings of thisstudy in fact illustrate that community characteristicscan contribute to the community capacity building fortourism development.

Design of Community-based Ecotourism at Cengkehan and Giriloyo, Wukirsari Village, Imogiri District, Bantul Regency, Special Region ofYogyakarta

9

5 DISCUSSION

This study has stated that the tourism community,which plays a role in the Giriloyo-Cengkehanecotourism development has significant effects onthe local economic development, especially on thecommunity development effort. Two points of thekey, coming from the respondents were educationalbackground and age. People who have highereducation have more activate in the (eco-) tourismdevelopment; it shows that educational backgroundand age have positive relationship to the communitycapacity carrying. People with 26-35 years oldhave more involved and responsible in ecotourismdevelopment.

A critical element in carrying community capacityand CBE development is defined as a group ofcommunity who able to influence policy, opinion, andaction in building BCE by their official role, title, andage (seniority) in the local community. Communitymanagement was an important element, role andvital to successful CBE. Hence, understandingrelationship between the community characteristicsand their attempt on building CBE is important forfurther planning and marketing Giriloyo-Cengkehan’secotourism.

6 CONCLUSIONS

CBE is able to develop at Giriloyo-Cengkehan, by itscommunity characteristic; as a central of batik craft,educational geotourism, cruising river outbond andtheir traditional market. By CBE, from individualmanagement that is not or less effective to be moreeffective in one CBE management. It also applicableto the virtual and real marketing management, by bothreal and virtual community-based ecotourism.

ACKNOWLEDGEMENTS

Our greetings attend to the Ministry of Researchand High Education (RISTEKDIKTI) which wasfunding the research by the first and second yearsof Penelitian Terapan Unggulan Perguruan Tinggi(PTUPT Scema) on 2018-2019. Special gratitudestend to the goverment of Bantul Regency, the headand staff of Wukirsari, the Giriloyo and Cengkehancommunities, POKDARWIS, as well as FORCIBARYABHATA, who have provided the researchfacilities, accompanied the research and gave avariety of very warm supports. A big appreciation is

supervised to LPPM IST AKPRIND Yogyakarta forthe opportunities to reach the PTUPT grant.

REFERENCES

Aczel, A. D., Sounderpandian, J., and Patille, L. (2006).Student problem solving guide for use with completebusiness statistics. McGraw-Hill, Irwin.

Arce, J. L., Walker, J., and Keppie, J. D. (2014).Petrology of two contrasting mexican volcanoes,the chiapanecan (el chichon) and central american(tacana) volcanic belts: the result of rift-versussubduction-related volcanism. International GeologyReview, 56(4):501–524.

Bray, J. D. and Rodriguez-Marek, A. (2004).Characterization of forward-directivity groundmotions in the near-fault region. Soil dynamics andearthquake engineering, 24(11):815–828.

Budayana, I. (2017). Geologi dan identifikasi fasies gunungapi berdasarkan stratigrafi batuan di daerah mangunandan sekitarnya. Kecamatan Dlingo, Kabupaten BantulDaerah Istimewa Yogyakarta, Laporan Sripsi Tipe-1.

Edwards, R. N. (1997). On the resource evaluationof marine gas hydrate deposits using sea-floortransient electric dipole-dipole methods. Geophysics,62(1):63–74.

Eliezer, I., Winarno, T., and Ali, R. K. (2019). Petrogenesislava bantal nampurejo di dusun kalinampu dansekitarnya, desa jarum, kecamatan bayat, kabupatenklaten, provinsi jawa tengah. Jurnal Geosains danTeknologi, 2(1):33–41.

Farsani, N. T., Coelho, C., and Costa, C. (2011).Geotourism and geoparks as novel strategiesfor socio-economic development in rural areas.International Journal of Tourism Research,13(1):68–81.

Hadian, M. S. D., Yuliwati, A. K., Pribadi, K. N., et al.(2016). Increasing community environmentalawareness through geodiversity conservationactivities at ciletuh, sukabumi, west java. Journal ofEnvironmental Management & Tourism, 7(2):14.

Hermawan, H. and Brahmanto, E. (2017). Geowisata:Perencanaan pariwisata berbasis konservasi.

Mulyaningsih, S. and Suhartono. dan Mindayani. E.,(2019b).

Schianetz, K., Kavanagh, L., and Lockington, D.(2007). Concepts and tools for comprehensivesustainability assessments for tourism destinations: Acomparative review. Journal of Sustainable Tourism,15(4):369–389.

Sproule, K. W. (1996). Community-based ecotourismdevelopment: Identifying partners in the process.The ecotourism equation: Measuring the impacts,99:233–250.

Wang, Y., Yu, Q., and Fesenmaier, D. R. (2002).Defining the virtual tourist community: implicationsfor tourism marketing. Tourism management,23(4):407–417.


10

Prototype Storage Locker Security System based on Fingerprint andRFID Technology

Apri Siswanto, Hendra Gunawan, Rafiq SanjayaDepartment of Informatics Engineering, Faculty of Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

aprisiswanto, [email protected], [email protected]

Keywords: Security, Fingerprint, RFID, Sensor, Automatic Locker.

Abstract: Locker Security System for storing goods is essential in public facilities such as at the bus station, airport, mallor library. Today’s commercially available security locker systems require complex system configurations thatinvolve high costs. For that, a more accessible and cheaper alternative is needed. In this study, a locker securitysystem was created using Arduino-based fingerprint biometrics. The purpose of this study is to improve thesecurity of lockers in goods storage services and can reduce theft by using fingerprint sensors and RFIDsensors. The research methods in this study include library research, system design, hardware design, andsoftware design. Based on the results testing both on the hardware and on the software that has been madeand looking at the objectives of the research, it can be summarized as follows: this equipment can be used asa storage locker for items that have good security.

1 INTRODUCTION

Storage locker is an essential facility in public placessuch as stations, shopping centres, libraries, and inrecreational areas, etc. As we know, the qualityof service from luggage storage dramatically affectsthe level of satisfaction of consumers (Erziana et al.,2018; Arta, 2017). Many things can become servicequality standards for goods storage such as in terms ofthe safety of goods that we will leave, the accuracy ofreturning goods so that there are no swapped goods,damage to goods and speed in service so as not tomake customers wait or queue (Moskowitz et al.,2002).

Several lockers in public area still using processmanually. The process is by the sign with paper or akey that has a number that matches with a locker onthe items we leave. In this case, the consumer canbe harmed if the number he has is taken by someoneelse. Then the officer is also difficult to remember theowner of the good who left the locker. The officeron duty is only focused on matching the numbergiven by the consumer with the number listed in thelocker where the thing is stored (Gangi and Gollapudi,2013).

With the rapid development of technology, almostall work done by humans is facilitated with thesupport of electronic devices. In the case of storageof items such as cabinets, drawers, and lockers, many

currently use electronic devices as a support level ofsecurity. The method is carried out, starting fromusing passwords, RFID and biometric authentication.Biometric functions are to recognize physical featuressuch as voice recognition, eye retinal scans, facialscans, and fingerprint scans. In order to communicateseveral security systems with a variety of tools, amicrocontroller is needed since easily understood andused by humans. One microcontroller that is widelyused today is Arduino (Siswanto et al., 2017; ARZAFand V., 2016). From the background above, it wasdeemed necessary to build a luggage storage lockerwith a fingerprint biometric security system (Patelet al., 2016).

2 RELATED RESEARCH

Research related to this area is, (Budiharjo and Milah,2014) proposed a room door security system withRFID and password using Arduino Uno. The systemis made using RFID sensors and finger passwordsas input and is processed by the microcontroller toopen solenoids. Then Siswanto et al. (2017) createda home door lock security system using fingerprinttechnology and an Arduino microcontroller.

(Khoirunnufus and Sutanto, 2013) designed asecure security system based on the Atmega8535microcontroller. The hardware in the system

Siswanto, A., Gunawan, H. and Sanjaya, R.Prototype Storage Locker Security System based on Fingerprint and RFID Technology.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 11-14ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

11

consists of a minimum system circuit ATMega8535microcontroller as a system controller, dc motordriver circuit which functions to control dc motors todrive locks on the safe door, a relay driver circuit thatserves to turn on the siren, as well as a power supplycircuit that functions as voltage source.

Then the research of DWI UTOMO ARZAF(2016), he proposed a security system for goodsstorage using microcontroller based RFID andpasswords. This safety deposit box security systemwas built with RFID and password sensors basedon the Arduino ATMega 2560 microcontroller thatuses LCD as an information medium. To open theitem storage box, the user must enter a password anddetection of the card, after the password and card aredetected correctly it will be processed on the ArduinoATmega 2560 microcontroller. Solenoid is used as anopening and security door closure for the storage box.

3 RESEARCH METHOD

The methodology used in this study is experimentalwhich is divided into five steps (Hossain et al., 2016):

• Analysis Phase

Analysis of the security system of theplace-to-keep lockers that are currently stillusing manual methods. First, the user goes tothe clerk to register. after that the consumerwill make a payment for the rental fee for theitem storage locker then the officer will provideinformation on the locker that the consumerwill use along with the locker key.The solution to dealing with these problemsis the need for a system that can improvethe security system of luggage storage lockers.Where the process of the user is paid to thecashier to determine the number of lockers thatwill be used. Then the user will scan thefingerprint which is used as a medium to detectdata from the user. The user data will be storedin the Arduino controller for the authenticationprocess if the locker has been used.

• Design system

In this automatic locker design, the maincomponents consist of Arduino Uno as thesystem controller centre, fingerprint sensor andRFID sensor as input and solenoid as output.Before designing hardware and software, afunctional block design system is needed in theform of block diagrams that explain the worksystem as in figure 1.

Figure 1: Hardware scheme locker security system.

In designing the scheme, the device explains theinstallation relationship of the device between thefingerprint sensor, RFID sensor, relay and solenoidwith the microcontroller so that it can be connectedto each other and become a complete system.

After designing a hardware scheme, the next stepis to determine the program logic that will be appliedto the system to be used. Then make coding that willbe implemented on the system. The flowchart of thesystem work process flow as shown in Figure 2.

4 RESULT AND DISCUSSION

Based on the analysis and design that has beendone, the design of goods storage lockers using thisfingerprint sensor has been realized, it is necessaryto do various tests to find out how the device works,as well as testing based on different fingerprintand RFID conditions, weaknesses and limitations offunction specifications. system that has been created.

4.1 Fingerprint Enrolment

This test is done to find out whether this fingerprintsensor can work properly, first the test is done with theauthor’s fingerprint which is using the thumb fingeron the left hand, before the testing is done by theauthor’s left hand thumbprint has been registered onthe sensor fingerprint

The testing step is to attach the left thumb tothe fingerprint sensor area, after the sensor hassuccessfully read and identified the correspondingfingerprint data, the solenoid that was in a defectiveposition or closed will be active so that the door canbe opened.

The next step is testing the response of thefingerprint sensor. After testing it can be concludedthat it takes as long as 5 seconds for the system towork properly and recognize the fingerprint of the lefthand thumb until the door opens.


12

Figure 2: Flow chart locker security system

Figure 3: Embedding Process

4.2 Sensor RFID Testing

This test is conducted to find out whether RFIDsensors can work properly, first the author tries to doa test using a card whose ID has been stored on the

Table 1: Result Hand Position

Hand Position Finger part Result

Left Hand

Thumb SuccessIndex finger UnsuccessMiddle finger UnsuccessRing finger UnsuccessLittle finger Unsuccess

Right Hand

Thumb UnsuccessIndex finger UnsuccessMiddle finger UnsuccessRing finger UnsuccessLittle finger Unsuccess

Table 2: Finger Position

Fingerprint PositionEnrolment

time(seconds)

Result

Thumb left hand

1 Unsuccess2 Unsuccess3 Unsuccess4 Unsuccess5 Success

Arduino microcontroller.

Figure 4: Testing RFID

The testing step is to attach the RFID card whosedata has been registered in the system so whathappens is that the RFID sensor successfully readsand identifies the appropriate data, the solenoid thatwas in a defective position or closed will be active sothat the door can be opened.

Table 3: RFID Test Result

RFID Test scenario ResultRFID cardenrolment insystem

attach the card thathas been registeredto the RFID sensor

The system respondsand the locker door issuccessfully opened

Other card

Attach another cardthat has not beenregistered to the RFIDsensor

The system refusesand the locker doorcannot be opened

In the next stage, the distance sensor can be readto the ID card so that the locker can be opened. After

Prototype Storage Locker Security System based on Fingerprint and RFID Technology

13

testing is done it can be concluded that at a distanceof 1.5cm, the sensor can read the RFID card.

Table 4: Result

RFID Distance (cm) Result

RFID Card

4 Unscuccess3 Unsuccess2 Success1 Success0,5 Success

5 CONCLUSION

Based on the analysis and discussion of the lockersecurity system using Arduino-based fingerprintbiometrics, it can be concluded that Arduino Uno canbe used as the main control in assembling severalcomponents into an intact system so that the securitysystem of this locker can increase consumers’ senseof security and comfort. when you want to depositgoods and also can reduce the occurrence of criminalacts that can harm the consumer.

REFERENCES

Arta, Y. (2017). Implementasi intrusion detection systempada rule based system menggunakan sniffer modepada jaringan lokal. IT Journal Research andDevelopment, 2(1):43–50.

ARZAF, D. U. and V. (2016). Sistem KeamananKotak Penyimpanan Barang Menggunakan Rfid DanPassword Berbasis Mikrokontroller. PoliteknikNegeri Padang.

Budiharjo, S. and Milah, S. (2014). Keamanan PintuRuangan Dengan Rfid Dan Password MenggunakanArduino Uno. J. ICT Penelit. dan Penerapan Teknol.

Erziana, Y., Mutiara, G. A., and Periyadi, P. (2018).Perancangan dan implementasi untuk membukaswitch locker penyimpanan barang berbasis facerecognition dan fingerprint. eProceedings of AppliedScience, 4(3).

Gangi, R. R. and Gollapudi, S. (2013). Locker openingand closing system using rfid fingerprint password andgsm. International Journal of Emerging Trends &Technology in Computer Science, 2(2).

Hossain, M. A., Hossain, M. B., Uddin, M. S., andImtiaz, S. M. (2016). Performance analysis ofdifferent cryptography algorithms. InternationalJournal of Advanced Research in Computer Scienceand Software Engineering, 6(3).

Khoirunnufus, N. S. and Sutanto, H. (2013). RancangBangun Sistem Pengaman Brankas BerbasisMikrokontroler Atmega8535. Diponegoro University.

Moskowitz, I. S., Longdon, G. E., and Chang, L. (2002). Anew paradigm hidden in steganography: CRC Press.

Patel, K. K., Patel, S. M., et al. (2016). Internet of things-iot:definition, characteristics, architecture, enablingtechnologies, application & future challenges.International journal of engineering science andcomputing, 6(5).

Siswanto, A., Yulianti, A., and Costaner, L. (2017).Arsitektur Sistem Keamanan Rumah DenganMenggunakan Teknologi Biometrik Sidik JariBerbasis Arduino. Paper presented at the SeminarNasional Aptikom 2017.


14

Feasibility Study of CO2 Flooding under Gross-split Mechanism:Simulation Approach

Muslim Abdurrahman1, Wisup Bae2, Adi Novriansyah1, Dadan Damayandri3 and Bop DuanaAfrireksa4

1Department of Petroleum Engineering, Universitas Islam Riau,Pekanbaru, Indonesia2Sejong University, South Korea

3LEMIGAS, Indonesia4 Inha University, South Korea

muslim, [email protected], [email protected], [email protected], [email protected]

Keywords: CO2, Simulation Study, WAG, Gross Split, NPV

Abstract: Importance of Carbon Dioxide (CO2) injection into the subsurface reservoir is essential since the concern ofglobal warming and climate change issues in Indonesia. Selecting the oil reservoir as a candidate for a storagesite is an attractive option due to CO2 gas utilization is effective for Enhanced Oil Recovery (EOR) purpose.Continuous and Water-Alternating-Gas (WAG) CO2 flooding are the most commonly applied scenarios in theoil and gas industries. Considering the EOR side, choosing an appropriate scenario is mandatory for costefficiency reason and influences the oil share amount between the Indonesian Government and operator underthe gross-split mechanism. Therefore, by using a simulation approach, the feasibility of continuous and WAGCO2 injection is observed to decide the most financially attractive choice. Simulation results reveal a WAGscenario recovers slightly more oil compare to continuous injection scheme. Application of gross-split underbase-share makes both injection strategies unattractive for investors. An adjustment of government-contractorshare is required to improve the feasibility of the project.

1 INTRODUCTION

As a part of greenhouse gas (GHG) pollutant, CarbonDioxide (CO2) emission issue becomes a majorconcern of major countries. Through The KyotoProtocol and Paris Agreement, most countries agreedto reduce CO2 emission level before 2050 dueto avoid the catastrophic effect of global warmingand climate change phenomena. Carbon Captureand Storage (CCS) is the only effective scheme toovercome this problem (Agency, 2016). However,storing CO2 in the aquifer is not financially satisfiedsince CO2 is injected into the storage site withoutgaining any benefit during this activity. This storymay sound interesting if CO2 storage is performed inan oil reservoir.

Besides act as a storage site, injecting CO2in oil reservoir may bring another benefit in formoil production enhancement, commonly known asCO2-Enhanced Oil Recovery (CO2-EOR). CO2-EORhas successfully implemented in North America formore than a decade, either using the natural or

anthropogenic source (Whittaker et al., 2011; Jishunet al., 2015). Mostly CO2 Flooding Targets crudeoil contains high intermediate component becausethe miscible condition of CO2 and crude oil canbe achieved under reservoir condition (Abedini andTorabi, 2014). Minimum Miscibility Pressure (MMP)determination is mandatory in designing the injectionscenario. MMP can be determined through slim-tube,swelling, vanishing interfacial tension, and risingbubble experiments. Moreover, PVT and slimtubesimulation methods are capable to estimate MMPwith a reasonable gap with experimental work(Abdurrahman et al., 2015).

Besides MMP, Deciding the injection scheme isalso important for CO2 flooding because it relatesto the efficiency of CO2 utilization in displacingresidual oil. In terms of CO2 utilization factor.Statistically, more than one barrel (bbl) Oil can beproduced by injecting 1 million standard cubic feetof CO2 (Azzolina et al., 2015). CO2 utilizationfactor implicitly has an effect to the feasibility ofthe CO2 flooding project because it correlates to how

Abdurrahman, M., Bae, W., Novriansyah, A., Damayandri, D. and Afrireksa, B.Feasibility Study of CO2 Flooding under Gross-split Mechanism: Simulation Approach.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 15-19ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

15

much CO2 gas should be provided, i.e., how muchfund is required for purchasing CO2 or constructingCO2 anthropogenic capture facilities. Deciding touse CO2 from CCS activity potentially reduce theCCS cost itself (Rubin et al., 2015). Therefore,CO2-EOR, either from natural or anthropogenic,i.e., from CCS, may bring a financial interest ifproperly implemented, including the injection schemeselection.

Deciding the most suitable scheme of CO2flooding is risky and relates to the oil share betweenthe Indonesian government and operator becauseIndonesia adopts production share mechanism.Indonesia adopted a relatively new oil sharemechanism, known as gross-split. This mechanismis officially introduced and effectively valid since2017. This new mechanism still has to be improvedbecause indicating an undesirable profit for theoperator, feasibility study of CO2 by consideringinjection scheme under gross-split mechanism isanother interesting topic for the researchers (Irhamand Julyus, 2018).

This Paper analyses under simulation methodthe feasibility of CO2 flooding scheme by usinggross-split mechanism. Two injection strategies, CO2Continuous injection and CO2 Water Alternating Gas(WAG) are compared their capability in recoveringresidual oil after primary stage and also feasibilityduring CO2 flooding stage. Mathematical modelrepresents one of Indonesia oil field conditionwas generated by using BUILDER generator andsimulated under GEM simulator. Both of thesemodules are licensed under CMG Software. Resultsfrom the GEM simulator will be analyzed itsfeasibility for each injection scenario. Injectionscenario is decided by considering the economicparameter such as NPV and IRR.

2 METHODOLOGY

The reservoir grid model from Indonesia oil field isused for demonstrating the field-scale CO2 floodingin this study. This grid model consists of morethan 7,800 cells with 56, 46, and 3 cells along x,y, and z directions (represented as i, j, and k in thesoftware). Figure 1 shows the grid model with itsgrid-top parameter. The average permeability is quitelow, ranged from 30 to 100 millidarcy (md). Therange of porosity of 0.13 to 0.19. The pore-volume ofthis model is 0.83 billion reservoir cubic feet (cuft).Figure 2 and 3 depict the relative permeability (kr)plot for water-oil and gas-oil systems, respectively.The relative permeability model in this study is

obtained directly simulation study (Millah, 2014).In the oil-water system, kr is plotted over watersaturation (sw) and gas saturation (sg) for gas- oilsystem. Subscript o, w, and g in figure 2 and 3 areoil, water, and gas. Twelve injectors are planned toinject CO2 under continuous and WAG scenarios andthe performance will be analyzed based on productiondata on 5 production wells (location of the wellsare shown in Figure. 4). Total injection volume islimited on 0.6 PV due to economic reason and the 1:1WAG ratio is selected because this ratio is common infield-scale operation (Christensen et al., 1998). 2%Half Cycle Slug Size (HCSS) is designed for thisstudy. Configuration of CO2 and water injection rateare tabulated in Table 1.

The model is simulated from 1996 until the end of2013 for primary recovery stage and continued to 10years CO2 flooding under scenario in Table 1 until theinjection period is finished (2024). The oil productionduring this CO2 flooding simulation is recorded forfeasibility calculation.

Figure 1: The grid model that is used in this study, the colorlegend represents the grid top of the cell in feet unit.

Table 1: Gas and water injection rate in CO2 floodingscenarios. “Mscf” means thousand standard cubic feet.

Injection ScenarioGas Rate Water rate(Mscf/day) (bbl/day)

Continuous CO2 injection 1463 -WAG 1463 1873

Figure 5 draws Schematic share diagram of GrossSplit between government and operator (mentionedas ”contractor” in this diagram). The difference ofthis new mechanism with previously cost-recoverymechanisms is the contractor must bear everyoperating cost, risk, and all taxes. The governmentand contractor shares are divided from the gross oilproduction while in the cost recovery mechanism, theoil should be shared to both parties after deductedfrom cost recovery post. Three variable influencesthe share of government and contractor, e.g., Basesplit, variable component, and progressive component


16

Figure 2: Relative permeability curve for water-oil system.

Figure 3: Relative permeability curve for gas-oil system.

(Giranza and Bergman, 2018). These variables areaffected by field condition, development status, andoil price (Roach and Dunstan, 2018).

Several assumption will be made for studying thefeasibility of CO2 flooding project in this field. Theoil price for this study is assumed 90 US$/bbl andthe share for government and contractor is under basesplit (57% - 43%). Moreover, the Indonesian tax isassumed 45% (Roach and Dunstan, 2018). All costand revenue components in this study are tabulatedin Table 2, based on study of Jarrel et al. (2002).This study also utilized recycled CO2 and water fromthe recycling facilities whereby the annual handling

Figure 4: Distribution of injection and production wells inthe grid model.

Figure 5: Schematic diagram of Indonesia gross-splitmechanism.

capacity of which are 18 MMSCF CO2 and 730thousand barrels of water. The Weighing average costof capital (WACC) for this study is 12%. Net PresentValue (NPV) of each scenario is will be compared.


Figure 6 compares the annual production during 10years continuous CO2 Flooding and WAG, while thecumulative production on each scenario are plotted

Table 2: Cost and revenue components assumptions in thisstudy.

Cost or revenue components ValueInjection well cost 0.600 MMUS$/wellProduction well cost 0.450 MMUS$/wellWell completion 0.200 MMUS$Water injection capital cost 0.011 MMUS$/wellCO2 facility capital cost 0.012 MMUS$/wellProduction facility capital cost 0.027 MMUS$/wellWater Injection Cost 1.000 US$/bblCO2 Price 2.500 US$/MscfChemical Cost 0.020 MMUS$/well/yr.CO2 recycle OPEX 0.750 US$/mscfWater Recycle OPEX 0.300 US$/bblOil Price 90 US$/bbl

Feasibility Study of CO2 Flooding under Gross-split Mechanism: Simulation Approach

17

in Figure 7. Continuous CO2 injection shows higherproductivity over WAG during two years injectionand gradually decrease for the rest period. Itis contrast with performance under WAG scenariowhere the oil recovery is still low in the first year butsignificantly increase more than 120% in the secondyear. Productivity on WAG tend to show a stable trendfor the next seven years. Results from the figure 7indicates the WAG application can recover oil slightlymore than continuous flooding scenario with 1%recovery gap, i.e. the 10-years oil recovery is same. Interms of CO2 utilization factor, a ratio of Injected CO2to the amount of oil production, simulation resultsshows low CO2 utilization factor is revealed for WAGscenario, means requires less CO2 to produce onebarrel of oil. Comparing the data trends on bothscenarios clearly indicates a continuous growth ofCO2 utilization factor, indicates the requirement toproduce crude oil becomes higher over the time, whileWAG shows a decreasing trend. WAG is effective toovercome the gravity segregation issue, compare tocontinuous CO2 flooding. Due to lower density. CO2tend to move upwards in the reservoir, resulting a poordisplacement efficiency (Jaafar et al., 2014),

Figure 6: Annual oil production during CO2 flooding phasefor each scenario.

Figure 7: Annual Cumulative oil production during CO2flooding phase for each scenario.

Despite both injection strategies shows sameachievement in term of oil recovery, WAG option

Figure 8: Annual CO2 utilization factor for continuous andWAG CO2 flooding.

is more attractive because consume less CO2inducing low CO2 Purchase cost. Comparingthese scenarios under gross-split mechanism revealunprofitable conclusion, as indicates in negativevalue of NPV (Figure 9). Therefore, base-sharebetween government and contractor is not feasiblefrom the contractor side, means share adjustmentbetween these shareholders are required. Thegovernment-contractor share is then adjusted to35%-65% because these share is suitable for highoperating cost, i.e., both CO2 flooding scenarios arecategorized into high operating cost projects (Roachand Dunstan, 2018). Recalculation of NPV underthis new share results negative NPV for continuousinjection project (-30.5 MM$) and 6.9 MM$ forWAG, means WAG scenario is more profitable.Moreover, the Internal Rate of Return (IRR) of thisproject indicate a significant profit can be madeduring this injection period, i.e., the IRR is higherthan Indonesia WACC (32.7% compare to 8%). Inshort, CO2 WAG scenario is effective in displacingresidual oil and also more profitable than anotheroption. Share adjustment in this study may be anevidence on the urgency CO2 issue in Indonesiagross-split mechanism. Therefore, it is recommendedto include CO2 issue into the variable and progressiveshare components.

The information shared to the all of communities.A monitor with all the information related to the waterquality installed at the community center or at thepoint of common assembly of community for easy todelivery of information. Furthermore, all the peopleand community can have an access to informationshows including the status of river water levels. Basedon monitoring system then all the information isupdate for public service and knows the status of theriver.


18

Figure 9: Effect of share adjustment to NPV for continuousand WAG CO2 flooding.

4 CONCLUSIONS

This paper analyze the feasibility of CO2 projectunder Indonesia gross split mechanism by usingreservoir simulation method. One of Indonesia oilfield reservoir is modelled for this study, where theCO2 injection schemes is limited to continuous andWAG scenarios. Simulation results reveals a betterperformance of WAG in recovering remaining oil inthe reservoir. Moreover, feasible indication is shownon WAG scheme after adjusting the base share ofgovernment and contractor. Including the CO2 issuesinto the variable and progressive share, points mayincrease the tendency of CO2 flooding application inIndonesia

REFERENCES

Abdurrahman, M., Permadi, A., and Bae, W. (2015). Animproved method for estimating minimum miscibilitypressure through condensation–extraction processunder swelling tests. Journal of Petroleum Scienceand Engineering, 131:165–171.

Abedini, A. and Torabi, F. (2014). Oil recoveryperformance of immiscible and miscible co2huff-and-puff processes. Energy & Fuels,28(2):774–784.

Agency, I. E. (2016). 20 Years of Carbon Captureand Storage: Accelerating Future Deployment.International Energy Agency.

Azzolina, N. A., Nakles, D. V., Gorecki, C. D., Peck,W. D., Ayash, S. C., Melzer, L. S., and Chatterjee,S. (2015). Co2 storage associated with co2 enhanced

oil recovery: A statistical analysis of historicaloperations. International Journal of Greenhouse GasControl, 37:384–397.

Christensen, J. R., Stenby, E. H., Skauge, A., et al.(1998). Review of wag field experience. InInternational petroleum conference and exhibition ofMexico. Society of Petroleum Engineers.

Giranza, M. and Bergman, A. (2018). Indonesia’s newgross split psc: Is it more superior than the previousstandard psc. Journal of Economics, Business andManagement, 6.

Irham, S. and Julyus, P. (2018). The new energymanagement policy: Indonesian psc-gross-splitapplied on steam flooding project. In IOP ConferenceSeries: Earth and Environmental Science, volume106, page 012109. IOP Publishing.

Jaafar, M., Omar, S., Anuar, S., and Suradi, S.(2014). Reservoir monitoring of eor processes (wag,foam and polymer) using streaming potential. InScientific Cooperations International Workshops onEngineering Branches, pages 8–9.

Jarrell, P. M., Fox, C. E., Stein, M. H., and Webb, S. L.(2002). Practical aspects of CO2 flooding, volume 22.Society of Petroleum Engineers Richardson, TX.

Jishun, Q., Haishui, H., and Xiaolei, L. (2015). Applicationand enlightenment of carbon dioxide flooding in theunited states of america. Petroleum Exploration andDevelopment, 42(2):232–240.

Roach, B. and Dunstan, A. (2018). The indonesian psc: theend of an era. The Journal of World Energy Law &Business, 11(2):116–135.

Rubin, E. S., Davison, J. E., and Herzog, H. J. (2015). Thecost of co2 capture and storage. International Journalof Greenhouse Gas Control, 40:378–400.

Whittaker, S., Rostron, B., Hawkes, C., Gardner, C., White,D., Johnson, J., Chalaturnyk, R., and Seeburger, D.(2011). A decade of co2 injection into depletingoil fields: Monitoring and research activities of theiea ghg weyburn-midale co2 monitoring and storageproject. Energy Procedia, 4:6069–6076.

Feasibility Study of CO2 Flooding under Gross-split Mechanism: Simulation Approach

19

Online Classroom Attendance System based on Cloud Computing

Sri Listia Rosa and Evizal Abdul KadirDepartment of Informatics Engineering, Faculty of Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

srilistiarosa, [email protected]

Keywords: Classroom Attendance, RFID Reader, Cloud Computing, Database

Abstract: Attendance of students in the classroom is one of mark representation of total marking after finish the endof class, some of the students are cheating they are attendance while manual system by sign in the formof attendance. Furthermore, manual attendance is ineffective way while digital technology is available andwidely used nowadays and waste of papers. This research discusses on automatic attendance system forstudents and lecturers, where every student before entering classroom have to tap their student card on RFIDreader and before out need to tap as well. Duration of time set as tolerance of lately as well as for earlyout of the classroom. Similar to students, every lecture required to tap as well before and after teaching in aclassroom, besides that lecturer required to hold his card on RFID reader to on electricity in the classroom elseno electricity and no power in the classroom. The data of students and lecturer attendance with room numberis set and send to a database for student’s attendance and honorarium for lecturer. This system tested in aclassroom of Faculty of Engineering, Islamic University of Riau with the number of students 40 people. Datacollected by RFID reader passed to the cloud server which controls by University information technologyand connects to the payroll system in the finance department. The system gives effective and efficiency inadministration, while no more manual record as well as clerk, do not need to summary lecturer attendance atthe end of the month for an honorarium. Paperless and efficiency for staff to control and manual attendance isone of the advantages of this system, and also students and lecturer unable to cheat their attendance in doubleclass teaching at the same time.

1 INTRODUCTION

Classroom teaching is a common method thatcurrently applying by most the academic institutionincluding in school and colleges. The conventionalmethod by having manually signed the attendance ina sheet of paper then passed around the classroomwhile lecturer conducts the teaching in the classroomis wide implements nowadays. This method couldundoubtedly allow the students to do cheating abouttheir attendance in the classroom, where a studentmay sign for an absent student. In addition, the helpform can easily be lost or lost during circulation.A more rigorous approach, especially to preventstudents from cheating on their attendance, is alsoboring, where a teacher tells each student’s namebased on a list of student names and validates eachstudent’s attendance. It has been proven that the formof a manual method for bringing student attendance isdifficult and time-consuming to verify each student.Without control, whether confirmed students respondor not, consolidated attendance calculations areanother important task that can cause manual errors.

In some other cases, attendance sheets may be lostor stolen by some students. The consequence ofsuch a problem with attendance notes on paper hasmade it stressful and ineffective, especially in largeclasses. As a result, there is a need to find new andmodern ways to track and manage student attendancerecords at higher academic learning institutions moreefficiently and effectively.

Therefore, it is very important to develop anassistance system that is equipped with an onlinedatabase, especially to prevent data loss, as well asto promote ecological and paperless and ecologicaltechnology campaigns. In addition, this applicationwill help reduce time wasted, which will leadto greater learning productivity in the classroom.Several paperless assistance systems have beendeveloped, but they must be equipped with acomputer or RFID reader, which incurs additionalcosts for hardware and can result in maintenance.With that in mind, our goal is to overcome thisproblem by having a system with minimum hardwarerequirements and, at the same time, enhancing themobility aspects of the existing support system.

20Rosa, S. and Kadir, E.Online Classroom Attendance System based on Cloud Computing.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 20-25ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

Furthermore, to overcome such troubles asmention in the above discussion, the required ofautomated attendance system is required for systemmanagement. Many way and technique are availableas the basic concept of the system. In this systemproposed an automatic student and staff (lecturer)attendance system, where RFID reader installed inevery classroom and assign with an identity foridentification of what classroom used.

2 RELATED WORKS

This section discussed on several works have beendone on previous research conducted. Someof previous works review related systems andstudent different for the methods in record student’sattendance. The use of android based system forstudents attendance as discussed in (Noor et al., 2015)where the application installed then can be downloadthe students list from a designated web server. Referto students attend in the classroom after their scan thecard to Radio Frequency Identification (RFID) reader(Evizal et al., 2012). Additional of device such ascameras used to support the system information andstudent’s attendance confirmation. Another researchdiscussed on this attendance system which elaboratein (Varadharajan et al., 2016) describe the studentsattendance without human interference. The usedof camera as a method to fix in the classroom andwill capture the image when every student going intoroom, the faces of students are detected and thenrecognized and match to the database and finally theattendance of student is marked. If the attendanceis marked as absent the message about the student’sabsent is send to their parents.

The others research is developed studentattendance system used a fraction of the classroomfor participation points and lead the students’attendance list into a preset teaching system suchas attendance by checking every student, randomquestioning based on the list, and quiz. Similar tothe ladder ranking system that widely used in currentonline computer games, students can check theirranking of accumulated absence and points in the endof class as a long term stimulus for study. (Debiec,2017; Gunawan and Kadir, 2017; Xiao et al., 2018).

The traditional student attendance system requiredphysically sign the attendance sheet every timeconduct lecture in the classroom. This method isunnecessarily time consuming to notice and markstudent’s name on the attendance sheet. Thisis happening that some students may accidentallymark the others student name or willingly to do

it. Normally, the hard copy of attendance sheetafter a few weeks may get lost or easily get messy.Used of smartphone such android technology willhelp teacher to get student attendance easily byonline system then be able to check percentagestudent attend the class as well to copy or printit. By using the stored information, teacher easilyto mark student attendance, attendance percentagecalculations, marking intruders’ entry, send emailsor send message to the parent to keep them updatedabout their child’s attendance at the school or college(Islam et al., 2017; Tarimo and Hickey, 2016).

Online Biometric-enabled Class AttendanceRegister System (OBCARS) prototype elaborateby (Wei et al., 2017) develop and design to changeof misplaced and torn attendance register form invarious classroom in school or college. System usedbiometric fingerprint reader for every student beforeentry the classroom. While the (Wei et al., 2017)discuss on student attendance system used NearField Communication (NFC) system. The solutionbe able to provides a traditional and mobile learningsystem for classroom to the school or college anduniversity to enhance the interaction in the process oflearning between the students and reduce the numberworkload given to the lecturers in summary of theattendance while in the clasroom (Kadir et al., 2016)All over previous research used normal online systemthen in this research proposed a new method of onlinesystem for student and lecturer pairing to make surelecturer attend in the classroom as well. Besidethat the use of cloud computing is one of additionalfeature in this system to make sure data of student’sattendee can be access staff in everywhere. Studentattendance information is very important is not onlyfor classroom marking but for finance department topay lecturer honorarium.

3 PROPOSED SYSTEM OFSTUDENT ATTENDANCE

The proposed solution for online student attendancesystem uses several components and integration tobecome a system that is able to manage student’sattendance. Difference to the current systemthat developed by other researchers, in this cloudcomputing has been used for data managementsystem beside local server in an academic institution.Figure 1 shows diagram of the student’s attendancesystem, where Arduino and RFID reader is the mainunit for this system to control student and staffattendance.

Student and staff card occupied with RFID chip


21

Figure 1: NumberBlock diagram of student attendancesystem.

which is Mifare 13.56 MHz and memory 1kBthus in this case users of the RFID reader toretrieve student or staff information by using anRFID system. Information stored in student cardis limited, only the identity (ID) data stored withsome information, this system designed to retrievestudent ID information which is 9 characters sameas to student matric number, as well as for thestaff ID with 9 characters. Once ID of student orstaff received by RFID reader then the informationreceived in Arduino Microcontroller to compare tostudent or staff ID in database, this case studentinformation linked to student academic managementsystem, where every student as they are accountablefor academic purpose, since the data and informationavailable then attendance system only connectedto the database without to set up a new databasemanagement system. Similar to student database,information of student classroom and schedule linkedto the academic management system which everyfaculty have to manage lecture classroom, schedule,subject, time, and student registration the subject.

Figure 2 shows a flowchart of the attendancesystem that flows of the process in the system. All theinformation start from student scanning the card thensystem decide whether valid or information to processor not then make the decision of student attendance.

3.1 RFID

Radio Frequency Identification (RFID) is atechnology based on wireless communication andNon-Line of Sight (NLOS) to retrieve information.Radio wave concept in RFID is able to collectinformation from the transponder (tag) to RFIDreader, with advantages of this technology and moreconvenience for student attendance system thus applyin this system. Figure 3 shows a sample of student ID

Figure 2: Flowchart of the student attendance system toprocess the information.

card used in this system with an emended RFID chip.

Figure 3: Sample of student ID card.

Similar to the student ID card, every lecturer andstaff occupied with RFID chip in ID card as well, thusthe process of data retrieve same as to student ID card.Figure 4 shows a sample of lecturer and staff ID cardwith an embedded RFID chip.


22

Figure 4: Sample of Lecturer and staff ID card.

3.2 Arduino

Arduino is a project based on an open source systemthat easy to use by the developer, hardware andsoftware integrated system developed in a package.Currently, the Arduino module widely used in manyapplication, thus in this attendance system usedArduino for microcontroller system. Figure 5 shows apicture of the Arduino module connected to an RFIDreader to read and retrieve card information. Allthe information analysis and to be matched to thedatabase as well as class schedule and verificationthen final information stored in the database. Inorder to be accessed by any party that required thisinformation thus a cloud database setup to keep allthe information.

Figure 5: An Arduino module with RFID reader.

3.3 Cloud Computing

Cloud computing is a technology in computer sciencerecently become an alternative to change from thelocal server to the cloud. The demand for availabilitysystem resources in a computer and especially forthe storage of data and computing for power systemwithout direct to a local server that manages by theuser. The term cloud computing is in general usedto describe data centres available to many users overinternet access. Figure 6 shows a configuration of acloud computing to be accessed by any user and themanagement system.

Figure 6: Configuration of cloud computing.

4 RESULTS AND DISCUSSION

Application of student attendance system has beendeveloped and tested in the real classroom, some classof lecture tested with this system. Figure 7 shows ascreenshot of student and lecturer attendance systemin the classroom.

Figure 7: Application student attendance system.

In this case, an average of students in a classroom


23

is 30 to 40 students, in the previous student usedmanual sheet form that must sign to proof attendancein a lecture class, with this application student justwipe the ID card to RFID reader installed in frontof a classroom. Once student wipes the card, if thestatus of the student is matched to class schedule andclassroom then the information recorded and send tothe data center, in this case, cloud computing usedto store all the information. Maximum tolerance forthe late in the classroom is 15 minute, so after lateduration student consider absence although they wipethe ID card then no record keeps in the database.Similar to late toleration duration, the student mustwipe ID card to RFID reader before the class finishto record the attendance, in this case, the durationis 15 before time schedule and 10 minutes after theschedule that every student must wipe the card else noout class recorded and student consider attendance notcomplete. Figure 8 shows a system for managementbefore class start have to set by the officer.

Figure 8: Attendance schedule system.

A report of student attendance system generatedonce lecture class finished, the report shows forevery student in a classroom that attends the subjectconducted by the lecturer. The report also recordedattendance for all the weeks, in this case, 16 weeksto complete a subject in a semester. Figure 9 shows areport sheet generated by this system.

Figure 9: Student attendance report sheet.

All the information for every student andclassroom including staff or lecturer conducted thelecture in classroom sent to the integrated databasemanagement system, the central database manages

for a student account and payroll system for lecturer,this system assists in management to calculate hourof every lecturer in a month and amount to pay thehonorarium. The information on student attendancerecord in cloud computing, then further developmentis to create a mobile system for the report to parent orguardian.

5 CONCLUSIONS

Student attendance system will benefit for anacademic institution, instead of using a manualsystem that raises many issues and uncontrolled forstudent cheating. The system tested in several oflecture classroom, out of 38 students listed in theclassroom where 36 students attend in the class and2 students’ absence recorded for the first testing,continue by 4 weeks. The system success to recordsall student and lecture attendance then record in adatabase. The system helps the officer and efficientsystem; management staff just verify the lecture in theclassroom then confirmation before the final record.Cloud computing used as a database to make easydata retrieval from other parties.

ACKNOWLEDGEMENTS

Authors would like to say thank you very much toKEMENRISTEKDIKTI Indonesia for funding thisproject and Universitas Islam Riau, Indonesia.

REFERENCES

Debiec, P. (2017). Effective learner-centered approach forteaching an introductory digital systems course. IEEETransactions on Education, 61(1):38–45.

Evizal, E., Rahman, T. A., and Rahim, S. K. A.(2012). Active rfid technology for asset trackingand management system. TELKOMNIKA(Telecommunication Computing Electronics andControl), 11(1):137–146.

Gunawan, H. and Kadir, E. A. (2017). Integration protocolstudent academic information to campus rfid gatepass system. In 2017 4th International Conferenceon Electrical Engineering, Computer Science andInformatics (EECSI), pages 1–6. IEEE.

Islam, M. M., Hasan, M. K., Billah, M. M., and Uddin,M. M. (2017). Development of smartphone-basedstudent attendance system. In 2017 IEEE Region10 Humanitarian Technology Conference (R10-HTC),pages 230–233. IEEE.


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Kadir, E. A., Rosa, S. L., and Gunawan, H. (2016).Application of rfid technology and e-seal in containerterminal process. In 2016 4th InternationalConference on Information and CommunicationTechnology (ICoICT), pages 1–6. IEEE.

Noor, S. A. M., Zaini, N., Latip, M. F. A., and Hamzah,N. (2015). Android-based attendance managementsystem. In 2015 IEEE Conference on Systems,Process and Control (ICSPC), pages 118–122. IEEE.

Tarimo, W. T. and Hickey, T. J. (2016). Fully integratingremote students into a traditional classroom usinglive-streaming and teachback. In 2016 IEEE Frontiersin Education Conference (FIE), pages 1–8. IEEE.

Varadharajan, E., Dharani, R., Jeevitha, S., Kavinmathi,B., and Hemalatha, S. (2016). Automatic attendancemanagement system using face detection. In2016 Online International Conference on GreenEngineering and Technologies (IC-GET), pages 1–3.IEEE.

Wei, K. C., Singh, M. M., and Osman, H. M. B.(2017). Near field communication interactivelearning system (niles) for blended learning: apervasive social networking services. In 2017Palestinian International Conference on Informationand Communication Technology (PICICT), pages71–77. IEEE.

Xiao, S., Liang, W., and Tang, Y. (2018). Classroomattention restoration using computer game rewardingmechanism. In 2018 13th International Conference onComputer Science & Education (ICCSE), pages 1–6.IEEE.


25

Analysis of Porosity and Permeability on Channel Deposit Sandstoneusing Pore-gas Injection and Point Counting in Sarilamak Area, West

Sumatra

Bayu Defitra, Tiggi Choanji and Yuniarti YuskarDepartment of Geological Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

[email protected], [email protected], yuniarti [email protected]

Keywords: Emulsion, Local Demulsifier, Palm Oil, Bottle Test

Abstract: Porosity and permeability is one of important factor to determine the quality of reservoir. Eight samples ofsandstone channel deposit that made into core had been established to determine the porosity and permeabilityfor the quality of reservoir using Pore-Gas Injection and Point Counting Method. This study is focusingon measuring and finding relationship between porosity and permeability, and shows an analog for reservoirbased on surface data. The effective porosity ranged from 0.5% - 24.8% classified into negligible – verygood porosity, the visible porosity ranged from 3.36% - 18.32% classified into poor – good porosity, and theeffective permeability ranged from 1.376 mD – 363 mD classified into tight – very good permeability, thereare differences between porosity and permeability which caused by grain size, sorting, and compaction ofsandstone. The average result of porosity and permeability classified as good reservoir.

1 INTRODUCTION

Porosity and permeability are things that cannot beseparated from rocks, porosity and permeability arealso things that are mutually related to each otherwhose discussion will be interconnected. In theexploration of petroleum or groundwater, porosityand permeability are important factors in determiningthe quality of a rock reservoir, this caused porosityand permeability can determine the amount of fluidpresent in rocks and the ability to drain fluid(Koesoemadinata, 1980).

Sandstones are the most widely distributedreservoir rocks on earth, and about 60% of allreservoir rocks are sandstones (Nichols, 2009).

Based on the appearance and condition on thefield, the study area was included in the distalfan subfasies of the Brani Formation (Wibowo andFardiansyah, 2016)

Sandstone on this area shows a channel depositthat analog to the fluvial channel on recent conditions(Choanji et al., 2019; Yuskar and Choanji, 2017) andwhich porosity and permeability are usually affectedby local structure (Choanji et al., 2018)

The purpose of this study was to determinehow the conditions of porosity and permeabilityin sediment sandstones in sarilamak area, west

sumatraprovince which have same characteristicor analog to the sand reservoir on Ombilin andCentral Sumatra Basin. This study is focusing onmeasuring and finding relationship between porosityand permeability on channel deposit sandstone atBrani Formation (Figure 1).

Figure 1: Map of Study Area

26Defitra, B., Choanji, T. and Yuskar, Y.Analysis of Porosity and Permeability on Channel Deposit Sandstone using Pore-gas Injection and Point Counting in Sarilamak Area, West Sumatra.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 26-30ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

2 METHODOLOGY

There are eight samples of channel deposit ofsandstone which are cored and analysis using porosityand permeability tools (Figure 2).

2.1 Porosity

This study using Pore-Gas Injection and PointCounting Method for determination the porosity ineight channel deposits sandstone on Brani Formation.

2.1.1 Pore Gas-Injection

Pore Gas-Injection was conducted using HeliumPorosimeter had been used to determine the effectiveporosity of eight samples. This method is usinghelium gas which has become nature of helium gasthat can easily enters the pore cavity and also thisdry gas produce no chemical reactions which willcause changes in the physical properties of the core sothat the existing porosity will be disrupted (Dandekar,2006). Eight samples had established to determiningthe effective porosity using the following equation:

vb =14

πd2h (1)

vsp =14

πd2sphsp (2)

vsop =14

πd2soshpop (3)

DV = (PccPoc

−1)vsp (4)

GR = (PccPoc

−1)vb (5)

vg = (vsop −GR)+DV (6)

bp = vv − vg (7)

ρg = (8) (8)

Øe f f = 100% (9) (9)

Where, d is core diameter, h is core height, dsp issteel plug diameter, hsp is steel plug height, dsop issteel out plug diameter, hsop is steel out plug height,pcc is close core pressure, poc is open core pressure,mc is core weight, vb is rock volume, vsp is steel plugvolume, vsop is steel out plug volume, DV is deadvolume, GR is Gauge Reading, vg is grain volume,vp is pore volume, ρgis groin density, and Ø eff iseffective porosity.

2.1.2 Point Counting

Petrographic method for calculating the percentageof elements or minerals contained in a rock samplewas formed into a thin section. This method isexplained by Chayes (1968) and Griffiths (1967),then developed by (Demirmen, 1972) called pointcounting cell models. This method was also usedto determine the visible porosity using the followingequation :

Visiblexorosity =TotalPoreonCell

TotalCellX100% (10)

The effective porosity and visible porosityestimated in laboratory classified by classificationof porosity by Koesoemadinata (1980) intoNegligible/Very Poor 0 - 5 % , Poor 5 - 10 %,Fair 10 - 15 %, Good 15 - 20 %, Very good 20 - 25 %, and Excellent > 25 %.

2.2 Permeability


Method for permeability analysis was conduct usingGas Permeater which had been used to determine theeffective permeability. This Method using nitrogengas which more easily enters the pore cavity andno chemical reactions that will cause changes in thephysical properties of the core so that the existingporosity will be disrupted (Handwerger et al., 2011).Eight samples had established to determining theeffective permeability using the following equation:

Q = (High Flow - Lol Fwow) (11)

∆P = (P1 −−P2) (12)

A = 2πr(r+h) (13)

K =µQL

A(∆P)(14)

Where, r is core radius, h is core height, Q is flowrate, ∆P is Pressure, A is section area, µ is Viscosity,and K is Permeability.

The effective permearility estimated in labobatiryclassified by classification of permeabiloty byKoesoemadinata (1980):

• Tight < 5 mD

• Fair 5 - 10 mD

• Good 10 - 100 mD

• Very good 100 - 1000 mD

• Excellent >1000 mD

Analysis of Porosity and Permeability on Channel Deposit Sandstone using Pore-gas Injection and Point Counting in Sarilamak Area, WestSumatra

27


Based on laboratory work, the porosity andpermeability of eight channel deposits sandstoneshowing difference of value. The following result ofthe porosity and permeability:

3.1 Porosity


The effective porosity of eight channel depositssandstone had been estimated using HeliumPermeameter in range from 0.5% - 24.8%, theeffective porosity belonging to negligible – verygood porosity. Core 2C and core 3A has thesmaller effective porosity because the rock has beencompacted and has poor sorting. The summary ofeffective porosity shows in Table 1.

3.1.2 Point Counting

Based on thin section of eight channel depositssandstone (Figure 2) the visible porosity had beenestimated using grid cell ranged from 3.36% -18.32%, the visible porosity belonging to negligible– good porosity. The summary of visible porosityshows in Table 2.

3.2 Permeability


The effective permeability of eight channel depositssandstone had been estimated using Gas Permeameterin range from 1.376 mD – 363 mD the effectivepermeability belonging to tight – very goodpermeability. Core 2C and core 3A has thesmaller effective permeability because the rock hasbeen compacted and has poor sorting. The summaryof effective permeability shows in Table 2.

According the result of laboratory work ofeffective porosity, visible porosity, and effectivepermeability, it classified for potential reservoir asshown in Table 4. Figure 2: Thin Section of Eight Channel deposits Sandstone

(visible porosity marked by dark blue color).


28

Table 1: Summary of Effective Porosity.

CNreoumber

d(cm) h (cm)

mc(gr) DV(cm3) GR(cm3) Vg

(cm3) Vp(cm3) ρg(gr/cm3)Ø

effective(%)

VisislePorobity

(%)1 3.1 7.9 178.72 0.077 0.32 67.067 7.467 3 12.52 13.28

2A 3.3 3.6 88.37 0.70 0.435 33.915 3.135 2.9 10.18 7.842B 3.1 7.9 174.25 0.084 0.33 67.064 7.464 2.92 12.53 11.682C 3.3 7.6 198.53 0.118 0.47 66.985 5.868 3.05 3 5.763A 3.3 4.6 106.33 1.044 0.95 39.514 0.194 2.7 0.5 3.363B 2.9 8.2 124.57 0.78 3.40 67.57 13.43 2.3 24.8 18.323C 3 7.3 89.88 0.37 0.902 61.008 9.408 1.74 18.23 13.64 3.1 7.6 107.85 0.46 1.705 66.065 8.735 1.9 15.23 16.96

Table 2: Summary of Effective Permeability.

roCeNumber

d(cm)

h(cm)

A(cm2)

Q(cm3/s) (cP) P

(atm)K

(mD)1 3.1 7.9 92 3.342 0.018 0.13 40

2A 3.3 3.6 54.40 0.518 0.018 0.068 92B 3.1 7.9 92 3.418 0.018 0.095 562C 3.3 7.6 95.85 0.567 0.018 0.588 1.3763A 3.3 4.6 54.40 1.538 0.018 0.560 43B 2.9 8.2 87.88 19.855 0.018 0.260 1283C 3 7.3 82.9 3.90 0.018 0.017 3634 3.1 7.6 89.07 17.84 0.018 0.300 91

Table 3: The Result of Laboratory Work for Potential Reservoir of Eigth Channel Deposits Sandstone.

CoreNumber

EfsectivePorofity

(%)

VisiblePorostiy

(%)

effemtivePErmeability

(cD)

PorosityCondition

PermeabilityCondition

PRtentialoeservoir

1 12.52 13.28 40 Fair Good Fair2A 10.18 7.84 9 Fair Fair Fair2B 12.53 11.68 56 Fair Good Fair2C 3 5.76 1.376 Neglilibge Tight Poor3A 0.5 3.36 4 Negligible Tight Poor

3B 24.8 18.32 128 VeryGood

Veoy Gord VeryGood

3C 18.23 13.6 363 Good Very Good VeryGood

4 15.23 16.96 91 Good Good Good

Analysis of Porosity and Permeability on Channel Deposit Sandstone using Pore-gas Injection and Point Counting in Sarilamak Area, WestSumatra

29

The porosity classified as negligible porosity iscore 2C (3%) and 3A (0.5%), fair porosity is core 1(12.52%), core 2A (10.18%) and core 2B (12.53%),good porosity is core 3C (18.23%) and core 4(15.23%), only core 3B (24.8%) that classified asvery good porosity. The permeability classified astight permeability is core 2C (1.376 mD) and core 3A(4 mD), fair permeability is core 2A (9 mD), goodpermeability is core 1 (40 mD), core 2B (56 mD),and core 4 (91 mD), very good permeability is core3B (128 mD) and core 3C (363Accordind the valueof porosity and permeability can be conclude into apotential reservoir by Koesoemadinata (1980) is core3B, core 3C, core 4 because has good – very good inporosity and permeability.

4 CONCLUSION

The result shows that this channel depositssandstone has the effective porosity which rangedfrom 0.5% - 24.8% that classified as negligible –very good porosity, however the visible porosityshowed value 3.36% - 18.32% which classified intonegligible – good porosity, effective permeability instudy area ranged from 1.376 mD – 363 mD. Thedifference result from the value of the porosity andpermeability in study area caused by the compaction,sorting, grainsize of the sandstone which differentbetween channels. According the value of porosityand permeability in study area, can be conclude aspotential reservoir are only three core (3B, 3C, and 4)cause has good – very good porosity and permeability.

ACKNOWLEDGMENTS

Authors would say thanks to all of the field team,and also Department of Geological Engineering,Universitas Islam Riau for giving support for thisstudy.

REFERENCES

Choanji, T., Rita, N., Yuskar, Y., and Pradana, A. (2018).Analog study of fluid flow on deformation band atpetani formation, riau, indonesia. In MATEC Web ofConferences, volume 159, page 01034. EDP Sciences.

Choanji, T., Yuskar, Y., Putra, D. B. E., and Cahyaningsih,C. (2019). Clustering Slope Stability UsingDem Lineament Extraction And Rock Mass RatingIn Pangkalan Koto Baru. WEST SUMATRA,INDONESIA. Int. J. Geomate, 17.

Dandekar, A. Y. (2006). Petroleum reservoir rock and fluidproperties. Boca Raton, FL?: CRC/Taylor & Francis.

Demirmen, F. (1972). Operator error in petrographicpoint-count analysis: A theoretical approach.Mathematical Geology - MATH GEOL.

Handwerger, D. A., Keller, J., and Vaughn, K. (2011).Improved Petrophysical Core Measurements on TightShale Reservoirs Using Retort and Crushed Samples.SPE Annu. Tech. Conf. Exhib.

Koesoemadinata, R. P. (1980). Geologi Minyak dan GasBumi. InstitutTeknologi Bandung, Bandung.

Nichols, G. (2009). Sedimentology and stratigraphy. J.Chem. Inf. Model. 53, 53(419.).

Wibowo, A. and Fardiansyah, I. (2016). Alluvial – fluvialarchitecture of synrift deposits: An observation fromthe outcrops of brani fm. Ombilin Basin, WestSumatra. Ber. Sedimentol, 36.

Yuskar, Y. and Choanji, T. (2017). Uniqueness deposit ofsediment on floodplain resulting from lateral accretionon tropical area. J. Geosci. Eng. Environ. Technol. 2,2(14.).


30

A Simulation Study of Downhole Water Sink Guidelines Plot Applicationusing Real Field Data

Praditya NugrahaUniversitas Papua, Sorong, West Papua

[email protected]

Keywords: Downhole Water Sink, Simulation Study, Guidelines Plot, Water Coning.

Abstract: One solution for water coning problem is Downhole Water Sink (DWS) system. A dual completion systemis used to produce the oil perforated zone and the water separated zone separately. Pressure drawdown in thewater zone is used to oppose pressure drawdown in the oil zone so the water-oil contact is remained stableand prevents the water coning. A DWS guideline plot proposed by Marhaendrajana and Alliyah is used as abasis in application of DWS by using real field data. This research aimed to apply the DWS guideline plotto get the benefit of DWS which is controlling the water coning problem. A geological reservoir model hasbeen upscaled and history-matched into a representative dynamic reservoir model used in this study. Thesimulation is conducted by applying 5 scenarios in DWS application considering the number of active wellsand the variation of flow rate in this reservoir. DWS guideline plot and its application using real field data gavegood results in increasing oil recovery with some concern related with the amount of water produced in waterperforated zone. The best scenario which is using DWS in high and medium rate wells group gave 16.24%recovery factor.

1 INTRODUCTION

Water almost always co-exist with our desired fluidsin a reservoir, therefore, it is expected to producea certain amount of water during production. Theamount of water produced is usually referred to asthe water cut. The highwater cut will lower the oilproduction rate and increase the water treatment cost.This problem arises in a water drive reservoir andwater injection in waterflooding operations. Waterwhich has higher mobility than oil tends to bypass theoil flow and cause water coning. A lot of researchhas been conducted on studying critical productionrates and water breakthrough time to control waterconing (Chaperon et al., 1986; Abass et al., 1988;Høyland et al., 1989). On the other hand, economicalproduction rates also need to be considered whenproduction rates are limited. Downhole water sink(DWS) was introduced for controlling water coningwithout limiting the oil production rate below itscritical rate (Wojtanowicz et al., 1991).

This paper presents a simulation study of DWSguideline application using real field data. The basicconcept of DWS and its guideline will be coveredbriefly. Then, the field data and some assumptionsused are presented before the result is summarized.

2 DOWNHOLE WATER SINKTECHNOLOGY

One technology to overcome water coning problemis Downhole Water Sink technology (DWS). DWSis a dual completion application technology wherethe oil zone and water zone are produced separately.This concept was proposed by Wojnatowicz in1991 (Wojtanowicz et al., 1991) and then calledas Downhole Water Sink for the first time in1997 (Shirman and Wojtanowicz, 1997). An equalpressure drawdown is created in water perforatedzone to prevent water coning and to create a stableoil-water contact, so oil can be produced fromthe top perforation while water is produced fromthe bottom completion. Astutik (2006) has listedseveral studies that showed the DWS applicationsuccessfully worked to preventwater coning andincrease oil production without water breakthrough.Those studies included numerical studies and fieldapplication. However, most of those studies werefocused on comparing DWS with conventionalcompletion technique.

Marhaendrajana and Alliyah proposed a guidelinefor DWS design (Marhaendrajana, Sukarno, andAlliyah, 2008) which incorporates parameter

Nugraha, P.A Simulation Study of Downhole Water Sink Guidelines Plot Application using Real Field Data.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 31-34ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

31

Figure 1: Schematic of Downhole water sink (taken from(Wojtanowicz, 2006)). A. DWS water drainage-injection.B. DWS water drainage-production.

affecting water coning such as permeabilityanisotrophy (kv/kh )and perforation interval (hp/ho).Where Qtop* and Qbottom* are respectively :

Q∗top = Qtop +

(10α1)

[(kv

kh

)]α2[(hp

ho

)]α3

(1)

Q∗bottom = Qbottom +

(10β1

)[( kv

kh

)]β2[(hp

ho

)]β3(2)

Where : α1=2.401433, α2=0.518346, α3=1.283428;and β1=3.227316, β2=0.842945, β3=1.567493.

The preferable condition is where instead of waterconing, the oil coning happened or called as reverseconing. The segregated and reverse coning phasein the DWS guideline plot become the guideline todetermine the production rate in the oil zone (Qtop)and the water zone (Qbottom).

3 SIMULATION AND FIELDDATA

The simulation and field data used are from aJurassic reservoir in China (Huawei et al., 2013).A reservoir dynamic model has been upscaled fromgeological model and well history-matched with itsproduction history data. The model was built usingPETREL and run using ECLIPSE. Production historydata showed that water production rose rapidly andbecome a major problem. This reservoir has 4 majorlayers (Y71, Y81, Y82, and Y91) with an averagepermeability of 100 mD and average porosity 14.5%.

Figure 2: DWS Guideline Plot (taken from(Marhaendrajana et al., 2008).

Table 1 and Table 2 summarized the reservoir andoil properties.

In this reservoir there are 81 vertical wells and 1horizontal well. At the end of history matching 12wells are converted to be water injector wells. 15years of production years is used as the basis for thedevelopment strategy.

The oil recovery factor at the end of historymatching is 7.26%. From Figure 3, the remaining oilsaturation for each layer is still quite high which is 0.6inthe green color region.

Table 1: Rock Properties (taken from Huawei et.al., 2013).

Rock CharacteristicsPorosity, % 14.5Horizontal permeability, millidarcy (mD) 100Kv/Kh 0.1Compressibility, 1/bar 0.00055

Table 2: Fluid Properties (taken from Huawei et.al., 2013).

Oil Water

Density, kg/m314.5

1000(32.15API)Viscosity, cp 8.88 0.5494FVF 1.13 1.014Compressibility, 1/bar 4.16 x 10-5

At first, it was needed to optimize the waterinjection scheme to maintain reservoir pressureabove the bubble point pressure while increasing therecovery factor (RF). The optimization resulted inrecovery factor of 14.94%. The optimized waterinjection case will be used as our base case inimplementing DWS.


32

Figure 3: Remaining oil saturation at the end of historymatching (So initial for development).

4 DWS GUIDELINE PLOTAPPLICATION

For employing DWS concept in the reservoirsimulation, a well with DWS is two wells in the samelocation with different perforation intervals. Oneperforation will perforate the oil zone while the otherone will perforate the water zone in the same well.The production rate for the water zone is higher thanin the oil zone to keep a good Oil-Water Contact(OWC) in straight line or to make the oil and waterin segregated phase.

In applying the DWS technology, the wellsare sorted into three groups. High rate wells(production rate > 15 m3/day), medium rate wells(production rate between 10-15 m3/day), low ratewells (production rate < 10 m3/day). There are 5cases conducted in this simulation study to evaluatewhich case gives the highest recovery factor. Theoperation condition for DWS (Qtop and Qbottom)are determined by 3 chosen operation conditions foreach sorted group of different production rate (high,medium, and low).

High – Qtop* = 200bopd, Qbottom* = 1000bopdMedium – Qtop* = 100bopd, Qbottom* = 800bopd

Figure 4: DWS Operation condition for each groupwell.(modified from Marhaendrajana, Sukarno, andAlliyah, 2008).

Low – Qtop* = 50bopd, Qbottom* = 100bopd

For Case 1, 8 wells from high rate wells group wereusing DWS with Qtop = 30 m3/day and Qbottom =160 m3/day.

For Case 2, 5 wells from medium rate wellsgroup were using DWS with Qtop = 15 m3/day andQbottom = 80 m3/day.

For Case 3, 10 wells from low rate wells groupwere using DWS with Qtop = 8 m3/day and Qbottom= 30 m3/day.

For Case 4, DWS was implemented in high ratewells and medium rate wells and did nothing for thelow rate wells.

For Case 5, DWS was implemented in each groupof well, high rate, medium rate and low rate.

Qtop and Qbottom used in each group wells werecalculated from the DWS guideline plot. The valuesalso have been converted from SIunit (InternationalSystem of unit) in reservoir data unit (China using SIunit) into field unit in DWS guideline plot. After thesimulation, the results are presented in Table 3.

Table 3: Simulation Study Results.

Case Scenario RF(%)

Basecase

Optimized WaterInjection

14.94

Case 1 Base case + DWS highrate

15.37

Case 2 Base case + DWSmedium rate

15.23

Case 3 Base case + DWS lowrate

14.66

Case 4 Base case + DWS highand medium rate

16.24

Case 5 Base case + DWS high,medium and low rate

16.15

A Simulation Study of Downhole Water Sink Guidelines Plot Application using Real Field Data

33

From the results, case 4 gave the highest recoveryfactor with only DWS application in high and mediumrate. This shows that DWS application in lowrate wells did not give significant water drainagein reducing water coning. These results correlatewith DWS operation condition for the low grouprate which is located at segregated zone (Figure4). Segregated inflow production can only beachieved for a relatively low flow rate. In the fieldoperations, reverse coning has been used mostlyin the reversed coning mode of DWS production(Shirman and Wojtanowicz, 1997). While on otherhand, the preferred oil coning provides additionalconstrain in terms of water treatment capacityas the more water will produce in conjunctionwith higher water production rate in water zone.DWS water drainage-injection mode can be used toovercome this excess water problem (Figure 1A.)The water drainage was pumped into water zonebelow the water drainage perforated zone. Thisapproach has already been applied in real fields suchas Greater Burgan Field (Al-Fadhli et al., 2019)and North Kuwait (Anthony and Al-Mosaileekh,2016). But in general, the DWS guideline plotprovide a good approximate operating conditionin DWS application.In its application, the Qtop*and Qbottom* can be optimizedfor each well withdifferent production rates. The grouped productionrates are used to simplify the simulation consideringthe number of wells in this field. Production rateshould be a screening criterion in DWS application.An adequate flow rate is needed to operate DWS inreverse coning region to optimize the benefit of DWS.

5 CONCLUSIONS

From this study, we observe that DWS guidelineplot gave good approximate operation condition interms of production rate in oil zone (Qtop) andwater zone (Qbottom). Grouped production ratewells can be used to simplify the implementation ofDWS application as different production rate needdifferent DWS operation condition. Reverse coningregion is the preferred operation condition for DWSapplication. Screening of production rate is neededto make sure DWS application in reverse coningoperation region. In DWS application,economicevaluation is needed to make sure the incrementaloil production can cover the investment of additionalwater treatment capacity as more water will beproduced. DWS water drainage-injection mode canbe used as alternative to overcome excessive waterproduction.

ACKNOWLEDGMENTS

This work is partially from the author’s MasterThesis at Institut Teknologi Bandung (ITB). Theauthor also would like to thank Dr.AmegaYasutrafrom ITB for his guidance, Prof. Ning Zhengfufrom China University of Petroleum-Beijing (CUPB)for providingthe data used in this study andhis PhDstudents in helping author understanding the data.

REFERENCESAbass, H., Bass, D., et al. (1988). The critical production

rate in water-coning system. In Permian Basin Oiland Gas Recovery Conference. Society of PetroleumEngineers.

Al-Fadhli, W., Kurma, R., Kovyazin, D., and Muhammad,Y. (2019). Modeling and simulation to produce thinlayers of remaining oil using downhole water sinktechnique for improved oil recovery. a case study ingreater burgan field.

Anthony, E. and Al-Mosaileekh, S. (2016). Downhole watersink technology improves recovery and rates fromstrong water drive reservoirs in north kuwait – a pilotcase study.

Astutik, W. (2007). A study of down-hole water sink (dws)technology - optimum dws design in vertical wellconsidering reservoir parameters.

Chaperon, I. et al. (1986). Theoretical study of coningtoward horizontal and vertical wells in anisotropicformations: subcritical and critical rates. In SPEannual technical conference and exhibition. Societyof Petroleum Engineers.

Høyland, L. A., Papatzacos, P., Skjaeveland, S. M., et al.(1989). Critical rate for water coning: correlationand analytical solution. SPE Reservoir engineering,4(04):495–502.

Huawei, Z. et al. (2013). Pengyang Jurassic Oilfield :Fine Reservoir Description Reservoir Study. ReseacrhReport, China University of Petroleum-Beijing.

Marhaendrajana, T., Sukarno, P., Alliyah, I., Geologi,H., Buniayu, S. B. T. K., Di Daerah, S. P.S. K., and Cilacap, J. T. (2008). Oil productionenhancement using bottom-hole water sink: Aguideline for optimum design application. Proceedingfor Simposium Nasional & Kongres IX Ikatan AhliTeknik Perminyakan Indonesia (IATMI), Jakarta,pages 15–17.

Shirman, E. and Wojtanowicz, A. (1997). Waterconing reversal using downhole water sink-theory andexperimental study.

Wojtanowicz, A., Xu, H., Bassiouni, Z., et al. (1991).Oilwell coning control using dual completion withtailpipe water sink. In SPE Production OperationsSymposium. Society of Petroleum Engineers.

Wojtanowicz, A. K. (2006). Down-hole water sinktechnology for water coning control in wells.Wiertnictwo, Nafta, Gaz, 23(1):575–586.


34

Groundwater Exploration using 2D Electrical Resistivity Imaging (ERI)at Kulim, Kedah, Malaysia

Adi Suryadi1, Muhammad Habibi2, Batara3, Dewandra Bagus Eka Putra1, Husnul Kausarian1

1Department of Geological Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2GWS Drilling Engineeering Sdn. Bhd., No. 6 Jalan Metro Perdana Timur 11, Kuala Lumpur, Malaysia3School of Ocean and Earth Science, Tongji University, Guokang Rd, Yangpu Qu, Shanghai Shi, China

adisuryadi, dewandra.bagus, [email protected], [email protected], [email protected]

Keywords: 2D Electrical Resistivity Imaging (ERI), Dipole-Dipole, Groundwater, Resistivity, Kulim, Malaysia

Abstract: Water demand in the study area has been increasing by time but surface water is not sufficient to fulfil thedemands. 2D Electrical Resistivity Imaging (ERI) survey was conducted in order to looking for groundwaterpotential as freshwater alternative resources at Kulim, Kedah, Malaysia. The data acquisition was carriedout using 5 meters multi-electrodes spacing with pole-dipole configuration array. The geophysical surveyinvolved both resistivity and chargeability at the same time. The result of 2D Electrical Resistivity Imagingindicated that the groundwater potential area has low resistivity value with range 10 – 100 Ωm. Groundwaterpotential zone divided into 2 characteristics which is shallow groundwater zone (>75m in depth) and deepgroundwater zone (>100m in depth). The groundwater potential zone covered by high to very high resistivityvalue. Those high resistivity value 200 – 1000 Ωm interpreted as dry top soil at near surface while at deepzone is interpreted as fresh bedrock. Chargeability value of groundwater potential area ranging from 0 up to 8msec. All interpretation later confirmed by drilling data.

1 INTRODUCTION

Geo-electrical survey is a survey that lookingthe physical parameters which is resistivity valueto differentiate subsurface material. Recently,the interest of underground sources of water isincreasing rapidly to fulfilled the water demand(ASuryadi et al., 2019). Electrical ResistivityImaging (ERI) is the most common and successfullyused especially in groundwater exploration andenvironmental problems(Azhar et al., 2016; Hamzahet al., 2008; Hamzah et al., 2007; Jumary et al.,2002; Saad et al., 2012). By using ERI, resistivitydistribution of subsurface will be modelled intotwo-dimensional image(A Suryadi et al., 2019). Themodel that resulted is showing the apparent resistivityvalue which can be interpret depend on the value.

The study area is located at Silterra MalaysiaSdnBhd at Lot 8 and 9 in Kulim, Kedah, Malaysiawith coordinate N 5024’18.24” and E100035’33.09”.The shortage of piped water supply at headquartersSilterra has caused considerable problems to severalactivities of the central area. The supply of water tothe central area is insufficient due to high demandof water. Long period of dry season also affected

to hydrogeology cycle. This water problem isnot only caused problem to the factory but it alsoaffected the nearby residential area(Adi Suryadi etal., 2019). So, aim of this study is to locate anddelineate groundwater potential zone as alternativewater resources at study area.

The area is located about 10 km from Pekan Kulimand about 3 km from Sungai Jarak. Secondary forestand palm oil plantation are covered the study areawith almost flat topography (Figure 1). It easily toreach the location by using a car. Nine (9) lines of2D Electrical Resistivity Imaging (ERI) survey wereconducted with length of survey line up to 400 m(Figure 2).

2 GEOLOGICAL SETTING OFSTUDY AREA

Geology of Study area is consist of granite andsurround by metamorphic rock (slate, phyllite andschist) and sedimentary rock (sandstone, siltstone andshale) (Figure 3). Granite of study area known asKulim granite that consist of two main types, namely

Suryadi, A., Habibi, M., Batara, Eka Putra, D. and Kausarian, H.Groundwater Exploration using 2D Electrical Resistivity Imaging (ERI) at Kulim, Kedah, Malaysia.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 35-40ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

35

medium to coarse grained biotite granite and thesparsely porphyritic micro-granite. Both of them arealmost similar in mineral contain except the formeralso contain traces of galena, pyrite and garnet. Theessential of mineral in the granite are K-feldspar,plagioclase, quartz, biotite and muscovite. K-Armineral ages for biotite sparates from pink porphyriticPenanti granites (north of Bukit Mertajam) definedan age 196±8 Ma. K-Ar mineral ages for biotiteand muscovite sparates from the Karangan biotitegranite (northeast Kulim) gave an age of 190±10 and180±10 Ma respectively(Hutchison, 1989).

Figure 1: Topography map that show location of study areais almost flat.

Figure 2: Satelite image of study area that shown line surveylocation.

3 METHODOLOGY

ABEM SAS1000 resistivity meter and ABEM LundES464 selector system is the equipment that used

Figure 3: Geological Map of study area that consistof granite and surrounded by sedimentary rock andmetamorphic rock(Hutchison, 1989).

to collect the resistivity data. The survey employed61 multi-electrodes with 5 m minimum electrodespacing. The line survey length is reach 400 mthat arranged in a straight line. The selector systemwas connected with all electrodes through multi-corecable (Figure 4)(Loke and Barker, 1995)(Azhar etal., 2016; Hamzah et al., 2008; Loke and Barker,1995; A Suryadi et al., 2019). In each measurementthe resistivity meter only select four electrodes toactivate. Beside of that, coordinate of line surveymust be recorded to correlate all the lines taken(Kausarian et al., 2018, 2016; Lubis et al., n.d.;LUBIS et al., 2018; Suryadi, 2016)

Apparent resistivity (ρa) calculated by multiple ofgeometry factor (k) with Voltage (V) and divided byCurrent (I) injected.

ρa = kV/I (1)

Geometry factor (k) is depend on configurationelectrode that utilized. In this study configurationused id pole-dipole (Figure 5) that k calculated withformula:

k = 2π(b(a+b))/a (2)

a is the distance from P1 to P2; b is the distance fromC1 to P1


36

Figure 4: Equipment set up to acquisition resistivitydata(Loke and Barker, 1995)

Figure 5: Equipment set up to acquisition resistivitydata(Loke and Barker, 1995)

The data collected processed by using inversemodelling software which is RES2DINV. The resultof inverse modelling will interpreted based onapparent resistivity and proven by drilling data.


Nine (9) ERI lines survey data has been processed inorder to produce 2D inversion model of resistivity.The resistivity value representing the subsurfacecondition of study area. There are two typical ofgroundwater potential zone in this study which aredeep groundwater potential and shallow groundwaterpotential.

Figure 6 is the result of line 6 show the typical2D ERI result of study area with deep groundwaterpotential. Generally, resistivity value can be groupedinto 3 layers or zones. First zone with moderateto high resistivity value (100 – 1000 Ωm) thatrepresented by colour orange to purple near surfaceis interpreted as top soil. Usually soil always showingmoderate to low resistivity value because it has highmoisturized due to subtropical area(N. Nwankwo andO. Emujakporue, 2012; A Suryadi et al., 2019).But in this study top soil showing high resistivityvalue, this value indicating the condition of soil isdry. Below top soil, resistivity value is extremelyhigh represented by red to dark purple in colourwith resistivity range 300 to 2000 Ωm. this layer isinterpreted as fresh bedrock layer. Based on geologyregional of study area, bedrock of the site is consist

of granite. The third layer is located about 100 min depth from surface with low resistivity profile (10– 100 Ωm). This layer showed by bright green toyellow in colour. From those resistivity value, thethird layer is interpreted as groundwater potential areabecause water saturated zone are conductive zone thateasily to transfer electrical current. From the resultof chargeability also support the interpretation withshowing low chargeability (2 – 20 msec).

Another typical of groundwater potential zones isrepresenting by result of line survey 7 (Figure 7). Thisresult also divide into 3 layer. The first layer is drytop soil layer with resistivity value range (100 – 1000Ωm), followed by very high resistivity value (300 –2000 Ωm) that interpreted as granite fresh bedrock.In granite zone there is an anomaly resistivity valuewith coning shape at depth 25 to 75 m. This zone haslow resistivity profile which is 3 – 100 Ωm interpretedas shallow groundwater potential. It also linear withchargeability result that showing low chargeabilityvalue 2 – 8 msec. Table 1 showing all the groundwaterpotential zone from 9 survey lines.

From the result of 2D Electrical ResistivityImaging (ERI), some location that has groundwaterpotential has been drilled to prove either it actuallywater saturated zone or not. Besides that, drilling dataalso proven for all geological interpretation basedon resistivity value. Table 2 is drilling locationcoordinate according to groundwater potential zonesthat has been interpreted.

Table 1: Groundwater potential zone characteristic andlocation based on 2D ERI

Survey line

Groundwater potential zone

Resistivity(Ωm)

Chargeability(msec)

Depth (m) Locationfrom 1st

electrode(m)

Line 1 8 - 110 0 – 2 75 – 125 80 – 180Line 2 10 – 100 8 – 12 ¿ 125 225 – 255Line 3 2 – 100 2 – 5 75 – 150 80 – 210Line 4 3 – 100 1 – 5 75 – 125 140 – 265Line 5 20 – 100 0 – 1 125 – 150 150 – 230Line 6 10 – 100 2 – 12 100 – 125 140 – 240Line 7 1 – 100 0.5 – 5 25 – 75 185 – 280Line 8 20 – 100 2 – 12 50 – 100 215 – 290Line 9 1 – 100 1 – 2 25 – 50 185 – 220

PDL 6 and PDL 7 are located at survey line 6 andsurvey line 7. Based on drilling data PDL 6 (Figure8) from the surface to 6 is consist of top soil withcharacteristic light yellowish brown in color,soft andslightly silty clay. From 6 m to 12 m the materialis firm fine sandy silty clay with color light reddishbrown. Hard layer of clay found at depth 12 m up to30 m. starting from 30 of depth till the end of drilling(300 m) represented by weathered granite. At 100 mand 280 m of depth was identified as fractured zone.In conjunction between 2D ERI result of line 6 anddrilling data of PDL 6 can be correlated. The low

Groundwater Exploration using 2D Electrical Resistivity Imaging (ERI) at Kulim, Kedah, Malaysia

37

Figure 6: 2D Electrical Resistivity Imaging result of line survey 6

Figure 7: 2D Electrical Resistivity Imaging (ERI) result of line survey 7

resistivity value (10 – 100 Ωm) from 2D ERI result atdepth 125 interpreted as groundwater potential zoneand it supported by drilling data. According thedrilling data, at 100 m of depth found fractured zoneof granite that has very high possibility as secondaryporosity to preserve groundwater resources.

PDL 6 and PDL 7 are located at survey line 6 and

survey line 7. Based on drilling data PDL 6 (Figure8) from the surface to 6 is consist of top soil withcharacteristic light yellowish brown in color,soft andslightly silty clay. From 6 m to 12 m the materialis firm fine sandy silty clay with color light reddishbrown. Hard layer of clay found at depth 12 m up to30 m. starting from 30 of depth till the end of drilling


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Table 2: Coordinate of drilling location

NameCoordinate

Latitude LongitudePDL 1 5 24’ 18.37” N 100 35’ 30.99” EPDL 2 5 24’ 14.66” N 100 35’ 32.62” EPDL 3 5 24’ 17.38” N 100 35’ 32.08” EPDL 4 5 24’ 17.02” N 100 35’ 29.32” EPDL 5 5 24’ 9.63” N 100 35’ 31.84” EPDL 6 5 24’ 8.63” N 100 35’ 30.23” EPDL 7 5 24’ 11.07” N 100 35’ 30.10” EPDL 8 5 24’ 15.95” N 100 35’ 32.20” EPDL 9 5 24’ 15.48” N 100 35’ 30.02” E

(300 m) represented by weathered granite. At 100 mand 280 m of depth was identified as fractured zone.In conjunction between 2D ERI result of line 6 anddrilling data of PDL 6 can be correlated. The lowresistivity value (10 – 100 Ωm) from 2D ERI result atdepth 125 interpreted as groundwater potential zoneand it supported by drilling data. According thedrilling data, at 100 m of depth found fractured zoneof granite that has very high possibility as secondaryporosity to preserve groundwater resources.

5 CONCLUSION

2D Electrical Resistivity Imaging (ERI) Survey hasbeen successfully used in this study to locate anddelineate groundwater possibility potential at Kulim,Kedah, Malaysia in conjunction with chargeabilitydata and drilling data. The drilling location wasdetermined by groundwater potential zone that shownfrom 2D ERI result. The resistivity result show thatthere are 3 layers or zone within study area. Firstlayer is top soil (clay) in dry condition representedby moderate to high resistivity value ranging from100 – 100 Ωm at near surface. Another layeris extremely high resistivity value 300 Ωm up to2000 Ωm thatindicate granite as bedrock of studyarea. Groundwater potential zone shown by lowresistivity value ranging from 1 – 100 Ωm. Potentialzone of groundwater divided into 2 based on itsdepth, shallow groundwater potential with depth 25m to 75 m from the surface and deep groundwaterpotential with depth more than 75 m. drilling datawas proven all the interpretation of 2D ERI wherethe groundwater potential zone is fractured zone ofgranite. Fractured zone become secondary porositythat can be store groundwater.

Figure 8: Drilling data of PDL 6

ACKNOWLEDGMENTS

The authors would like to give an acknowledgment toGWS Drilling Engineering Sdn. Bhd. members fortheir cooperation in data collection that help authorsvery much in field. The authors also thanks to SilterraMalaysia SdnBhd for the great hospitality at field.

Groundwater Exploration using 2D Electrical Resistivity Imaging (ERI) at Kulim, Kedah, Malaysia

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Hamzah, U., Ismail, M. A., and Samsudin, A. R.(2008). Geophysical techniques in the study ofhydrocarbon-contaminated soil.

Hamzah, U., Samsudin, A. R., and Malim, E. P.(2007). Groundwater investigation in kuala selangorusing vertical electrical sounding (ves) surveys.Environmental geology, 51(8):1349–1359.

Hutchison, C. S. (1989). Geological Evolution of South-eastAsia. Clarendon Press, Oxford.

Jumary, S. Z., Hamzah, U., and Samsudin, A. R. (2002).Teknik-teknik geoelektrik dalam Pemetaan air masindi Kuala ( Mapping of groundwater salinity at KualaSelangor by geoelectrical techniques ).

Kausarian, H., Batara, B., Putra, D. B. E., Suryadi,A., and Lubis, M. Z. (2018). Geologicalmapping and assessment for measurement the electricgrid transmission lines in west sumatera area,indonesia. International Journal on AdvancedScience, Engineering and Information Technology,8(3):856–862.

Kausarian, H., Sri Sumantyo, J., Karya, D., Bagus, D., andAbdul Kadir, E. (2016). Geological mapping for theland deformation using small uav, dinsar analysis andfield observation at the siak bridge i and ii, pekanbarucity, indonesia.

Loke, M. H. and Barker, R. D. (1995). Least-squaredeconvolution of apparent resistivity psuedosection.Geophysics 60, 1682–1690.

Lubis, M., Anurogo, W., Kausarian, H., Choanji, T., Antoni,S., and Pujiyati, S. (2018a). Discrete equispacedunshaded line array method for target identificationusing side scan sonar imagery. In IOP ConferenceSeries: Earth and Environmental Science, volume176, page 012025. IOP Publishing.

Lubis, M. Z., Pujiyati, S. R., Pamungkas, D. S., Tauhid,M., Anurogo, W., and Kausarian, H. (2018b).Coral reefs recruitment in stone substrate on GosongPramuka, Seribu Islands, Indonesia. Biodiversitas,19(4):1451–1458.

N. Nwankwo, C. and O. Emujakporue, G. (2012).Geophysical Method of Investigating Groundwaterand Sub-Soil Contamination – A Case Study.American Journal of Environmental Engineering,2(3):49–53.

Saad, R., Nawawi, M. N. M., and Mohamad, E. T.(2012). Groundwater detection in alluvium using 2-Delectrical resistivity tomography (ERT). Electron. J.Geotech. Eng, 17.

Suryadi, A. (2016). Fault analysis to DetermineDeformation History of Kubang Pasu Formation atSouth of UniMAP Stadium Hill. Ulu Pauh,. JGEET(Journal Geosci. Eng. Environ. Technol, 1.

Suryadi, A., Batara, A., and N., S. (2019). Electricalresistivity imaging (ERI) and induced polarization(IP) survey to solve water drought problem at alorgajah. Melaka, Malaysia. IOP Conf. Ser. Mater. Sci.Eng. 532, 532:012025.

Suryadi, A., Putra, D. B. E., Kausarian, H., Prayitno, B.,and Fahlepi, R. (2018). Groundwater explorationusing Vertical Electrical Sounding (VES) Method atToro Jaya. Langgam, Riau. J. Geosci. Eng. Environ.Technol. 3, 3(226.).


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Risk Identification in Management System Process Integration WhichHave Impact on the Goal of Management System Components

Nastasia Ester Siahaan, Leni Sagita and Yusuf LatiefDepartment of Civil Engineering, Universitas Indonesia, Depok, [email protected], [email protected], [email protected]

Keywords: Risk Identification, Process Integration, Integrated Management System.

Abstract: Integrated Management System is a combination of two or more management system that facilitate acompany to achieve its goals. In this case, the integrated systems are Quality Management System (QMS),Environmental Management System, and Safety Management System. In integrating one management systemwith another, the approach used is process integration. In the process integration, there are several risksthat have impact on component goals in the management system process integration. The purpose of thisstudy is to identify risks that have an impact on the goals of the component and make the dominant risksmanagement strategy in the process integration. This study uses respondents’ survey strategy to identifyrisks in the management system process integration and case study strategy to find out the dominant risksmanagement strategies. The result of this study are risks in the process integration of management system anddominant risk management strategies.

1 INTRODUCTION

Implementation of Integrated Management Systemfor better quality management is a preferencefor many organizations (Muzaimi et al., 2017).Previously, organizations in the world were notexempt from construction companies too focused onindividual management systems (Mourougan, 2015).

The American Society of Quality (2015) dividesthe integration of management systems in threeapproaches which are process integration, riskintegration, and audit integration (Paraschivescu,2016). Process integration is a simulated device thataims to achieve optimization, feasibility, and integralsolutions in a sustainable design (Klemes et al., 2013)

Process integration is a method of combining partor all of the process to reduce resource consumption(Bugdol and Jedynak, 2015). This research usesa process integration approach that consists of 8components, namely the scope (1), leadership (2),integration of management policy (3), planning (4),support (5), operational (6), performance evaluation(7), and improvement (8) (Masuin et al., 2018).

The integration of system management hasadvantages for the organization. On the other hand,there are factors that inhibit and cause the purposeof the management system components to be notachieved. In the research of Rajkovic, Aleksic,

Milicevic, and Cudic (2008), the risk comes frominternal and external.

Process integration has a fairly high risk andcan have an impact on objectives. Therefore, it isnecessary to mature planning and identify the risksthat may occur either during management systemprocess integration. Once the risk is identified, therisk should be assessed based on possible occurrenceand impact it may cause. This is done to prevent anyaccidents that occur and can have an impact on projectwork in particular and on the safety of the surroundingenvironment in general.

From the explanation above, the study wasconducted with the aim of identifying the risks thatcan occur in the integration process. When the risk isidentified, the appropriate strategy can be applied tomanage risk (in this research is the dominant risk) andthe purpose of the component on process managementsystem integration can be achieved.

2 LITERATURE REVIEW

Integrated Management System (IMS) is amanagement system that combines all componentsinto a comprehensive system to facilitate theachievement of objectives and goals (Muzaimi, Chew,& Hamid, 2017). An IMS occurs when two or more

Siahaan, N., Sagita, L. and Latief, Y.Risk Identification in Management System Process Integration Which Have Impact on the Goal of Management System Components.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 41-48ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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systems unite by eliminating the independence of oneor both, but without losing their identities (Poltronieriet al., 2017). The integration consists of three mainmanagement systems: Quality Management System(QMS), Environmental Management System (EMS),and Safety Management System (SMS). The goal ofimplementing a management system by integratingseveral standards and documents is to achievesynergistic action in the organization (Zgodavova andBober, 2012).

IMS can be done by using 3 approaches,namely process integration, risk integration, and auditintegration (Paraschivescu, 2016). Process integrationis a method of combining part or all of the process toreduce resource consumption and harmful emissionsto the environment (Klemes, Varbanov, & Kravanja,2013). Bugdol et al (2015) explained that only 0-70%of all processes are integrated with the integrationmatrix (Bugdol & Jedynak, 2015). Bugdol (2015)said that not all processes need to be integrated.

This research uses a process integration approachthat consists of 8 components, namely the scope(1), leadership (2), integration of management policy(3), planning (4), support (5), operational (6),performance evaluation (7), and improvement (8)(Rofi’udin, Masuin, & Latief, 2018).

The three standards of QMS, EMS, andSMS are generally based on the principle ofcontinuous improvement by the Deming cycle(Plan-Do-Check-ACT) (Zeng et al., 2010). ThePDCA cycle is a concept of sustainable businessenhancement and additional troubleshooting (Singh,2013). The process integration of the third processmanagement system is also based on the PDCAapproach described in Figure 1.

Blue lines demonstrate leadership, integration ofmanagement policy, scope, planning, supporter,operational, performance evaluation, andimprovisation supporting the system to performprocess integration.

The red lines demonstrate PDCA cycle in processintegration and its correlation with managementsystem components. PDCA is an ongoing approachof management system in the flow of planning,implementation, checking and corrective action(Ribeiro et al., 2017). The planning stages consistof scope, leadership, and integration of managementpolicies. Leadership is needed to create the unityof goals and direction and involvement of peopleactivating an organization to align strategies, policies,processes and resources to achieve its objectives.The Input of planning in the integration processmanagement system is the needs and expectations ofstakeholders as well as internal and external issues of

the organization that are reflected in the scope of thesystem regarding organizational objectives and goals(Mourougan, 2015).

The implementation stage requires operationaland supporting components. The operation of thesystem must be done in accordance with the planned.In operation, it takes resources that build, implement,and maintain an integrated management system. Therequired resources are on supporting components.

Performance evaluation should be done to theresults and services produced in the operationalphase. The result of performance evaluation wasmade the foundation for a system improvement.Organizations must find and filter opportunities forimprovement and take important actions to respondto system sustainability objectives.

3 RESEARCH METHOD

This study uses two methods, respondents surveyand case studies. Respondents survey is suitableto answer what and how large the correlation ofeach survey variable. Analysis of surveys is usefulfor identifying a thing (Yin, 2013). Therefore, thisstrategy is used to identify risks in the integrationof process management systems that impact theobjectives of IMS components on constructioncompany organizations. The samples taken in thisresearch survey strategy are purposive samples. Inaccordance with the research restrictions that havebeen included in the research constraints in the firstchapter, selected respondents are the stakeholders ofthe construction management (government or privateowned) implementing QMS, EMS, and SMS.

Case studies are used to investigate a smallnumber of cases in depth, such as the study of why aproject failed (Tan, 2011). The case study strategy issuitable for answering the question ”How and why”(Yin, 2013). Yin (2013) argues that this strategyis conducted without controlling the characteristicerrors of the events studied and the research focuseson contemporary events. The case studies researchstrategy is due to questions relating to operationalrelationships that need to be tracked over time, ratherthan sheer frequency or incidence. This strategy issuitable for use in this research as it can answerstrategies for managing the dominant risk, so thatthe objectives of the integrated management systemcomponents can be achieved.


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Figure 1: Process integration model. Source: (Rofi’udin, Masuin, & Latief, 2018)

Figure 2: Research Operational Model

3.1 The Goals of Management SystemComponents

This study defines the purpose of the clauses orcomponents of the integration process management

system. The purpose of clauses is obtained by literarystudies and validated by experienced experts in theIntegrated Management System.

3.1.1 Scope

Scope assignment is required:

• to identify external and internal issues of theorganization

• to know the organization and its context andidentify the needs and expectations of thecompany

3.1.2 Leadership

Good leadership is one aspect that guarantees thecontinuity of the system achieved (Gianni andGotzamani, 2014). The goals of this component orclause are:

• to determine who is responsible for the QMSEMS, and SMS;

• to create a unity of purpose and direction oforganizational policy;

• to establish norms or standards that become areference to integrating management systems.

3.1.3 Integration of Management Policy

Integration of management policies integratesseveral elements, which are values, regulations,objectives, objectives, vision, and organizationalmission (Rofi’udin et al., 2018). The integrationof management policies is a process by which an

Risk Identification in Management System Process Integration Which Have Impact on the Goal of Management System Components

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institution performs a change from a irregularity andmulti-dimensional institution to a new governancesystem (Candel and Biesbroek, 2016). The goals ofthis component are:

• to provide instructions regarding the outcome ofan organization

• to define the most important and commonterminology in the design process approach,implementation, operation of integratedmanagement systems

3.1.4 Planning

Planning aims to set project scope, correct theobjectives, and determine the required actions for theproject’s purpose to be achieved. In planning, theinputs needed in the management integration processare the needs and expectations of stakeholders as wellas internal and external issues of the Organizationin relation to the objectives and objectives ofan organization (Mourougan, Auditing IntegratedManagement System for Continuing Suitability,Sustainability, and Improvement, 2015).

3.1.5 Support

The goals of this component or clause are:

• to determine and provide the resourcesrequired for the establishment, implementation,maintenance and continuous improvement

• to determine competence. Competence criterianeed to be set for each function and role relevantto the management system

• to raise the awareness of the people involved inthe management system of policies, significantaspects, and the impact of relevance on theiractivities.

• to ensure that the mechanisms that facilitate thecommunication in the management system runeffectively

3.1.6 Operational

The goals of operational are:

• to ensure that processes are ready to meet therequirements of the management system and toimplement the actions identified in the planning;

• to establish, implement and maintain thenecessary processes to address potentialemergency situations identified.

3.1.7 Performance Evaluation

Therefore, evaluation is an important part ofthe integration of process management systems.Performance evaluation includes inspection,measurement, analysis, assessment, internal audit,and management review. The goals of this componentare:

• to determine the range of monitoring andmeasurement necessary to assess the fulfilment ofobligations on the management system.

• to ensure that all processes are audited at therequired frequency and ensure that internal auditsare consistent and thorough, clear objectives andscope must be set for each audit

• to ensure the continued suitability, adequacy andeffectiveness of quality management system.

3.1.8 Improvement

This component has several purposes as follows:

• to determine the opportunity for improvement andapply the necessary actions to achieve the desiredresults.

• to eliminate the cause of the actual problem so asto avoid recurrence of the problem.

• to continuously improve the suitability, adequacyand effectiveness of management systems(quality, environment, safety) to improveperformance.

3.2 Risks in Management SystemProcess Integration

After defining the purpose in the clause in theintegration process, the findings gained are theidentification of risks that occur in the integrationprocess that may affect the purpose of the clause orcomponent. These risks are obtained by conductingrelated literary studies and conducting 2-round expertvalidation. The identified risks that are validated byexperts are as many as 95 risk factors.

3.2.1 Risk Assessment

Risk quality analysis is performed to determine thelevel of risk, whether low, moderate, or high. TheLevel of risk can be obtained by multiplying theaverage probability value and the average impactvalue. The average probability value is obtained bysumming the risk frequency and then divided by thetotal data obtained, which is 30 respondents. The


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average impact value is obtained by summing theimpact value then divided by the amount of data,which is 30 data. The following are indicators of thescale:

Table 1: Scale Assessment of Risk Frequency.

Scale Category Indicator0,1 Very Low Very small possibilities0,3 Low Less likely to occur0,5 Moderate Quite possibly happening0,7 High It may happen0,9 Very High Very likely to happen

Table 2: Risk Impact Assessment Scale.Scale Category Indicator

0,05 Very LowNo impact on the purpose of

components/clauses

0,1 LowSlight impact on the purpose of

components/clauses

0,2 ModerateInsufficient impact on the

purpose ofcomponents/clauses

0,4 HighImpact on the purpose of

components/clauses

0,8 Very HighGreatly affects the purpose of the

component/clause

After obtaining the average probability value andthe average impact value, the multiplication is donebetween the two values to get the risk value. Fromthe risk value, it is rated from 1 to 95 from the highestrisk rating to the lowest risk rating. Then, determinedthe level of risk by looking to match the table below.

Table 3: Risk Category.

Risk Score Risk Category0,01-0,05 Low Risk0,06-0,17 Moderate Risk0,17-0,72 High Risk

After the calculation is done, 10 of the highestrisks are obtained as follows in Table 4.

3.3 Strategies for Managing theDominant Risks

At the previous stage, the dominant risk has beenidentified through a qualitative assessment of risk.Dominant risk is interpreted as a high level of risk.This stage aims to collect data in the form of strategyproposals by outlining causes, preventive measures,impacts and corrective actions.

3.3.1 Causes and Impact of Risk

Causes that have been identified and validated asmuch as 9 causes. One cause could be the causefor some risk. The most common cause of risk isP2, which is lack of human resources competenceIn

Table 5 are compiled causes previously validated byexperts.

Table 5: Causes of Risk in Process Integration ManagementSystem.

Code Cause

P1Lack of awareness to consider inflation in theidentification of issues

P2 Lack of human resource competenceP3 Limited partner availabilityP4 Understanding the different scopes

P5Lack of socialization on the importance ofunity

P6 Preparation of an immature program

P7Management system problems are rarely usedas a subject in the company’s activities

P8Lack of training and certification obtained byhuman resources

P9Analysis of the root cost is not specific or noton target

The impact has been identified and validated byexperts as much as 35 impact. Any impact can occurdue to more than one risk factor. The most impactoccurs because the risk occurs is D2 and D6. D2is an implementation of an integrated managementsystem that is not optimal. D6 is an organizationalperformance goal not achieved. Table 6 are compiledimpacts previously validated by experts.

Table 6: Impacts of Risk in Process IntegrationManagement System.

Code Impact

D1 Identify external and internalorganization issues inaccurate

D2 Implementation of integratedmanagement system not optimal

D3Organizational risk does notcomply with the third process ofmanagement systems

D4 Company identification needand expectation inaccurate

D5 Workers ’ views are not equal orunequal

D6 Organizational performancegoals not achieved

D7 The audit process is not runningproperly

D8 Ineffective management system

3.3.2 Risk Response

After identification of the cause of the risk, apreventative action can be sought to prevent the causefrom occurring. The proposed preventive action is9 actions and has received approval from the expert.Preventive measures may be enforced to prevent morethan one cause. The most proposed preventive actionto prevent the cause is TP5, which is conductingrelated socialization activities. Table 7 are compiledpreventive actions previously validated by experts.


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Table 4: Highest Risks that Have Impact on the Goal of Management System Components

Risk Ranking Risk Score Goal of the ComponentComponent/Clause Scope

X1. Lack of inflationconsiderations

2 0.307

To identify external and internal issues of the

X2. The organization in theconstruction company doesnot set the Job Description& Standard/Requirementsintegrated to the 3 systems

3 0.291

X3. Weak partner selection 1 0.481 organizationX4. The organization in theconstruction company hasnot been able to identifyand analyse importantissues related to Risk andOpportunity in relationto quality, safety, andenvironment

9 0.218

X5. Inaccurate Corporatepriority orientation

8 0.231 To know the organization and its context and identifythe needs and expectations of the company

Component/Clause LeadershipX6. Lack of unity of view ofall employees who are alreadyworking under the previousstandard

6 0.24 To create a unity of purpose and direction oforganizational policy.

Component/Clause SupportX7. Lack of financialresources

7 0.235 To determine and provide the resources required forthe establishment, implementation, maintenance andcontinuous improvement

X8. Lack of employeemotivation

4 0.264 To raise the awareness of the people involved in themanagement system of policies, significant aspects,and the impact of relevance on their activities

Component/Clause Performance EvaluationX9. Lack of competenceauditors

10 0.215 To ensure that all processes are audited at therequired frequency and ensure that internal audits areconsistent and thorough, clear objectives and scopemust be set for each audit

X10. Evaluation of follow-upresults of audit results still lessprecise

5 0.258 To ensure the continued suitability, adequacy andeffectiveness of quality management system.

Table 7: Preventive Actions of Risk in Process IntegrationManagement System.

Code Preventive ActionTP1 Consider economic factors

TP2

Using competent human resources to setJOB Description & Standard/requirementsintegrated to all three managementsystems,

TP3 Conduct a partner prequalification

TP4Improving socialization and relatedtraining

TP5 Conducting socialization regarding

TP6Prepare programs for financial resourceneeds in detail

TP7Integrate management systems withbusiness processes

TP8Increase training and certification programsrelated to

TP9Ensuring evaluation of follow-up results ofaudit results researched

The risks that occur will cause impact. Therefore,it is necessary to identify the impact that will occur,so that it can be determined the corrective action.From table 8, it is possible to know that a proposedcorrective action was proposed to take as many as 8actions. The corrective action can be proposed formore than one variable. The most corrective actionto be proposed for risk factors is TK1, which is toperform the related review.


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Table 8: Corrective Actions of Risk in Process IntegrationManagement System.

Code Corrective ActionTK1 Perform related rereviews

TK2Set Job Description According toscope management system used

TK3Choose a new partner that’sconsidered stronger

TK4 Re-identifyTK5 Re-socialize

TK6To make planning the financialresources

TK7

Monitor motivation by integratingmotivation towards understandingthe management system in thecompany

TK8Audit by combining senior auditorsand junior auditors

Lack of HR competence is the cause of the manyrisks that occur. There are 5 risk factors that canoccur due to lack of HR competence. It is in thebackground of lack of perfect knowledge of humanresources in the field of integrated managementsystem considering the integration of managementsystem has not been implemented in many companies,especially construction companies(Asif et al., 2008).

Lack of HR competence can be prevented bypreventive measures such as conducting socialization,training, and certification related to integratedmanagement system. It is considered relevant becausethe most corrective action proposed in the study isto socialize the details of the integrated managementsystem. From the findings,it can be seen that theorganizational performance is not achieved is themost widely encountered impact when a risk occurs.As for the most proposed corrective action is to doa re-review of issues or problems that occur in theintegration of process management systems.

3.3.3 Pattern Recognition

After defining the cause and impact of the risks thatoccur, as well as propose preventive actions andcorrective actions, can be made recognition patternas in Figure 3. The recognition pattern is a flowfrom left to right, starting from preventive action,cause, risk, impact, corrective action. From therecognition pattern, it can be clearly seen the patternof interrelated strategies between one’s risk and theother risk. For example, TP5 can be done to preventthe causes of P5 and P6.

4 CONCLUSIONS

Process integration has a fairly high risk and can havean impact on objectives. Therefore, it is necessaryto mature planning and identify the risks that mayoccur either during management system process

Figure 3: Recognition Pattern for Top 10 Risks

integration.The identified risks must be managed bydefining their causes and impacts. Once known causeand impact, it can be proposed preventive measures toprevent occurrence and corrective action in responseif the impact occurs.

Based on this study, there are 10 highest risks inmanagement system process integration and 5 risksoccuring in scope component/clause.

ACKNOWLEDGMENTS

The authors would like to thank the financial supportprovided by University of Indonesia Universitythrough the PITTA 2019 funding scheme managedby Directorate for Research and Public Services(DRPM) University of Indonesia.

REFERENCES

Asif, M., Bruijn, E. J., and Fisscher, O. A. (2008).Process Embedded Design of Integrated ManagementSystems. POMS 19th Annual Conference. California.

Bugdol, M. and Jedynak, P. (2015). Integrated ManagementSystem. New York: Springer International Publisher.


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Candel, J. and Biesbroek, R. (2016). Towards a processualunderstanding of policy integration. Policy Sci,49:211–231.

Gianni, M. and Gotzamani, K. (2014). Managementsystem integration: Lesson from an abandonmentcase. Journal of Cleaner Production, 86:265–276.

Klemes, J., Varbanov, P. S., and Kravanja, Z. (2013).Recent development in process integration. ChemicalEngineering Research and Design, 91(10).

Masuin, R., Latief, Y., Zagloel, T. Y., and Sagita, L.(2018). Integrated Management System to AchieveSustainable Construction - A Conceptual Framework.AIP Conference Proceeding.

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Muzaimi, H., Chew, B. C., and Hamid, S. R. (2017).Integrated Management System: The Integration ofISO 9001, ISO 14001, OHSAS 18001, and ISO 31000.AIP Conference Proceeding, Melaka.

Paraschivescu, O. (2016). The advantages of the processof integrating quality management system. EconomyTransdisciplinarity Cognition, 19(2):45–55.

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Tan, W. (2011). Practical Research Method (4th ed.).Jurong: Pearson Education South Asia.

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The Performance of 3D Multi-slice Branched Surface Reconstruction onCPU-GPU Platform

Normi Abdul Hadi1 and Norma Alias2

1Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Malaysia2Ibnu Sina Institute, Universiti Teknologi Malaysia, 81310 Skudai, Johor

[email protected], [email protected]

Keywords: Spline, CPU-GPU, Parallel Processing.

Abstract: In this paper, a CPU-GPU algorithm to generate composite contour for 3D branching surface is presented.The composite contour is generated based on the data points from based and branched contours and located inbetween the two contours. Distance calculation is one of the processes in composite contour generation whichconsumes the most CPU time, therefore, this process is chosen to be executed on the GPU. The developedcomposite contour generation method on the CPU-GPU platform is then applied on CT images of Stanfordbunny and human pelvic with three different number of curve points per segment. These samples generate 12composite contours in total. The performance of the developed algorithm is measured based on the processingtime and the speedup. The result shows that the CPU-GPU algorithm has improved the speedup as high as150 times.

1 INTRODUCTION

In medical imaging, the studied object such as organsare typically stored as 2D contours with evenly spacedcross sectional images called slices (Sunderland et al.,2015). Two commonly used multi-slice imagesare Computed Tomography (CT) and MagneticResonance Images (MRI). CT scan plays a significantrole in a wide range of applications such as medicaldiagnosis, security, and manufacturing (Ziabari et al.,2018).

In medical diagnosis, the reconstructed 3D imagefrom CT scan must be in high resolution to assistclinical examinations (Kainz et al., 1901) for exampleto get the precise location as well as the size oftumour (Sentana et al., 2018). The 3D visualizationof the image must be easily understood for treatmentplanning and further analysis (Ge, 2018; Sunderlandet al., 2015). The challenges in handling CT scanimages are the amount of data to be considered andthe branched contours in some image slices. Theamount of data is in terms of the number of pixelsin each image slice which is usually 256times256or 512times512, and the number of image sliceswhich can exceed a hundred slices. Thus, the 3Dimage reconstruction process requires a powerfulprocessor to ensure the process can be run efficientlywith a sufficient amount of data within the optimal

processing time.CT scan images of real-life objects such as hand,

heart and bone cannot avoid a branching contoursituation where the number of contours in a slice isnot the same as the adjacent slice (Sunderland et al.,2015). This situation is also known as multi-furcatingsurfaces (Joshi and Bhatt, 2019).

Graphical Processing Unit (GPU) was originallydeveloped to calculate the 3D graphics in CentralProcessing Unit (CPU). Presently, the use of GPUhas been expanded to be used in scientific calculationto save computational time (Hosokawa et al., 2015).Each GPU consists of hundreds of cores that calculatethe given tasks in parallel. Thus, it is suitablefor a huge number of calculations which cannot beafforded by CPU to accelerate the calculation processand increase the accuracy of the result (Kainz et al.,2015). On the other hand, a small amount of datashould be processed in the CPU only to avoid idletime in GPU.

Since CPU and GPU have different abilitiesto process the data, numerous research have beencarried out to combine these two processors in thesame algorithm, for example in generating 2D font(Abdul Hadi, 2019) and 3D image (Hadi, 2018;Hadi and Alias, 019a). This algorithm is namedas CPU-GPU and hybrid computing (Sentana et al.,2018). The illustration of GPU is given in Figure 1

Hadi, N. and Alias, N.The Performance of 3D Multi-slice Branched Surface Reconstruction on CPU-GPU Platform.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 49-54ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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(Alias and Kamal, 2017)

Figure 1: The GPU illustration

The host and device in Figure 1 is the CPU andGPU, respectively. Each task is assigned to the devicethrough a kernel from the host. A GPU consists of anumber of grids with each grid containing a certainnumber of blocks, and each block having hundreds ofthreads. A thread communicates with another threadin a block by high- speed shared memory, and otherblocks by global memory (Alias et al., 2016; Hadi andAlias, 019b).

In this paper, the CPU-GPU algorithm isdeveloped in the branching surface reconstructionprocess. Details of the method is will be discussedin section 2. The performance of the developedalgorithm is then analyzed in section 3. This paperis concluded in section 4.

2 MATERIALS AND METHOD

2.1 CT Scan Images

This study employs two sets of CT scan imagesobtained from (Kels and Dyn, 2011) which areStanford bunny and human pelvic. The Stanfordbunny data, consisting of 254 slices, is the mostwidely used data in 3D image reconstructionprovided by Stanford Computer Graphics Laboratory,Stanford University (“Computer Graphics at StanfordUniversity,” n.d.). Human pelvic data consists of257 slices but only bottom part of the pelvic, whichconsists of 141 slices is considered in this work. Allconsidered images have undergone the pre-processing

stage to convert the original grayscale images tobinary images.

The number of branching cases in both datasetsare three for bunny and nine for pelvic. An exampleof branching case for each dataset are shown in thefollowing figure.

Figure 2: CT images with branching cases

In Figure 2, there are two types of branchingcases: (a) and (b) one-to-two case, and (c) isone-to-three case. This makes the 3D surface ofthe image discontinuous at the branching slice. Thereconstructed surface with discontinuous surface atthe branching slice is shown in Figure 3.

The branching slices have divided the 3D imageto five parts for bunny, and twelve parts for pelvic.Therefore, to join these parts, a new contour knownas composite contour is introduced to fit in betweenthe separated part of the image.

discontinuous parts

Figure 3: 3D surface with discontinuous branching parts

2.2 Composite Contour Generation

Composite contour is a generated contour usingcurve points from based and branched contours and


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located in between those contours. The flowchart ofcomposite contour generation is as follows:

Figure 4: The flowchart for composite contour generation

The first step is the cubic beta-spline curve fittingto all data points in the based contours. Beta-spline isa reliable curve developed by Brian A. Barsky in 1981(Barsky, 1981) based on G2 condition. This conditionmakes the beta-spline curve always continuous andsmooth, independent of the distribution of the controlpoints. The equation of cubic beta-spline curve (Hadi,2018) is as follows:

F(t) = [T ][M][V ] (1)

[T ] is the matrix of parameter t with 0<t<1, [V ] is theset of 4×4 control points, and [M] is the beta-splinebasis function (refer (Halim et al., 2018)). Then,the required ith curve points for each curve can beextracted by F(ti ). After that, distances betweeneach data points in the branched contours to the curvepoints in the based contours are calculated. Thepair of points (based-branched) with the minimumdistance is selected as the potential composite contourdata points. Finally, the midpoint between eachpair of points is appointed as the data point for thecomposite contour.

Figure 5 shows the datapoints of based andbranched contours, and the generated compositecontour.

The number of extracted curve points in thebranched contour must be sufficient to ensure the

Figure 5: Based, branched and composite data points

accuracy of the generated composite contour. Fewercurve points produces a smaller number of datapoints in the composite contour and less accuratereconstructed image. However, the processing timeto calculate the distance between each branched datapoint to each based curve points is also increased.Therefore, this study has employed the GPU to handlethe process.

2.3 Composite Contour Generation onGPU

Basically, the GPU is employed at the chosen stepin the CPU process. From the flowchart in Figure 3,only one process is executed on the GPU, which is thedistance calculation process. The earlier processes areexecuted on the CPU, and the extracted curve pointsare transferred to the GPU to calculate the requireddistance. Finally, the calculated distance is gatheredin the CPU to calculate the midpoint. The generatedcomposite contour is treated as other contours tofit beta-spline surface. The equation of beta-splinesurface is extended from the cubic beta-spline curveequation in (1) with parameters u and v as follows:

S(u,v) = [T ][M][V ][M]T [U ] (2)

where [V ] is the 16×4 control points. Theperformance of the developed algorithm is discussedin the following section.

3 RESULT

The employed CPU is Intel (R) XEON (R) (2.10GHz)with 2 processors, and the GPU is NVIDIATesla K20c running on Windows 10 64-bit. Theperformance is measured in terms of the processingtime for the whole composite contour generationprocess and speedup. The data for bunny and pelvicis combined in the same analysis

The Performance of 3D Multi-slice Branched Surface Reconstruction on CPU-GPU Platform

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3.1 Processing Time

Processing time is the time taken for a process tobe completed. This paper compares processing timebetween CPU-alone and the developed CPU-GPUalgorithm for different number of curve points percurve segment. There are twelve branching casesfor bunny and pelvic, and the processing time iscombined and compared in Figure 6.

Figure 6: CPU and GPU processing time for differentnumber of curve points

CPU-3, CPU-5 and CPU-10 (represented by solidlines) are the CPU-alone execution time for 3, 5and 10 curve points per curve segment, respectively.GPU-3, GPU-5 and GPU-10 (represented by dashedlines) are the time consumed by the CPU-GPUalgorithm. The number of curve segments for eachbranching case is presented at the x-axis. Processingtime for GPU is the total execution time including thecommunication between CPU and GPU.

Based on Figure 6, both CPU and GPU processingtime are increased with the increment of the numberof curve points. For 1155 data points for example,the increment of curve points from 3 to 10 points persegment has increased the CPU processing time 24×from 4.59s to 110.41s. Although the GPU processingtime has also increased, which is only 4.97× which is

still low. This shows that the GPU can still affordmore data compared to the CPU. Furthermore, thesudden increment in CPU time suggests that the CPUhas reached its limit.

3.2 Speedup

The speedup is calculated as time for CPU per timefor GPU to show how fast the GPU is as compared tothe CPU. The speedup for the developed CPU-GPUalgorithm is shown in Figure 7.

Figure 7: Speedup for three different number of curvepoints per segment

From Figure 7, all three curves have almost linearshape curves. This shows that the speedup of thedeveloped algorithm is getting better when largernumber of data points is considered. The position ofCP-10 curve is also higher than CP-5 and CP-3 whichshows that the speedup is better when the number ofcurve points per segment is increased. This is becausethe GPU has hundreds of threads to do the task. Thebest speedup from the figure is 150 for CP-10 whichshows that the GPU has accelerated the processingtime 150×.

3.3 Reconstructed 3D Images

The developed algorithm is applied on two datasets ofCT scan images: bunny and pelvic. The reconstructedsurface with branching slice has been shown in Figure3.

Figure 8 shows the same reconstructed 3D imagesas in Figure 3 but with composite contour. Basedon the figure, separated parts for both figures havebeen joined smoothly using cubic beta-spline surface.Stanford bunny is a widely used data for 3Dimage reconstruction. Thus, the comparison of thereconstructed bunny in this paper is compared to aprevious similar work by (Abdul Hadi et al., 2013),as shown in Figure 9.


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Figure 8: reconstructed surface with composite contours

Figure 9: The reconstructed surface with compositecontours

Figure 9(a) shows the generated bunny using themethod developed in this paper, and Figure 9(b) is thegenerated bunny using CPU-alone by (Abdul Hadi,Ibrahim, Yahya, & Md Ali, 2013). In Figure 9(a), thetexture on the bunny body and paws are clearer. Thisis because Figure 9(a) consists of 500 surface pointsper slice, while Figure 9(b) has only 75 surface pointsper slice due to the memory limitation of the CPU.

The CPU limitation also has disadvantage ingenerating composite contour. Thus, some branchingpart for example ear in Figure 9(b) is not smoothlyjoined and can be obviously seen.

4 CONCLUSION

In this paper, an algorithm for generating compositecontour on the CPU-GPU platform has beendeveloped. The composite contour occurs whenthe adjacent image slices have different number ofcontours. The decrement of the processing time andthe improvement of the speedup of the developedalgorithm suggest that the CPU-GPU platform issuitable to be employed in the composite contourgeneration since the process involves huge number ofdata points.

The capability of GPU also allows the numberof surface points to be high enough to produce thesmoothed and accurate surface. Furthermore, thefitted cubic beta-spline surface has high continuity(G2) to confirm the continuity of the surface.

For future research, more process will beconsidered to be executed on the GPU. Furtheranalysis of the performance will also be studied toensure the quality of the developed method.

ACKNOWLEDGMENTS

This study is supported by Ministry of Education,Malaysia, Universiti Teknologi MARA and UniversitiTeknologi Malaysia. Normi Abdul Hadi is aresearcher of Universiti Teknologi Malaysia under thePostdoctoral Fellowship Scheme.

REFERENCES

Abdul Hadi, N. (2019). Digital khat calligraphy usingbeta-spline curve on cpu- gpu platform.

Abdul Hadi, N., Ibrahim, A., Yahya, F., and Ali, J.(2013). Composite contour generation for beta-splinesurface reconstruction. AIP Conference Proceedings,1522:435–440.

Alias, N. and Kamal, M. H. A. (2017). Integrationof a big data emerging on large sparse simulationand its application on green computing platform.ARPN Journal of Engineering and Applied Sciences,12(12):3817–3826.

Alias, N., Mohsin, H. M., Nadirah, M., Mustaffa, S.,and Reyaz, R. (2016). Parallel artificial neuralnetwork approaches for detecting the behaviour ofeye movement using cuda software on heterogeneouscpu-gpu systems. Jurnal Teknologi, 78(12-2).

Barsky, B. A. (1981). The beta-spline: A localrepresentation based on shape parameters andfundamental geometric measures.

Computer Graphics at Stanford University. (n.d.), .Ge, T. (2018). Optimization of gpu-accelerated iterative ct

reconstruction algorithm for clinical use.Hadi, N. (2018). Big data simulation for surface

reconstruction on cpu-gpu platform. In Journalof Physics: Conference Series, volume 1192, page012006. IOP Publishing.

Hadi, N. A. and Alias, N. (2019a). 3-Dimensional HumanHead Reconstruction using Cubic spline surfaceon CPU-GPU Platform. International ConferenceProceedings Series by ACM.

Hadi, N. A. and Alias, N. (2019b). 3-Dimensional HumanHead Reconstruction Using Cubic Spline Surface onCPU-GPU Platform. Proceedings of the 2019 4thInternational Conference on Intelligent InformationTechnology, 16–20. ACM.

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Halim, S. A., Halim, M. S. A., and Hadi, N. A. (2018).Surface reconstruction from computed tomography(CT) image of human head with the effect of noise.AIP Conference Proceedings, 2013.

Hosokawa, F., Shinkawa, T., Arai, Y., and Sannomiya, T.(2015). Benchmark test of accelerated multi-slicesimulation by GPGPU. Ultramicroscopy, 158:56–64.

Joshi, K. and Bhatt, A. (2019). Experiments with t-meshfor constructing bifurcation and multi-furcation usingperiodic knot vectors. Computer-Aided Design andApplications, 16:382–395.

Kainz, B., Steinberger, M., Wein, W.,Kuklisova-murgasova, M., Malamateniou, C.,Keraudren, K., and . . . Rueckert, D. (1901).Corrupted Stacks of 2D Slices. 34(9).

Kels, S. and Dyn, N. (2011). Reconstruction of 3D objectsfrom 2D cross-sections with the 4-point subdivisionscheme adapted to sets.

Sentana, I. W. B., Jawas, N., and Wardani, A. E. (2018).Hybrid cpu and gpu computation to detect lungnodule in computed tomography images. In 2018Third International Conference on Informatics andComputing (ICIC), pages 1–6. IEEE.

Sunderland, K., Woo, B., Pinter, C., and Fichtinger, G.(2015). Reconstruction of surfaces from planarcontours through contour interpolation. MedicalImaging, (9415.).

Ziabari, A., Ye, D. H., Srivastava, S., Sauer, K. D.,Thibault, J.-B., and Bouman, C. A. (2018). 2.5d deeplearning for ct image reconstruction using a multi-gpuimplementation. 2018 52nd Asilomar Conference onSignals, Systems, and Computers, pages 2044–2049.


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Tile-based Game Plugin for Unity Engine

Salhazan Nasution1, Arbi Haza Nasution2 and Arif Lukman Hakim1

1Department of Informatics Engineering, Universitas Riau, Pekanbaru, Indonesia2Department of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

[email protected], [email protected], [email protected]

Keywords: Unity, Plugin, Tile-Based Game, Level Editor.

Abstract: Nowadays video games have become mainstream in the modern lives of people in the world. Along withthat, the game development process has been dramatically improved by the emergence of free to use gameengines. One of the most used game engines worldwide is Unity. Unity provides strong features to supportits developers, one of them is the ability to use plugins. Meanwhile, tile-based games are also very popular.Without support from any kind of plugins, development of tile-based games will increase development time,especially in level editing process. Readjusting each tile to a perfect position while it is being added to Unityscene view is very time-consuming. This plugin aims to solve this problem by extending the Unity editorscript. This plugin provides support for creating and deleting tiles, enables the developers to cut the timeneeded to create levels in tile-based games.

1 INTRODUCTION

The popularity of video games has increased sincethe first emergence of video games around the 1950s.Video games have always been a component of popculture and being the center of the multi-billion dol-lar entertainment industry. Nowadays because of theinternet, the availability of game development soft-ware has been increasing, along with the ease of gameready device distributions and game distributions it-self, encouraging advancement in the game develop-ment industry (Bergonse, 2017). Game developmentsoftware, usually called game engine is a tool de-signed to reduce budget, complexity, and time neededto market in a game development process. This soft-ware creates an abstraction layer above the main func-tionality of creating a video game. This abstractionlayer is packed with the tools that are designed tofunction as the functional components that can bemodified or added with an addition of third party com-ponent (Halpern, 2018).

Game engines have been popular than before. Themost popular game engine with the number of devel-opers is Unity, with more than 5,5 million developerslisted in 2016, then followed by Unreal Engine, thathas reached more than 4 million developers in 2017(Salomao et al., 2019).

Unity is a game engine that gives huge benefitscompared to the other game engine that is available

on the market nowadays. Unity gives drag and dropcapability on its visual workflow and supports script-ing in C# language, which is very popular. Unity haslong been supporting 3D and 2D graphics; also Unityprovides a set of tools for these two types of graphicsthat is always improving and always been very easyto use on each update. Unity also made especiallyto support developers using plugins from third partysoftware. Unity also provides its asset store that hasso many plugins for Unity itself, made from develop-ers and made for developers (Halpern, 2018).

The plugin itself consisted of many things, amongthem are assets like 3D models, 2D sprites, textures,materials, sound effects, music, scripting, particle ef-fects, and many more. All of them are available inUnity asset store, from the free to paid ones.

Beside of that, tile-based system for makinggames have been used widely, thus becoming a defacto for a standard approach to making games formost of the game design technology. This system isnot only for 2D games, 3D games could also use thesame system. Tile-based systems are popular becausethis system solves a different amount of problems thatare so complex to be solved with other ways (Spuy,2010).

Unity engine does not provide support to makegames with tile-based system, related plugins withgood functionality had a paywall, and the free oneslack good functionality, so the developer has diffi-

Nasution, S., Nasution, A. and Hakim, A.Tile-based Game Plugin for Unity Engine.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 55-63ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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culty in terms of accessibility to good tile-based sys-tem plugin. This study was done in order to make abetter tile-based system than before more accessibleto more Unity developers especially in terms of edu-cation.

2 LITERATURE REVIEW

The foundation of this research is the history of previ-ous researches related to the plugin for game engines.

The first research is entitled “Uni-CAVE: AUnity3D Plugin for Non-head Mounted VR DisplaySystems”. Unity3D has been popular and is free touse by many game developers especially for design-ing and constructing a virtual environment. How-ever, Unity3D itself has not yet have an immersiveprojection base Virtual Reality (VR). The objectiveof this research is to give a free solution to adaptUnity3D with any VR immersive projection system.Uni-CAVE provides support for multiple VR displayconfigurations, multiple stereo techniques, 3D head,and wand tracking system, and display synchroniza-tion. Uni-CAVE is a plugin that is meant to ease thedevelopment of immersive 3D VR display systemson Unity3D. This plugin has been tested on a six-sided CAVE environment, using active quad-bufferedstereo, on twenty curved tiled display screen systemthat uses side-by-side stereo, also two projector powerwall using quad buffered active stereo and dual-pipeactive stereo. These configurations can be saved asUnity prefabs, allowing to be reused multiple timesby developers (Tredinnick et al., 2017).

The second research is entitled “A Game EnginePlug-in for Efficient Development of InvestigationMechanics in Serious Games”. Educative SeriousGames (SG) has been widely used in education, train-ing, and domain like sports and medical treatment.Regardless of the increasing interest on SGs, the dis-tributions of SGs is constrained by the difficulty ofcombining the effectiveness of education with enter-tainment, a high resource needed to the developmentprocess, and involves different fields of study. This re-search proposes a development framework to supportinvestigation in SG. This framework provides a de-scription template which allows developers to definewhat items that had to be investigated in a structuralway possible. The descriptor is processed on runtimeby the game engine plugin which is responsible tomanage the virtual environment and the correspond-ing gameplay. The objective of this research is toease the development of Open World Serious Gamesalso for knowledge domain experts that haven’t hadany programming experience yet. This plugin pro-

vides an XML template to easily manage global vari-ables, choice of the game plot and the correspondingsolution, data distributions in different POIs (Pointof Interests), management of suspected parameters,graphic visualization of POI information with the cre-ation of custom graphic elements, translation of userinterface into different natural languages, manage-ment of graphic skins, management of the music,management of the solution of the game (one solutionfor each plot), generation of the help of the game, andthe parsing of the XML file containing parameters ofthe game (Carmosino et al., 2017).

Another research is entitled “HPGE: An HapticPlugin for Game Engines, Serious Games”. The mo-tivation behind using haptic feedback in a game isthe educational benefits from the sensory and motorexperience, also active exploration from the player.Besides, many VR applications have promising forcefeedback devices. The objective of this research isto create a plugin that allows haptic device integra-tion within Unity3D, because Unity3D does not sup-port haptic device integration. The features includedin this plugin are drag-and-drop support, Graphi-cal User Interface (GUI), haptic texture rendering,custom haptic force-feedback, and device logging.This plugin has been used in two serious games thathave been developed to teach geometry to children(Balzarotti and Baud-bovy, 2017).

Another interesting research is “An Unreal En-gine 4 Plugin to Develop CVE Applications Lever-aging Participant’s Full Body Tracking Data. Alongwith the availability of powerful open-source gameengines, labs that have research in a VR field havebeen migrated to use game engines, which is a newdevelopment environment that is far more produc-tive, customizable, extensible, easy-to-use interface,rich of features, and almost no budget needed, withthe addition of multi-platform development. On theother side, CVE (Collaborative Virtual Environment)itself, allows two or more people to work in a vir-tual working environment to do work that is difficultto be done by one person. The unique feature thatstands out from CVE is the ability to bring full-bodymovement from a person in the real world to the VR.The objective of this research is to implement a plu-gin that could manage full-body tracking in a multi-player CVE network environment in Unreal Engine4. This plugin features mainly the network communi-cation plugin and the animation plugin. The networkcommunication plugin is used to manage the interac-tion between participants in a network, while the ani-mation plugin manages the skeletal animation of par-ticipant’s 3D model in the environment (Luongo andLeoncini, 2018).


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The last reviewed research is entitled “UnrealHap-tics: A Plugin System for High Fidelity Haptic Ren-dering in the Unreal Engine”. VR devices have beenmore affordable, such as Oculus Rift and HTC Vive.Modern game engines like Unity and Unreal alsosimplifies the VR development process dramatically.However, these VR devices are only limited to twotypes of human sense, vision and hearing. This limitsa large number of people that cannot benefit from VRcontents like the blinds. To overcome this problem, ahaptic device is created, which is to stimulate sense oftouch. Because Unreal Engine does not support hap-tic device, hence this study is done to create a pluginfor Unreal Engine that allows Unreal Engine to sup-port haptic devices. This plugin consists of three sep-arate plugins that support one another. Those plug-ins are named HAPTICO, COLLETTE, and FORCE-COMP. HAPTICO is a plugin that enables developersto use haptic devices directly from Unreal Engine 4automatically. COLLETTE is the collision detectionplugin that does the collision detection integrated withthe haptic device. FORCECOMP is the plugin used tocalculate force computation needed for the physicalsimulation of forces (O. Rudel et al., 2018).

2.1 Tile based Game

Tile has always been popular in the context of 2Dgame development, as the reusable terrain element,that allows bigger terrain construction, which is be-cause of the size and management issues cannot behandled with normal bitmaps. This technique is verypopular in the past, but this technique is back in de-mand in the context of a handheld device. Besideof that, there is a growing trend towards the revivalof the 2D games with the emphasis on more pop-ulated terrain, more intelligent actions, stronger ef-fects, and character design using 3D modeling instru-ment for 2D games. Tile is a tiny bitmap, usually16x16 or 32x32 pixels, used as terrain constructing el-ement. This technique is still used until now, and thistechnique offers many benefits for game developers.Lesser game storage size and faster terrain process-ing can be achieved because only little informationis needed to be described. Another benefit from thissystem is if the developer wants to construct biggerterrain, developer only had to add new tiles withoutdesigning all bitmap from the beginning. Games thatare using tiles as the basis graphic component withinare called tile-based game (Karouzaki et al., 2007).

Figure 1: Tile-based games 2D (top), and 3D (bottom).

2.2 Game Engine

A game engine represents all basis of a game, provid-ing functionality to do optimized and efficient graph-ics rendering, accessing file system, player inputsthrough input devices such as keyboard and mouse,audio player, network connectivity also saving andloading game status (Freiknecht et al., 2016).

Game engine is a framework for game develop-ment that has some core parts, the audio engine, ren-dering engine, and physics engine. The audio engineplays a key role in the game. If the player’s charac-ter is fighting an enemy, and the mechanism uses asword, the sword will produce a sound effect whilethe sword comes in contact with the enemy’s sword.That part of the work is done by the audio engine.Audio engine is also used to play background musicto enhance the atmosphere of the game. Renderingengine helps to choose what is actually displayed tothe player. The output is a visual treat to the playerwhile playing the game. Rendering helps to make thegraphical content of the game feels alive. Physics en-gine helps to simulate physics in the game (Nandy andChanda, 2016).

2.3 Unity3D

Unity (also known as Unity3D) is a game engineand an Integrated Development Environment (IDE)


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to make interactive media, usually video games. TheChief Executive Officer (CEO) of Unity, David Hel-gason describes that “Unity is a tool set that used tomake games, and Unity is a technology that executesgraphics, audio, physics, interactions, and network-ing”. Unity is known by the capability of fast proto-typing and big amount of publishing target platform(Karouzaki et al., 2007).

Figure 2: Unity Engine Editor Interface.

2.4 Plugin

Plugin is a binary extension unit that used for ap-plication which the architecture allows to introducefunctionality to end users after application installa-tion. Plugin is a software entity that has a closerelation with components. Component-based devel-opment usually does not consider that componentscannot be added in the application after installationprocess. Components usually used to facilitate ap-plication construction itself (Cervantes and Villalo-bos, 2006). Plugin is a part of the code that modi-fies runtime behavior. Language can be consideredas a framework that provides a set of extension partswhich plugins could implement new functionalities tothe language. According to programming languageextension aspects, there are three categories of an ex-tension part : (1) algorithm related. (2) creation ofnew rules and rule execution cycle management and(3) language syntax related (Cuadrado and Molina,2006).

2.5 Microsoft Visual Studio 2017

Microsoft Visual Studio 2017 is an integrated devel-opment environment (IDE) from Microsoft. VisualStudio is used to develop computer programs such aswebsites, web apps, web services, and mobile apps.The latest version of Visual Studio 2017 has full fea-tures to develop apps for Android, iOS, Windows,web and cloud (S. Durano, 2018).

Figure 3: Microsoft Visual Studio IDE Interface.

3 METHODOLOGY

In this section, we detail the research methodology inthis research as depicted in Figure 4.

3.1 Literature Study

This step is done to get knowledge on the theory basisthat are needed to do this research. Literatures thathave been studied in this research is related to tile-based game, game engine, Unity3D and plugin.

Figure 4: Research methodology.

3.2 Level Editor Design

After the preparations of tools and materials needed,the next step is to design the level editor. The leveleditor will be implemented using a grid system. Thegrid will be used to position the tiles. The level editoritself is described as in Figure 5.


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Figure 5: Grids as shown in Unity Editor.

Figure 6: Level editor class diagram.

As shown in Figure 6, the main component ofthis system is MyLevelEditor script. MyLevelEditorscript extends the Unity default Editor script to im-prove Unity’s base editor as shown in the code in Fig-ure 7. In this script there is OnSceneGUI() methodthat used to position the 3D cursor on the grid, andmanages what will happen when mouse is clicked,moved, dragged, and when mouse is leaving sceneview. Also, there is a Snap method that used to snapthe 3D cursor to the squares in the grid. The Round()method used to round values needed to snap the 3Dcursor to get the right position.

Afterward there is a script named MyLevel whichis used to contain all properties that can be modifiedand configured by the developers using this plugin.These properties will be used in the MyLevelEditorscript. In this script there is only one method, whichnamed Awake(). This Awake() method is executed inedit mode to allow editing of properties out of gameruntime.

MyLevel script needs another script named My-Cursor. Game object that had MyCursor script willbe the 3D cursor in the scene view. MyCursor alsocontains configurations for the color of the 3D cursor.

And then there is a script named MyCursorEdi-

Figure 7: MyLevelEditor extends Unity’s editor script.

tor that used to change the 3D cursor color as in theconfigurations saved in MyCursor script. The color ofthe 3D cursor will also change depends on the type ofoperation in the MyCursorType enumeration.

3.3 Level Editor Implementation

Level editor that has been designed before will be im-plemented in Unity. The level editor will be imple-mented by extending the script named Editor in Unity,and then adding GUI element in the Unity scene view,so the developers can add, move also delete objectsthat are needed in the level.

3.4 Level Editor Testing

The implemented level editor will be tested, has thefunctionalities run as expected. If there are deficien-cies and bugs, a correction will be made so the func-tionalities could run as expected.

3.5 Plugin Deployment

After the testing process has done, the plugin will bedeployed to game developers. Game developers couldtry all of the features implemented in the plugin usingtheir own self-made asset. This plugin will be de-ployed with a user guide and a questionnaire. Theguide will be used to inform developers how exactlyto use this plugin when a questionnaire is used to getfeedbacks from the developers about the performanceof this plugin.

3.6 Result Analysis and Discussion

The result of this research is the questionnaires thatare collected from the game developers that were us-ing this plugin. From all the scores obtained from thequestionnaire, analysis and conclusion can be made,is this plugin effective or not to speed up the processof developing a tile-based game.


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4.1 Graphical User Interface

This level editor implemented using a Unity game ob-ject. This game object will be placed in a hierarchyand will appear in the scene view as shown in Figure8. To create levels, developers have to select the leveleditor game object in the hierarchy by clicking it. Af-terward the level editor can be used freely in the sceneview.

Figure 8: Level editor object named MyLevel in the hierar-chy.

This game object is called MyLevel. MyLevel hasa child object named Cursor. This Cursor object isused to be a 3D cursor that will appear in the sceneview to help level editing process. Besides the 3Dcursor, the grid will appear to help game developers tosee the positions that tiles could be added onto. Theposition of the tile will be placed exactly above thesquare of the grid as shown in Figure 9.

Figure 9: Level editor display in the scene view whenMyLevel object has been selected in the hierarchy.

The 3D cursor can be moved by moving mousepointer in the scene view. This 3D cursor will be usedto choose where the added or deleted tile will be inthe scene view.

Later, when MyLevel object is selected in the hier-archy, a component of the game object will appear in

the inspector, which is the representation of MyLevelscript. In this component, there will be properties tobe configured freely by the game developers as shownin Figure 10 and explained in Table 1.

Figure 10: MyLevel game object on the inspector.

All of those properties above could be modified asdesired by the developers. To add or delete an object,tile or decoration, game developers may choose op-eration type in the CursorType property as shown inFigure 11.

Figure 11: CursorType property display after it has beenclicked on the inspector.

The color of the 3D cursor can change based onthe color configuration in the properties of MyLevelgame object as shown in Figure 12.

After choosing an operation type developers canadd or delete an object, tile or decoration, by click-ing the 3D cursor on the desired position in the scene


60

Table 1: Properties from MyLevel script component.

No. Property Name Functionality1. Tiles Contains the amount and the types of tile objects that can be added

to the scene view.2. Decors Contains the amount and the types of decoration objects that can be

added to the scene view. These decoration objects will be addedabove the exact position of the tiles.

3. Add Tile Color Contains the color of the 3D cursor for the tile addition operation.4. Delete Tile Color Contains the color of the 3D cursor for the tile deletion operation.5. Add Decor Color Contains the color of the 3D cursor for the decoration addition op-

eration.6. Delete Decor Color Contains the color of the 3D cursor for the decoration deletion op-

eration.7. Cursor Type Contains all types of operation that can be done by the game de-

veloper in the level editor. The color of the 3D cursor will changecorrespondingly to the four color properties above.

8. Index Spawn A field to choose the index from a tile or decoration that will beadded to the scene view.

view.

Figure 12: 3D cursor color based on operation type, A) Tileaddition, B) Tile deletion, C) Decoration addition, and D)Decoration deletion.

Without the use of this plugin, game developerswill consume more time creating levels in tile-basedgames, because the coordinate of the tiles need tobe configured for each new tile added to the level.The coordinate must be perfect in order to make thetiles not colliding with each other and leaving a smallspaces between tiles. Hence, the tiles will be placedin a perfect way to create the aesthetic of tile-basedgame world. The implementation without the use ofthis plugin is shown in Figure 13.

With the use of the plugin, developers will havetheir time reduced to create levels, because this pluginprovides a point and click feature on tile operations asshown in Figure 14.

The same process also applies to deleting tiles.Without the use of the plugin, tile deletion is done

Figure 13: Coordinate configuration for each new tile addedto the scene view without plugin use.

Figure 14: Point and click feature for adding new tiles tothe scene view using the plugin.

by deleting each tile manually from the hierarchy asshown in Figure 15.

Meanwhile using the plugin, developers maychoose the tile deletion operation type, then clickingand dragging on the tiles which they want to delete asshown in Figure 16.

This plugin only supports 3D tile-based game de-velopment. But game developers may use it to builddifferent type and genres of games, because the leveleditor is independent with the main game mechanicsand game graphics scripting.


61

Figure 15: Deleting tile in the scene view without pluginusage.

Figure 16: Deleting tiles in the scene view using the plugin.

4.2 Plugin Convenience Test Results

Convenience test has done by five developers, andthese results have been collected from the question-naires filled by each developer. A questionnaire witha Likert scale is answered based on defined multiplechoice questions, where the answers represent devel-opers’ rating and opinion of some criteria like sat-isfaction, agreement, and so forth (Lubiano et al.,2017). Following (Sagi et al., 2015), the conveniencerate of this plugin from the answers given by respon-dents is calculated by the formula below:

ConvenienceRate(%) =AverageScore

IdealScore×100% (1)

The average score is calculated by the formula be-low:

AverageScore =TotalScore

AmountO f Questions(2)

Table 4 shows the plugin convenience test resultsaccording to Likert scale calculation.

The plugin convenience test has the results asshown in Table 4. In the first question, it can be seenthat there is one person chose the “Neutral” choicewith the score of three points, three people chose the“Agree” choice with the score of four points and oneperson chose the “Very Agree” choice with the scoreof five points. Thereafter the total choice of the re-spondents will be multiplied by the score of theirchoices, resulting in a total score for the first ques-tion equals to 20 points. This total score will be used

Table 2: Likert scale.

No. Category Score1. Very Agree (VA) 52. Agree (A) 43. Neutral (N) 34. Disagree (D) 25. Very Disagree (SD) 1

Table 3: Convenient rate.

No. Category Score1. Very Inconvenient 0%-19.99%2. Inconvenient 20%-39.99%3. Slightly Convenient 40%-59.99%4. Convenient 60%-79.99%5. Very Convenient 80%-100%

to calculate the plugin convenience rate for the firstquestion by dividing total score with the number of re-spondents equals to five and then multiplied by 100%,resulting in 80% of convenience rate for the first ques-tion. According to the Likert scale that has been de-signed as shown in Table 4, then the category of 80%rate of convenience is “Very Convenient”. The calcu-lations will be the same for the next question until thelast question. Afterward the total score and the con-venience rate of each question will be averaged, re-sulting in the final plugin convenience rate of 77,7%.According to the Likert scale, this results in the cate-gory of “Convenient”.

5 CONCLUSION

This plugin is made to ease the development of tile-based game on Unity game engine. This plugin hasthe ability to point and click tile level editing di-rectly in the scene view, also supporting custom tilesmade by developers to be used along with this plu-gin. With this plugin, game developers who want todevelop tile-based game don’t have to deal with thetime-consuming tile configuration for each new tileadded to the scene and also manual tile deletion onthe scene view. Hence, this plugin creates the op-portunity for game developers to create levels largerin scale than before, because of how time-saving itis. This plugin has been tested by five game devel-opers with experience in game development. Resultsas shown in results and discussion, the convenienceof this plugin is rated “Convenience” with an averagepercentage of 77.7%.


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Table 4: Plugin convenience test result.

No Statement Total Answer Total Score %VD D N A VA1. 3D cursor controls are very convenient. 1 3 3 20 802. Operation type selection for tile and deco-

ration objects is very convenient.2 2 1 19 76

3. Adding tiles and decorations to the sceneview is very convenient.

1 1 3 22 88

4. Deleting tiles and decorations from thescene view is very convenient.

1 1 3 22 88

5. Choosing colors for every 3D cursor typeis very convenient.

1 2 2 21 84

6. Adding new types of tile and decoration tothe inspector is very convenient.

2 2 1 19 76

7. Adding new types of tile and decoration tothe scene view is very convenient.

3 1 1 13 52

Total 136Average 19,4 77,7

ACKNOWLEDGEMENTS

The author would like to thank the developers in-volved in the plugin convenience test for their supportand honest feedback throughout the execution of thisresearch.

REFERENCES

Balzarotti, N. and Baud-bovy, G. (2017). HPGE: An Hap-tic Plugin for Game Engines. Games and LearningAlliance, 10653:330–339.

Bergonse, R. (2017). Fifty Years on, What Exactly is aVideogame? An Essentialistic Definitional Approach.The Computer Games Journal, 6(4):239–255.

Carmosino, I., Bellotti, F., Berta, R., De Gloria, A., andSecco, N. (2017). A game engine plug-in for effi-cient development of investigation mechanics in se-rious games. Entertainment Computing, 19:1–11.

Cervantes, H. and Villalobos, S. C. (2006). Usinga Lightweight Workflow Engine in a Plugin-BasedProduct Line Architecture. Component Based Soft-ware Engineering, 4068:198–205.

Cuadrado, J. S. and Molina, J. G. (2006). A Plugin-BasedLanguage to Experiment with Model TransformationJesus. Model Driven Engineering Languages and Sys-tems, 4199:336–350.

Freiknecht, J., Geiger, C., Drochtert, D., Effelsberg, W.,and Dorner, R. (2016). Game Engines Jonas. Seri-ous Games, pages 127–161.

Halpern, J. (2018). Developing 2D games with Unity : in-dependent game programming with C#.

Karouzaki, E., Savidis, A., Katzourakis, A., and Stephani-dis, C. (2007). Tile Dreamer: Game Tiles Made

Easy. Universal Access in Human Computer Inter-action. Coping with Diversity, 4554:382–391.

Lubiano, M. A., Salas, A., De, S., Saa, R. D., Montenegro,M., and Gil, M. A. (2017). Soft Methods for DataScience. 456:329–337.

Luongo, C. and Leoncini, P. (2018). An UE4 Plugin to De-velop CVE Applications Leveraging Participant’s FullBody Tracking Data. Augmented Reality, Virtual Re-ality, and Computer Graphics, pages 610–622.

Nandy, A. and Chanda, D. (2016). Beginning Platino GameEngine.

O. Rudel, M., Johannes, G., Weller, R., and Zachmann, G.(2018). UnrealHaptics: A Plugin-System for High Fi-delity Haptic Rendering in the Unreal Engine. IEEEComputer Graphics and Applications, 38(2):28–30.

S. Durano, V. M. (2018). Understanding Game ApplicationDevelopment.

Sagi, F. N., Udiana, I. M., and Ramang, R. (2015). KajianFaktor-Faktor Penyebab Ketidakefektifan Kinerja Ter-minal Bus Haumeni Kota Soe Kabupaten Timor Ten-gah Selatan. Teknik Sipil, IV(2):183–194.

Salomao, A., Andalo, F., and Luiz Horn Vieira, M. (2019).How Popular Game Engine Is Helping ImprovingAcademic Research: The DesignLab Case. Ad-vances in Human Factors in Wearable Technologiesand Game Design, 795:416–424.

Spuy, R. V. D. (2010). Game Design with Flash.Tredinnick, R., Boettcher, B., Smith, S., Solovy, S., and

Ponto, K. (2017). Uni-CAVE: A Unity3D plugin fornon-head mounted VR display systems. IEEE VirtualReality, pages 393–394.


63

Image Segmentation of Nucleus Breast Cancer using Digital ImageProcessing

Ana Yulianti1, Ause Labellapansa1, Evizal Abdul Kadir1, Mohana Sundaram2, and Mahmod Othman2

1Department of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Department of Fundamental & Applied Sciences, Universiti Teknologi Petronas, Perak Darul Ridzuan, Malaysiaana.yulianti, ause.labellapansa, [email protected], [email protected], [email protected]

Keywords: IHC Breast Cancer, ER/PR Receptor, Image Processing

Abstract: One of examination methods of breast cancer cells is using Immunohistochemistry (IHC). IHC is used todetermine the status of Estrogen Receptor (ER) and/or Progesterone Receptor (PR). The bonding reactionoccurring between the cell and the painting results in the color of the nucleus cell being blue which signifiesthe negative and brown ER/PR hormone for positive ER/PR. The given hormonal therapy will be effective tobreast cancer patients if they have positive ER/PR receptors. Up to now the Anatomy Pathology specialistcalculatses the percentage of positive cells that have been marked semiquantitatively. This is time-consuming,costly, subjective and tedious, thereby impacting the length of time required in determining appropriate therapyfor breast cancer patients. This study analyze the image of IHC breast cancer to determine the assessment ofER/PR hormone receptor using image processing. The use of kernels of different sizes shows differences inthe results of cell segmentation in connective tissue. The use of 3×3 and 1×1 kernels has indeed succeeded inremoving cells in the connective tissue, but not all cells in the connective tissue can be identified. If this stephas been completed, then the next process until cell count can be done.

1 INTRODUCTION

Breast cancer is a dangerous disease that occurs dueto the uncontrolled cells growth. One of examinationmethods of breast cancer cells is using Immunohisto-chemistry (IHC). IHC is used to determine the statusof Estrogen Receptor (ER) and/or Progesterone Re-ceptor (PR). The IHC technique is performed by ap-plying Hematoxylin and Diaminobenzidine and ob-serving the antibody presence bonds by microscopebased on the observation by Pathologyst. The bond-ing reaction occurring between the cell and the paint-ing results in the color of the nucleus cell being bluewhich signifies the negative and brown ER/PR hor-mone for positive ER/PR. The given hormonal ther-apy will be effective to breast cancer patients if theyhave positive ER/PR receptors. IHC image Positiveestrogen receptors and negative show in the Figure 1.

Up to now the Anatomy Pathology specialist cal-culatses the percentage of positive cells that have beenmarked semiquantitatively. This is time-consuming,costly, subjective and tedious (Limsiroratana andBoonyaphiphat, 2009; Estrogen, ), thereby impactingthe length of time required in determining appropriatetherapy for breast cancer patients. This study will an-

(a) (b)Figure 1: IHC image (a) Positive estrogen receptors (b)Negative estrogen receptors

alyze the image of IHC breast cancer to determine theassessment of ER / PR hormone receptor using digitalimage processing which is expected to help doctors todetermine whether the breast cancer patients requirehormonal therapy or not.

(Kostopoulos et al., 2007; Calhoun et al., 2019)provides a positive estrogen receptor assessment byanalyzing IHC images using a color texture feature.Assessment of positive ER receptor status with com-puter method is done through 2 stages, ie. stage Iof segmentation of nucleus using Otsu’s global im-age threshold method and morphology operation andstage II classification of nucleus based on brownand blue color using feature selection and K-Nearest

64Yulianti, A., Labellapansa, A., Kadir, E., Sundaram, M. and Othman, M.Image Segmentation of Nucleus Breast Cancer using Digital Image Processing.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 64-67ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

Neighbors weighted voted (KNN-WV).

(Yulianti et al., 2014; Akbari et al., 2011) seg-mented the immunohistochemical image of estrogenreceptor to breast cancer using watershed marker.(Labellapansa et al., 2016) conducted a similar studybut using the IHC HER2 method for scores of 1+ and3+ and the classification can be done correctly 100%for scores of 3+ and 65% for scores of 1+.

This study was able to indicate the status of ER /PR and remove the stacked cell area however the con-nective tissue cell that is not a nucleus cell counts asER / PR cell as shown in Figure 2. Our research willmake image improvements by removing connectivetissue that is not a nucleus cell which hopefully willbe able to calculate the number of ER / PR cells inmore detail.

Figure 2: IHC image positive estrogen receptors

2 RESEARCH METHOD

The first step is done by acquiring positive / negativeimages of ER / PR in the lab Medicine Faculty of Ga-jah Mada University. The phases of pre processingthe imagery are done by using the median filteringmethod. The clean image of the noise, will enter thesegmentation stage to separate the blue area (negativecell ER / PR) and brown area (positive cell ER / PR)using colour deconvolution. The Color deconvolutionmethod can read the colors of each channel Red GreenBlue (RGB)(Ruifrok et al., 2001). Watershed is usedto separate the stacked cell area using color decon-volution. The next step which is the most importantcontribution in this study is to identify the connectivetissue that is not a cell. The shape feature will be usedto remove this connective tissue area. The next stepis to calculate the portion of positive cell and nega-tive cell so that can be identified whether the image ispositive ER / PR or negative. Flow Chart of ResearchActivities as shown in Figure 3.

Figure 3: Flow Chart of Research Activities


The phases of nucleus IHC breast cancer image seg-mentation are shown in Figure 4. The input image(a) is pre-processed using the median filter (b) thencolor segmentation is done using color deconvolutionso that the image of channel 1 H (c) and channel 2DAB Positive (d) The next step is to separate the ac-cumulated cells in the H image and the positive DABimage by using watershed marker segmentation. Fig-ures 4 (e) and (f) are the results of the segmentationso that it is expected that the number of cells can becalculated.

Morphological reconstruction was carried out af-ter the process in Figure 4 was completed. Mor-phological reconstruction is a morphological transfor-mation involving two images and one structural ele-ment. The first image is the start point of transfor-mation, commonly referred to as the marker and thesecond image as a constraint, commonly referred to asa mask. The process of morphological transformationis based on the concept of pixel neighbors using struc-tural elements (Gonzalez et al., 2002). Pixel neighboroperation is an image processing operation to get thevalue of a pixel that involves neighboring pixel valuesand is mostly used for form analysis (Kadir, 2017).

The use of kernels of different sizes shows differ-ences in the results of cell segmentation in connectivetissue. This study uses a kernel size of 3x3 and 1x1.

Image Segmentation of Nucleus Breast Cancer using Digital Image Processing

65

(a) (b)

(c) (d)

(e) (f)Figure 4: The Stage of IHC Nucleus Image Segmenta-tion Stage of Breast Cancer (a) Image of estrogen recep-tor (b) Image Resulted by Median filtering (c) Image H Re-sulted by colour Deconvolution (d) Image DAB Resulted byColour Deconvolution (e) Image H Resulted by Watershed(f) Image DAB Resulted by Watershed

(a) (b)Figure 5: Image of the result of using (a) 3x3 Kernel Size(b) 1x1 kernel size

Figure 5 is the result of cell segmentation in connec-tive tissue using a 3x3 and 1x1 disk kernel. It is seenthat cells in the connective tissue are still counted asmany cancer cells while using a 1x1-sized kernel seenin cells in the connective tissue there are not manycounts.

Based on the results seen in figure 5, the use of3x3 and 1x1 kernels has indeed succeeded in remov-ing cells in the connective tissue, but not all cells inthe connective tissue can be identified. This researchwill be continued by using other methods to removecells in connective tissue. If this step has been com-pleted, then the next process until cell count can bedone.

4 CONCLUSIONS

From the steps that have been done above, some re-sults are obtained, namely stages of digital image pro-cessing to read IHC breast cancer images to obtainH cell counts and positive DAB cell numbers begin-ning with the pre-processing process using MedianFiltering, then proceed with colour segmentation us-ing Colour Deconvolution to obtain IHC H imagesand positive DAB IHC images and followed by cellsegmentation using Watershed Markers. The use of3x3 and 1x1 kernels has indeed succeeded in remov-ing cells in the connective tissue, but not all cells inthe connective tissue can be identified. This researchwill be continued by using other methods to removecells in connective tissue. If this step has been com-pleted, then the next process until cell count can bedone.

ACKNOWLEDGEMENTS

High appreciation should be given to Universitas Is-lam Riau (UIR) and Universiti Teknologi Petronas(UTP) for their support in matching grant of this re-search work.

REFERENCES

Akbari, H., Uto, K., Kosugi, Y., Kojima, K., and Tanaka, N.(2011). Cancer detection using infrared hyperspectralimaging. Cancer science, 102(4):852–857.

Calhoun, M. E., Chowdhury, S., and Goldberg, I. (2019).Medical analytics system. US Patent 10,255,997.

Estrogen, S. C. I. R. Kanker payudara menggunakan markerwatershed.

Gonzalez, R. C., Woods, R. E., et al. (2002). Digital imageprocessing.

Kadir, A. (2017). Teori dan aplikasi pengolahan citra.Kostopoulos, S., Cavouras, D., Daskalakis, A., Bougioukos,

P., Georgiadis, P., Kagadis, G. C., Kalatzis, I., Rava-zoula, P., and Nikiforidis, G. (2007). Colour-texturebased image analysis method for assessing the hor-mone receptors status in breast tissue sections. In 200729th Annual International Conference of the IEEEEngineering in Medicine and Biology Society, pages4985–4988. IEEE.

Labellapansa, A., Muhimmah, I., and Indrayanti (2016).Segmentation of breast cancer cells positive 1+ and 3+immunohistochemistry. In AIP Conference Proceed-ings, volume 1718, page 110002. AIP Publishing.

Limsiroratana, S. and Boonyaphiphat, P. (2009). Computer-aided system for microscopic images: applicationto breast cancer nuclei counting. INTERNATIONALJOURNAL OF APPLIED, 2(1):69.


66

Ruifrok, A. C., Johnston, D. A., et al. (2001). Quantifi-cation of histochemical staining by color deconvolu-tion. Analytical and quantitative cytology and histol-ogy, 23(4):291–299.

Yulianti, A., Muhimmah, I., and Indrayanti, I. (2014).Segmentasi Citra Imunohistokimia Reseptor Estro-gen Kanker Payudara menggunakan Marker Water-shed. Seminar Nasional Informatika Medis (SNIMed),0(5):1–10.

Image Segmentation of Nucleus Breast Cancer using Digital Image Processing

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An Integrated Framework for Social Contribution of Diabetes Self-careManagement Application

Zul Indra, Liza Trisnawati and Luluk ElvitariaDepartement of Informatics Engineering, Abdurrab University, Pekanbaru, Indonesia

zul.indra, liza.trisnawati, [email protected]

Keywords: Diabetes Mellitus, Diabetes Self-care Management (DSCM), Web Application.

Abstract: Diabetes mellitus (DM) has becoming a critical health problem due to number of mortality. This disease willaffect the entire life of diabetic with its biological, psychological and social effects. However, there is noknown cure for this chronic disease. Diabetics can only reduce the complications that arise by taking certainmeasures such to keep the blood glucose levels as close to normal as possible. The goal to keep the bloodglucose levels as close to normal requires the involvement of diabetics by diabetes self-care management(DSCM). However, successful treatment for diabetics is not only depending on patient’s role in the care oftheir diabetes but also requires family support. This research proposes an integrated DSCM application whichis enriched of social contribution feature since the DSCM application which accommodates the involvement ofdiabetics’ family (social contribution) is still scarce. This proposed DSCM is aimed to allow family memberof diabetics to encourage them to keep their blood glucose levels as close to normal and enabling the doctorsto be actively involved in helping diabetics in managing their lifestyle.

1 INTRODUCTION

Diabetes mellitus (DM) has becoming a critical healthproblem due to number of mortality. In 2011, theInternational Diabetes Federation (IDF) claimed thatevery year 4 million people die of diabetes with an av-erage of one person dying every 7 seconds (Alrahbi,2014). It has been estimated that 382 million peoplein the world had DM, with more than 90% of them aretype 2 diabetic (Thojampa, 2019). In addition, basedon The World Health Organization report, the numberof people with diabetes has risen from 108 million to422 million in just 34 years. This number of is ex-pected to increase to about 439 million in 2030, where69% of this number is estimated to occur in develop-ing countries (Shaw et al., 2010). Therefore in 2014,the World Health Organization (WHO) declared thatdiabetes is one of most serious disease and a costlyhealth condition around the world(Association et al.,2014).

As a chronic disease, diabetics will experiencevarious complications in their daily lives. This dis-ease will affects the entire life of diabetic with itsbiological, psychological and social effects (Mankanet al., 2017). As an example, diabetics have a greaterrisk of cardiovascular disease, eye or kidney disease,and even reduced life expectancy compared to normal

people. In terms of psychological problems, suffererswill experience a loss of life pleasure because theylose the confidence to live independently and becomediscouraged in living life. Furthermore, they have tomaintain a planned care throughout their lives and re-ceive professional help from time to time.

Unfortunately, to date, there is no cure for thischronic disease. Diabetics can only reduce the com-plications that arise by taking certain measures suchto keep the blood glucose levels as close to normal aspossible (Syaifuddin and Anbananthen, 2013). Effec-tive control of diabetes depends on self- monitoringand self-care activities such as blood glucose moni-toring, appropriate diet and nutrition, exercise regi-men and medication administration strategies. Also,individuals have to keep track of their overall healthrecord a holistic approach instead of only monitoringtheir blood glucose reading.

However, the goal to keep the blood glucose lev-els as close to normal cannot be achieved without in-volvement of patients in the management plan. Thisinvolvement occurs through diabetes self-care man-agement (DSCM) with patients assuming an indepen-dent role in the care of their diabetes. In addition,successful treatment for diabetics is not only dependon patients role in the care of their diabetes but alsorequires family support a good relationship with the

68Indra, Z., Trisnawati, L. and Elvitaria, L.An Integrated Framework for Social Contribution of Diabetes Self-care Management Application.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 68-73ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

diabetes care team, including open communicationand easy access to care, is essential for success (Sil-verstein, 2014). This research proposes an integratedpersonal health record which allow family member ofdiabetics to contribute in order to keep the blood glu-cose levels of diabetics as normal as possible.

2 LITERATURE REVIEW

DSCM can be defined as implementing actual per-formance for self-care activities for those who sufferfrom diabetes to manage their condition (Gharaibehet al., 2017). The main purposes of DSCM manage-ment is to the glucose levels as close to normal aspossible by doing diet, performing physical activities,monitoring blood glucose level, using of medications,another self-care actions. The workings of DSCM isto modify health behaviour by making changes to thedaily plan, if necessary, in accordance with the treat-ment regimen and completion of self-care activitiessuch as following a regular diet and exercise plan,independent monitoring of blood glucose levels, andtaking medication according to prescription (Khairnaret al., 2019).

Nowadays, DSCM is considered a critical part ofdiabetes management and has an important role inhelping diabetics to control the glycaemic and preventcomplications (Funnell, 2009). Furthermore, severalresearch has shown that DSCM can improve the qual-ity of life of diabetics and contributed in prevent-ing and lessening the severity of complications (Loriget al., 2009).

During the last five years, there are several re-searches that have been done to develop DSCM ap-plication. In 2014, an integrated model for cognitivebehavioural therapy for DSCM was proposed (Alanziet al., 2014). This proposed DSCM was intendedto implemented cognitive behavioural therapy for di-abetics by using smartphone technology. In 2016,another work for DSCM was performed by utilizingthe digital engagement concept (Burford et al., 2016).This research attempted to empower the diabetics byinviting them to participate in various digital activi-ties for the management of their health condition. Thesecond work for DSCM research in 2016 was carriedout by developing an application which is called byDiaHealth (Islam et al., 2016).

Based on the review of these several relatedworks, it can be inferred that there are many e-healthapplications for diabetes management systems avail-able, but most of these systems only focus on glucosemeasurement levels and have not accommodated theinvolvement of diabetics’ family (social contribution).

Therefore, this research proposes an integrated per-sonal health record which is enriched of social contri-bution feature. This feature is aimed to allow familymember of diabetics to encourage them to keep theirblood glucose levels as close to normal. Furthermore,this proposed DSCM is enabling the doctors to be ac-tively involved in helping diabetics in managing theirlifestyle.

3 SYSTEM REQUIREMENT

The DSCM application that is created is a web-basedapplication because it tends to be more flexible. Web-based applications can be accessed through variousdevices and various operating systems such as viasmartphones or tablets and others including smartwatches. It doesn’t matter whether users use Win-dows, Linux, iOS, Mac OS, Blackberry, Android orother devices; users can still use it only with a webbrowser. Users simply open a web browser (for ex-ample Firefox or Google Chrome) which then pointsthat web browser to the DSCM application URL touse this DSCM application.

In addition, users can also access this applica-tion through all the devices they have without hav-ing to install it first on each of these devices. Thisof course will make it easier for users who tend tohave multiple devices at once or change devices fre-quently. As for the website interface, DSCM appli-cation uses a bootstrap framework which is known asone of the best website front-end framework. By us-ing this bootstrap framework, the DSCM applicationbecomes more responsive and can adjust its appear-ance according to the devices that access it. How-ever, to use this website-based application, users donot need hardware with strong specifications becauseall applications are placed on the server side ratherthan on the client side.

4 FEATURE OF PROPOSEDDSCM APPLICATION

Based on literature study that has been conducted, thisDSCM application is designed to have 5 main mod-ules namely personal health record, knowledge baseand extraction, intelligent suggestion, notification andreminder and social contribution.

As seen in the figure 2, the DSCM application isdivided into two levels of users, namely the level ofdiabetics and social (family members and internists)who have different access rights. Diabetic Users will

An Integrated Framework for Social Contribution of Diabetes Self-care Management Application

69

Figure 1: Module of Proposed DSCM

Figure 2: Context Diagram of Proposed DSCM

be given the right to access the blood sugar level datainput features, input insulin data, input exercise dataand obtain a profile of their health records. In additionthey will also be given a notification to remind themto routinely check (input) blood sugar level data, dietadvice and also advice on physical activity. For sociallevel user, they will be given access to the health pro-file of diabetics, get notifications from the system andprovide encouragement so that diabetics can managetheir lifestyle. Moreover by using this DSCM, it isexpected the internist can get a health picture of thepatient real time and provide better treatment.

4.1 Personal Health Record

In this proposed DSCM application, the PersonalHealth Record Module consists of two main parts,namely data input section and the health profile ofdiabetics section. There are several data which isinputted by users into personal health records suchas blood sugar levels, insulin intake, exercise activi-ties and diet activities. All these records of data willbe processed by the Knowledge Base and Extractionmodule and then delivered to diabetics in the form ofsuggestions.

Figure 3: Homescreen of Proposed DSCM

DSCM application will give suggestion to diabet-ics regarding physical activity and a better and appro-priate diet in order to maintain their blood sugar levelsas close to normal. All data that has been inputted bythe diabetic user will be displayed by this DSCM ap-plication on the health profile display page so that therelated users, diabetics and family members of the in-ternist, can monitor the patient’s health condition realtime.

Figure 4: Profile of Diabetic

Figure 5: Graph Representation for Glucose and BloodPressure Level

4.2 Knowledge Base and Extraction

This module has a task to process raw data whichare inputted by users where concepts of data min-ing and machine learning are utilized in this mod-ule. So that the presence of the Knowledge Base and


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Extraction module makes this DSCM application be-come smarter as this DSCM will adjust itself, in termsof giving advice and notifications, according to thehealth profile of each user. For example, based on theresults of the blood sugar level record the DSCM ap-plication will look at the blood sugar level trend ofdiabetics then analyse the causes of elevated or de-creased blood sugar levels.

The results of this analysis will be displayed andcan be accessed by the user in personal health recordmodule. In addition, the results of this analysis will befurther processed in the intelligent suggestion moduleto be able to provide more suitable treatments relatedto diet, physical activity and so on.

4.3 Intelligent Suggestion

As explained in the knowledge base and extractionmodule, this developed DSCM application will intel-ligently provide advice according to the health profileof each diabetic. Thus the advice which is deliveredwill be more in accordance. For example, based onthe results of the analysis that has been carried outin the knowledge base and extraction, users will getadvice about physical activity and diet control that ismore in line with their habits in order to make it easierfor them to keep their blood sugar levels normal.

Figure 6: Sample of Intelligent Suggestion

4.4 Notification and Reminder

This module is an important module in the DSCMapplication that has the task of giving reminders tousers. Patients will be reminded to record their healthdata such as their blood sugar level and regular phys-ical activity. Due to diabetics are tend to forget orlazy to record their health data because they considerthis troublesome. This module will routinely checkwhether the patient has recorded their health data. Ifdiabetics have not yet recorded the data, the DSCMapplication through this module will send notifica-tions to users in order to remind diabetics to imme-diately record their health data.

4.5 Social Contribution

As explained earlier, another factor in the success oftreating diabetics is the contribution of family mem-bers. This module is intended to be a medium for

Figure 7: Sample of Intelligent Suggestion

Figure 8: Adding of Reminder Notification

Figure 9: Reminder Data

family members and doctors to be actively involved inhelping diabetics in managing their lifestyle. Throughthis module, they can easily monitor the health condi-tions of diabetic real time and encourage them to beable to regulate their lifestyle such as reminding themto check their blood sugar levels, follow a healthydiet, and do physical activities and so on.

Figure 10: List of Social Contributor

5 CONCLUSIONS

Successful treatment for diabetics is not only dependon patients role in the care of their diabetes but alsorequires family support to encourage them to keep theblood glucose levels of diabetics as normal as possi-ble. This research proposes an integrated DSCM ap-plication which allow family member of diabetics to


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Figure 11: Form of Social Contributor Registration

encourage them to manage their lifestyle and enablingthe doctors to be actively involved in helping diabet-ics real time. This research is still in the initial stagesin terms of identifying what modules are needed inthe development of DSCM applications. Further re-search needs to be carried out to find out how muchthe influence of proposed DSCM application in orderto ease the treatment of diabetics.

Figure 12: Approval for Social Contributor

REFERENCES

Alanzi, T., Istepanian, R. S., and Philip, N. (2014). An in-tegrated model for cognitive behavioural therapy formobile diabetes self-management system. In 201436th Annual International Conference of the IEEEEngineering in Medicine and Biology Society, pages5393–5396. IEEE.

Alrahbi, H. (2014). Diabetes self-management (dsm) inomani with type-2 diabetes. International Journal ofNursing Sciences, 1(4):352–359.

Association, A. D. et al. (2014). Standards of medicalcare in diabetes—2014. Diabetes care, 37(Supple-ment 1):S14–S80.

Burford, S., Park, S., Carpenter, M., Dawda, P., and Burns,J. (2016). Digital engagement, self-management, andshifting the locus of control: A mhealth program forpeople with type 2 diabetes. In 2016 49th Hawaii In-ternational Conference on System Sciences (HICSS),pages 3369–3378. IEEE.

Funnell, M. (2009). Bro n tl, childs bp, haas lb, hose gm,jensen b, et al. National standards for dia etes self-management education. Dia etes Care.

Gharaibeh, B., Al-Smadi, A. M., and Boyle, D. (2017).Psychometric properties and characteristics of the di-abetes self management scale. International journalof nursing sciences, 4(3):252–259.

Islam, M. A., Alvi, H. N., and Al Mamun, K. A. (2016). Di-ahealth: A smart app for complete diabetes lifestylemanagement. In 2016 International Conference onMedical Engineering, Health Informatics and Tech-nology (MediTec), pages 1–6. IEEE.

Khairnar, R., Kamal, K. M., Giannetti, V., Dwibedi, N.,and McConaha, J. (2019). Barriers and facilitators todiabetes self-management in a primary care setting–patient perspectives. Research in Social and Adminis-trative Pharmacy, 15(3):279–286.

Lorig, K., Ritter, P. L., Villa, F. J., and Armas, J.(2009). Community-based peer-led diabetes self-management. The Diabetes Educator, 35(4):641–651.

Mankan, T., Erci, B., Turan, G. B., and Akturk, U. (2017).Turkish validity and reliability of the diabetes self-efficacy scale. International journal of nursing sci-ences, 4(3):239–243.


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Shaw, J. E., Sicree, R. A., and Zimmet, P. Z. (2010).Global estimates of the prevalence of diabetes for2010 and 2030. Diabetes research and clinical prac-tice, 87(1):4–14.

Silverstein, J. H. (2014). Can we reduce barriers to diabetescare? The Journal of pediatrics, 164(6):1245–1247.

Syaifuddin, M. and Anbananthen, K. S. M. (2013). Frame-work: Diabetes management system. In IMPACT-2013, pages 112–116. IEEE.

Thojampa, S. (2019). Knowledge and self-care manage-ment of the uncontrolled diabetes patients. Interna-tional Journal of Africa Nursing Sciences, 10:1–5.


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Spatiotemporal Analysis of Urban Land Cover:Case Study - Pekanbaru City, Indonesia

Idham Nugraha1, Faizan Dalilla1, Mira Hafizhah Tanjung1, Rizky Ardiansyah2, and M. Iqbal Hisyam2

1Urban and Regional Planning Departement, Universitas Islam Riau, Pekanbaru, Indonesia2Student in Urban and Regional Planning Departement, Universitas Islam Riau, Pekanbaru, Indonesia

idham.nugraha, dalillafaizan, [email protected], [email protected], [email protected]

Keywords: Land Cover, Remote Sensing, Spatiotemporal, Pekanbaru.

Abstract: The number of people has an increasing pattern by years and it will impact spatial aspects. One of the impactswas land cover changes from the non-built area into the built-up area. Pekanbaru is one of developing cityin Indonesia that has a high number of the population surge. The purpose of this paper was to analyse theland cover change in the urban area of Pekanbaru city. The analysis spatiotemporal has been done by usingLandsat Imagery year of 2000, 2005, 2009 and 2014. The method of this paper was digital classificationusing maximum likelihood and their integration with Geographical Information Systems (GIS). Land coverclassification divided into two classes such as built-up area and non-built up land area. Based on the results,the built-up land area has been increased by years, on the other hand, the non-built up area has declined. Thepercentage of built-up area change from 29,51% into 59,99%. The spatial distribution of and cover changedominantly occurs in south part of Pekanbaru city. The mean of accuracy index for the land cover map in thisresearch was 85,17%. The land cover change of Pekanbaru city has a decreasing pattern where the year of2000-2005 has a significant number and decreasing by years massively.

1 INTRODUCTION

Globally, the number of populations has an increasingpattern. Based on the report of Worldmeters (Wor,2020), the rate of increasing population was 1,09%by years. Specifically, Indonesia has the number ofpopulation amount of 267.630.499. Indonesia cate-gorized as a country that has high urbanization indexin Asia around 2,75% by years and it’s above the na-tional index around 1,49% per year (Indrayani et al.,2017).

The increasing population will have some con-sequences. In the spatial aspect, the dimension ofspace has been pushed out by the increasing popu-lation. Yunus (Yunus, 2005) explained that spatialconsequences were increasing demand for space toaccommodate the population activities in the formof infrastructure and other physical structure. Thatwill be seen the massive of land cover change fromthe non-built area into the built-up area. Land coverchanges can be categorized by the complex interac-tions of structural and behavioural factors associatedwith technological capacity, demand and social rela-tions that affect both environmental capacity and thedemand along with the nature of the environment of

interest (Veldkamp and Verburg, 2004) (Butt et al.,2015). Land cover change is one of the main driv-ing forces of global environmental change, is cen-tral to the sustainable development debate (Hegazyand Kaloop, 2015). Land cover change becomes oneof the significant issues for planners and decision-makers in urban and regional policy (Wijaya andSusilo, 2013). In line with the issue of increasingpopulation, land cover change become an interestingissue to explore in a developing country, especially inIndonesia. Wijaya (Wijaya and Susilo, 2013) high-light that issue has been thriving because of the lack-ing of law enforcement and the policy inter-institutionhorizontally and vertically. The study of land coverchange is very essential to understand human activi-ties and natural phenomenon.

The study of land cover change has been devel-oped with different methods and cases (Purwanto andBayuardi, 2016). One of the methods to determinethat is the integration of remote sensing data and Ge-ographic Information Systems (GIS). For example, inChina the land cover change was obtained by usingthe integrated remote sensing data and GIS at yearsof 1992, 1996, 2001, 2004 and 2008 (Purwanto andBayuardi, 2016). In Indonesia, several studies have

74Nugraha, I., Dalilla, F., Tanjung, M., Ardiansyah, R. and Hisyam, M.Spatiotemporal Analysis of Urban Land Cover: Case Study - Pekanbaru City, Indonesia.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 74-79ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

been done, one of them was Indrayani et al (2016). Ithas been done to evaluate land cover change and itsrelations with the ecological connectivity index us-ing remote sensing data year of 1997 until 2012 inMakasar city.

The technology advance, especially on remotesensing and GIS, gives some benefit to obtain someinformation about earth surface such as land cover.One of them is remote sensing data can give quick in-formation and multi-series data (NUGRAHA, 2016).GIS advance can be used for measurement, mapping,monitoring and modelling (Star and Estes, 1990). Toease the used remote sensing data and GIS in landcover studies, it can be done by making land coverclassification (NUGRAHA, 2016).

Pekanbaru is a central city in Riau Province andcategorized as a developing city in Indonesia. Pekan-bary city connects the north-south littoral of Sumat-era, and it also connects the East and West of thisisland (Kausarian et al., 2018). Pekanbaru consistsof twelve (12) districts, there area Bukit Raya, LimaPuluh, Marpoyan Damai, Payung Sekaki, PekanbaruKota, Rumbai, Rumbai Pesisir, Sail, Senapelan, Suka-jadi, Tampan and Tenayan Raya (figure 1). Basedon Statistical data (Pekanbaru, 2016), Pekanbaru hastotal populations amount 1.038.118 in the year of2015. For the comparison, In 2000 Pekanbaru hasthe number of populations around 586.223. In 15years, Pekanbaru has 451.895 of people accretion andit will affect the spatial condition in Pekanbaru city.The research purpose was to review the land cover ofPekanbaru city year of 2000, 2005, 2009 and 2014by using Landsat imagery and digital classification.To achieved purposed, some step will be done. Therewere :

a) Determine the land cover of Pekanbaru city

b) Determine the accuracy of the land cover

map

c) Determine the land cover change of Pekanbaru

city

2 METHOD

To achieve the purpose of the research, some pri-mary and secondary data were needed. The data wereLandsat imagery, Rupabumi Indonesia Map (BaseMap), The draft of Spatial Regulation Document ofPekanbaru year of 2006. For further information, therequired data were:

Figure 1: Administrative map of Pekanbaru

Table 1: The Data Requirements

No Data Sources1 Landsat ETM+ year of

2000, 2005 and 2009.Landsat 8 year of 2014

USGS

2 Rupabumi Indonesia Related Institutions3 The draft of Spatial Regula-

tion Document of Pekanbaruyear of 2006

Related Institutions

4 The form of Land CoverChange

Field Observation

2.1 Determine The Land Cover ofPekanbaru City

To determine the land cover of Pekanbaru city,we used the classification of maximum likelihoodmethod by using ENVI 4.5. The maximum likeli-hood is categorized as supervised classification. Thismethod is classified as the pixel based on their valueto the particular class. Technically, the sample wascollected from Landsat imagery that has spatial reso-lution 30 m by selecting the Region of Interest (ROI).The land cover present into two classes, there werebuilt up area and non-built up area.

2.2 Determine the Accuracy of TheLand Cover Map

The accuracy assessment was needed to determine thecorrectness of the land cover map. The method is theKappa index assessment. This method is comparedto the land cover map with the actual condition on thefield. For the sample, we used 60 points that randomlydistributed. The minimum index that allowed is 85%(Jensen et al., 2004). The matrix of the accuracy indexis explained below.

T he total accuracy =a+d

T(1)

Spatiotemporal Analysis of Urban Land Cover: Case Study - Pekanbaru City, Indonesia

75

Table 2: The Matrix of Accuracy Index

Field InterpretationA1 A2 Total

A1 a b a+bA2 c d c+d

Total a+c b+d TSource: (Sutanto and Leung, 1999) with modification

2.3 Determine The Land Cover Changeof Pekanbaru City

The land cover change was obtained by overlaid theland cover map. This stage has been done to deter-mine the spatial distribution of the change by usingArcGIS. This method was using the raster calculator.For further analysis, field observation is needed. Theland cover change information will be guided to thefield observation. This step will be done to obtaininformation about the form of land cover change inPekanbaru city.


3.1 The Land Cover of Pekanbaru City

For this stage, we used the application of ENVI 4.5.From the Landsat images, we generated two classesof Region of Interest (ROI). There were built-up areaand non-built up area. There were 100 samples foreach class. Here below the figure 3, shows the landcover of Pekanbaru city 2000-2014.

Based on figure 2, we can see that the land coverof Pekanbaru city dominantly by the built-up areashown by the red mark on the map. Generally, thebuilt-up area in Pekanbaru has been developing. In2000, the built-up area amount of 208.712 pixels oraround 29,51% from the total of land cover in Pekan-baru City. For the comparisons, in the year of 2014,built up area was increasing. It is shown by the num-ber of pixels of the built-up area around 424.362 pix-els (59,99%). For the distribution, the built-up areadistributed randomly in Pekanbaru especially in thesouth part of Pekanbaru. It was because in the southpart of Pekanbaru found some of the developmentcentres as a triggered factor such as the centre of ed-ucation, the centre of government and centre of trad-ing. For the further, the pixel number of land cover inPekanbaru shown on the table below.

(a)

(b)

(c)

(d)Figure 2: The Land Cover Map of Pekanbaru City; (a) yearof 2000, (b) year of 2005, (c) year of 2009, (d) year of 2014


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Table 3: The Pixel Number of Land Cover in PekanbaruCity

Year Built UpArea

Non Built-Up Area

Lake River

2000 208712 491813 5377 14512005 349080 351445 5377 14512009 402534 297991 5377 14512014 424362 276163 5377 1451

3.2 The Accuracy of Land Cover Map

First step of this stage was determined the trainingarea or point as a sample. The number of sampleswere 60 points that randomly spread around Pekan-baru city. The mean of accuracy from Landsat imagewas 85.17%. For the detail information about the ac-curacy shown on table below.

Table 4: The Accuracy of Land Cover Map

Year Accuracy2000 84.22005 85.52009 85.02014 86.0Mean 85.17

3.3 The Land Cover Change ofPekanbaru City

The information about the land cover change in thispaper was obtained from the land cover map that ex-tracted from the Landsat image. The thematic mapwill be overlaid by using Raster Calculator tool onArcGIS application. The unit analysis for the landcover change is a pixel. We used the pixel to describedthe change value. The land cover change in Pekan-baru city occurred in the form of the non-built up arealike vegetation, swamp area transforms into the built-up area such as settlement, trading and service. Thesignificant change occurred in 2000 until 2005. Itis shown on the map, that change has been noticedby the red mark and been seen on the south part ofPekanbaru significantly. Meanwhile, the change be-tween 2005-2009 and 2009-2014 has a small portionand distribute more equal to the north part of Pekan-baru city. Figure 3 shows the land cover change inPekanbaru city 2000-2015.

Based on the analysis, the land cover change inPekanbaru city has decreases pattern. From 2000 un-til 2005 the land cover has been massively changedfrom the non-built area into the built-up area. From

(a)

(b)

(c)Figure 3: The Land Cover Change Map of Pekanbaru City;(a) year of 2000-2005, (b) year of 2005-2009, (c) year of2009-2014

the total pixel around 707.503 pixels, the land coverchange reaches 140.368 pixels (19,84%). From 2005-2014, the change has declined pattern, it looked fromthe percentage. The percentage of change 2005-2009amount of 53.454 pixel (7,5%) and 2009-2014 around21.828 pixels (3,0%). For the detail information, thepattern of land cover changes Pekanbaru city presentin figure 4 below.

The next stage of the paper is the land cover anal-ysis. We analyze the land cover change by using dis-trict administration as a unit and classified it into twoclasses (change and no change). We used the draftof Spatial Regulation Document of Pekanbaru Cityas other input. Pekanbaru city consists of 12 dis-tricts with each district has different size and num-ber of populations. Based on the analysis, we found


77

Table 5: The Number of Land Cover Change in Pekanbaru City 2000-2014 (pixel)

Districts 2000-2005 2005-2009 2009-2014Change No Change Change No Change Change No Change

Tampan 30118 34024 2150 61992 1394 62748MarpoyanDamai

7404 26881 1252 33033 995 33290

Bukit Raya 7437 20391 1925 25903 652 27176Sail 250 3622 ∗ 3872 ∗ 3872Lima Puluh 346 6020 ∗ 6366 ∗ 6366PekanbaruKota

36 2316 ∗ 2352 ∗ 2352

Sukajadi 17 4258 ∗ 4275 ∗ 4275Senapelan 81 3302 ∗ 3383 ∗ 3383PayungSekaki

9240 38352 1960 45632 2290 45302

Rumbai 20101 125565 18327 127339 7627 138039Rumbai Pe-sisir

8289 165976 13398 160867 4956 169309

TenayanRaya

57049 136278 14442 178885 3914 189413

Total 140368 566985 53454 653899 21828 685525

Figure 4: The Pattern of Land Cover Change in PekanbaruCity 2000-2014

that there were five districts has “no change” classfrom 2005 until 2014. It could occur because theylocated in the city centre with the least number ofthe non- built up area were available. Commonly,the other districts in Pekanbaru city have a decreasingpattern. For example, Tampan district and TenayanRaya district has the high number of change during2000- 2005, but decreasing in a heavy way by years.It showed that during 2009-2014 there were approxi-mately 1000-4000 pixel has been changed.

In over decades, Pekanbaru hit by land coverchange phenomenon as consequences of urban expan-sions. The increasing of populations due to fertilityand migrations will impact the land cover conditionsin Pekanbaru city. During 2000-2014, the land coverchange in Pekanbaru city has a decreasing pattern.The main reason was the limited access to the land

due to availability and land value. Based on the re-search, people have the tendency to develop the landaround the edge of the city. So for the future, theresearch related land cover change in the sub-urbanarea of Pekanbaru city. Regarding the remote sens-ing data, in this research, we used Landsat imageryas the main input. It has the spatial resolution around30 m. For future research, the used high resolution ofremote sensing data is needed.

4 CONCLUSIONS

For this paper, we can conclude some points therewere: 1) The land cover in Pekanbaru city was domi-nantly by the built-up area. It shows by the percentageof built-up area in 2014 was 59,99% from the total ofPekanbaru city, 2) The accuracy of the land cover mapmeasured by using the short method. The mean indexof the accuracy was 85,17%, and 3) the land coverchange from the non-built up area into the built-uparea has the decreasing pattern. It’s related to landavailability and land value.

ACKNOWLEDGEMENTS

This paper is part of the research with the title “Mon-itoring Perubahan Penutup Lahan Kota PekanbaruMenggunakan Citra Satelit Landsat” by Idham Nu-graha and Faizan Dalilla. This research was funded


78

and fully support by LPPM of Universitas Islam Riau.We thank all colleagues that involved in this research.

REFERENCES

(2020). Worldometers - real time world statistics.Butt, A., Shabbir, R., Ahmad, S. S., and Aziz, N. (2015).

Land use change mapping and analysis using remotesensing and gis: A case study of simly watershed, is-lamabad, pakistan. The Egyptian Journal of RemoteSensing and Space Science, 18(2):251–259.

Hegazy, I. R. and Kaloop, M. R. (2015). Monitoring ur-ban growth and land use change detection with gis andremote sensing techniques in daqahlia governorateegypt. International Journal of Sustainable Built En-vironment, 4(1):117–124.

Indrayani, P., Mitani, Y., Djamaluddin, I., and Ikemi, H.(2017). A gis based evaluation of land use changesand ecological connectivity index. Journal of Geo-matics and Planning, 4(1):9–18.

Jensen, R., Gatrell, J., Boulton, J., and Harper, B. (2004).Using remote sensing and geographic informationsystems to study urban quality of life and urban for-est amenities. Ecology and Society, 9(5).

Kausarian, H., Sumantyo, J. T. S., Putra, D. B. E., Suryadi,A., et al. (2018). Image processing of alos palsarsatellite data, small unmanned aerial vehicle (uav),and field measurement of land deformation. Interna-tional Journal of Advances in Intelligent Informatics,4(2):132–141.

NUGRAHA, I. (2016). Pemodelan Spasial PerubahanPenutup Lahan Dalam Rangka Estimasi Debit Pun-cak di Sub DAS Sail. PhD thesis, Universitas GadjahMada.

Pekanbaru, B. P. S. (2016). Kota pekanbaru dalam angka2016. Badan Pusat Statistik Kota Pekanbaru. Pekan-baru.

Purwanto, A. and Bayuardi, G. (2016). Monitoring theland use change in campus 2 stkip pgri pontianak.Geoplanning: Journal of Geomatics and Planning,3(1):77–86.

Star, J. and Estes, J. E. (1990). Geographic informationsystems: an introduction, volume 303. Prentice HallEnglewood Cliffs, NJ.

Sutanto, D. and Leung, C. H. (1999). Automatic index ex-pansion for concept-based image query. In Interna-tional Conference on Advances in Visual InformationSystems, pages 399–408. Springer.

Veldkamp, A. and Verburg, P. H. (2004). Modelling landuse change and environmental impact.

Wijaya, M. S. and Susilo, B. (2013). Integrasi modelspasial cellular automata dan regresi logistik biner un-tuk pemodelan dinamika perkembangan lahan terban-gun (studi kasus kota salatiga). Jurnal Bumi Indone-sia, 2(1).

Yunus, H. S. (2005). Manajemen kota: perspektif spasial.Pustaka Pelajar.


79

The Effectiveness of Rice Husk Biochar Application to MetsulfuronMethyl Persistence

Subhan Arridho, Saripah Ulpah and Tengku Edy SabliDepartment of Agrotechnology, Universitas Islam Riau, Pekanbaru, Indonesia

[email protected], ulpahsaripah,[email protected]

Keywords: Herbicide, Metsulfuron Methyl, Persistence, Leaching, Rice Husk Biochar.

Abstract: Metsulfuron methyl is an herbicide which has low toxicity and rapidly degraded in the soil, however DuPontstated that it is very poisonous to aquatic organism. Rice husk biochar is commonly used as ameliorants,moreoverit has ability to absorb and degradeharmful chemicals. This study aimed at investigating theeffectiveness of rice husk biochar application towards the persistence of metsulfuronmethyl in soil and seepagewater. This study applied completely randomized design factorial with two levels of herbicide dose (0 and 300gr/ha) and four levels of percentage of rice husk biochar(0%, 5%, 10% and 15% of total soil). The results ofthis research revealed that there was no metsulfuron methyl residue in soil of all treatments after 28 days ofherbicide treatment. The residue was found in seepageas much as 7.7 µg/L in treatment of 0% husk biocharand 6.8 µg/L in treatment of 5%husk biochar. The seepage reduced by the increasing of the percentage of ricehusk biochar application. Thus, it can be concluded that giving the rice husk biochar is effective for absorbingmetsulfuron methyl and preventing it from leaching. However, itcould not hold the presence of metsulfuronmethyl longer in soil.

1 INTRODUCTION

Metsulfuron methyl is an herbicide active substancewhich has low toxicity (LD50 in mice > 5000 mg/kg), a low recommended dosage, and is also rapidlydegraded in the soil. Devlin et al. (1992) reportedthatmetsulfuron methyl, known as Ally, containsDT50 for 2-4 weeks. However, in the DuPont SafetyData Sheet, it is explained that Ally 20 WG(20%metsulfuron methyl) is very poisonous to aquaticorganisms; it can cause long-term adverse effects inthe aquatic environment.

Persistence is the ability of the herbicide toremain on the ground in an active state. The longerthe persistence of herbicides in the soil, the morebeneficial it will be, in terms of efficacy. However,from an ecological perspective which is relatedto environmental quality, the too-long persistenceof herbicides is certainly undesirable and shouldbe avoided because it will pollute the surroundingenvironment. The persistence of herbicides inthe soil is influenced by several factors including:volatilization, photodecomposition, adsorption,leaching, microbial decomposition, chemicaldecomposition, and uptake by plants (Rao, 2000).Meanwhile, Jansar and Sahid (2016) stated that the

level of metsulfuronmethyl residue in the river nearoil palm plantations significantly increased duringthe rainy season because of leaching.

Rice husk biochar is commonly used asameliorants in agricultural cultivation to improvesoil quality by improving the physical, chemical andbiological properties of the soil. In addition, ricehusk biochar is also known to have the ability toabsorb agricultural chemicals and it is decomposedin physically, chemically and biologically intocompounds that are not harmful for the environment.Jing et al. (2018) assert that giving rice huskbiochar could reduce the loss of ethyl phenoxapropherbicides in the soil, and decreased the toxic effectsto earthworms. Moreover, Sudirja et al. (2015) statedthat the adsorption of paraquat herbicides by soilincreases in line with the increasing doses of zeolite,straw, and activated charcoal in the soil.

This research was conducted to investigate theeffectiveness of giving rice husk biochar amelioranttowards the persistence of metsulfuron methyl in soiland seepage water.

80Arridho, S., Ulpah, S. and Sabli, T.The Effectiveness of Rice Husk Biochar Application to Metsulfuron Methyl Persistence.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 80-84ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

2 MATERIAL AND METHODS

2.1 Materials

The The materials applied in this research include:Ally 20 WG herbicide, top soil, rice husk biochar,98% purified metsulfuron methyl solution (brand:Sigma Aldrich), methanol gred HPLC, acetonitrile,acetic acid, KH2PO4, NaHCO3, HCl, and distilledwater.

The tools include: plastic pots,Krisbow-semiautomatic handsprayers, scales,Agilent 1220 Infinity LC HPLC-VWD,OpenlabChemstation Software, Gyrozencentrifugation machines, hot plate stirrersThermolyne, orbital shaker Protech, Sartoriusanalytic scales, Sartorius pH meters, ultrasonicmachines, Biotage ISL Isolate Env+ Solid PhaseExtraction (SPE) cartridge, manifold vacuum,vacuum pump, syringe, 0.2 micron syringe filter,analysis vial bottle, beaker glass, volumetric flask,centrifuge tube, flask, measuring tube, glass bottle 20ml, and micropipette.

2.2 Research Site and Methodology

This research was conducted in the green house ofthe experimental garden at the Faculty of Agriculture,Universitas Islam Riau. The extraction and residualanalysis of the active substance of metsulfuron methylherbicide was executed in the pesticide analysislaboratory of the Faculty of Science and Technology,UniversitiKebangsaan Malaysia. The research wasconducted from April to June 2018. This researchapplied a completely randomized design (CRD)factorial pattern with two levels of herbicide dose (0and 300 gr/ha) and four levels of percentage of ricehusk biochar ameliorant (0%, 5%, 10% and 15% oftotal soil). The total amount of soil and rice huskbiochar in the pot is 2 kg, which was mixed evenly(Figure 1). The treatment was repeated 3 times, sothat there were 24 units of the total experimentaltreatments.

Herbicide was sprayed onto the ground with aconcentration of herbicide application 0.67 gr/L ofwater and a spray volume of 450 l/ha. Each potwas watered with 200 ml of water after 17 days ofherbicide application daily. The water that seeped outunder the pot was collected to be analyzed.

2.3 Sampling

The soil with the same treatment was composited,stirred evenly, aerated for 2 hours then taken as much

Figure 1: Mixture of soil and rice husk biochar.

as 500 grams per treatment. Meanwhile, seeped outwater from pots that have been collected each daywas taken as the sample for as much as ± 250 ml pertreatment and it was put in a glass bottle.

2.4 Metsulfuron Methyl Extraction

For the extraction of metsulfuron methyl in the soil,5 grams of soil sample were prepared, then mixedwith 0.1 M NaHCO3. The samples were shaken withorbital shaker (200 rpm, 2 hours). After that, theywere centrifuged for 20 minutes at 4000 rpm. TheSPE cartridge was rinsed with 3 ml of acetonitrileand 3 ml of distilled water. The supernatant resultedwas flowed about 2-3 ml per minute through theSPE cartridge (Figure 2). Then, metsulfuron methylabsorbed in the SPE cartridge was separated withmethanol and stored in a 20 ml glass bottle. Theextraction results were dried to a range of 1 ml. Afterthat, it was sucked with a syringe equipped with a 0.2micron filter, then transferred to a 1.5 ml analysis vialbottle.

Figure 2: Soil supernatant was flowed through SPEcartridge for absorbingmetsulfuron methyl.

For the extraction of metsulfuron methyl inseepage, 250 ml of seepage water samples wereprepared in a glass bottle. The pH of the water samplewas adjusted between 5-6 with potassium hydroxideand or hydrochloric acid. The cartridge was rinsed

The Effectiveness of Rice Husk Biochar Application to Metsulfuron Methyl Persistence

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with 3 ml of acetonitrile and 3 ml of distilled water.Then, the water sample was flowed about 2-3 mlper minute through the SPE cartridge. Next, themetsulfuron methyl that was absorbed in the SPEcartridge was separated with methanol and stored ina 20 ml glass bottle. The extraction results weredried to a range of 1 ml. After that, it was suckedwith a syringe equipped with a 0.2 micron filter, thentransferred to a 1.5 ml analysis vial bottle.

2.5 Metsulfuron Methyl Analysis

To provide a standard metsulfuron methyl primarysolution, 1.02 mg metsulfuron methyl (98% purity)was weighed and dissolved with 50 ml of methanolgred HPLC to produce a solution with a concentrationof 20 mg/L. Then, it was diluted so that theconcentration became 10 mg/L.

Next, to produce a standard metsulfuron methylcurve, 5 series of secondary solutions wereformulated with concentrations of 50 µg/L, 100µg/L, 200 µg/L, 300 µg/L and 500 µg/L respectively.A secondary solution was formulated by dissolvingthe primary solution as much as 0.05 ml, 0.1 ml,0.2 ml, 0.3 ml, and 0.5 ml with methanol gredHPLC until the solution volume became 10 ml in avolumetric flask. All the solutions made were placedin an ultrasonic device for 20 minutes and theninjected into a 1.5 ml vial analysis bottle by filteringit using 0.2 micron filters to be analyzed using HPLC.

Furthermore, the standard solution of metsulfuronmethyl, methanol, soil samples and water samplesstored in 1.5 ml vial bottle was inserted into theAgilent 1220 Infinity LC HPLC. Samples of each vialbottle were automatically analyzed for 18 minutes andthe results of the analysis were displayed through theOpenlabChemstation interface on a computer screen.


3.1 Calibration Curve

The highest correlation was obtained from acombination of 3 series of metsulfuronmethylstandard solutions, namely 100 g/L, 200 µg/L, and300 µg/L, which had a correlation coefficient of0.995. This implies that the concentration of standardsolutions gives an effect of 99% on the responseof the instrument, while the rest is influenced byother variables.The above curve also shows thatmetsulfuron methyl can be detected in the range ofRT (retention time) 5,391 minutes (Figure 3).

Figure 3: Linear regression curve of standard metsulfuronmethyl solution.

3.2 The Persistence of MetsulfuronMethyl in Soil

Table 1 demonstrates that the metsulfuron methylresidue was not found on the soil during HPLCanalysis. The ameliorant treatment of rice huskbiocharrevealed the same effect as the one without thetreatment of husk biochar after 28 days of herbicideapplication. In other words, this research found thatrice husk biochar could not maintain the persistenceof metsulfuron methyl longer in the soil.

Table 1: Level of metsulfuron methyl residues in soiln

TreatmentMetsulfuron MethylRetTime(minute)

Area(mAU*s)

ResidualLevel(µg/L)

0% huskbiochar

5.391 0 0

5% huskbiochar

5.391 0 0

10%huskbiochar

5.391 0 0

15%huskbiochar

5.391 0 0

One of the important processes that control thebehavior of herbicides in the soil is the adsorptioncarried out by the soil components. Herbicides canbe found in soil in the form of dissolved moleculesof the liquid phase and/or molecules that are boundto soil phases such as minerals, organic matter, plantresidues, etc. (Zanini et al., 2008). In addition,more than 36.3% to 55.7% of the applied metsulfuronmethyl turns into a residual form that binds to the soil(Pons and Baniuso, 1998; Xu et al., 2002; Wang etal., 2002). However, how the mechanism of colloidalsoil holds metsulfuron methyl and its metabolites isstill not clearly confirmed. Possible bonds betweenherbicides and colloidal soils include: (1) ionic bonds,


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(2) hydrogen bonds, (3) van der waals forces, (4)ligand exchanges, (5) charge transfer complexes, (6)hydrophobic partitioning, (7) covalent bonds and (8)sequestration (Gevao et al., 2000).

Based on the results of this research, thedegradation of metsulfuron methyl herbicide in thesoil is resulted from through several degradationprocesses, namely: hydrolysis, photolysis andmicrobial decomposition. However, the authorsassume that the degradation of metsulfuron methylwas more influenced by chemical degradation(hydrolysis) than by biochemistry (microorganisms)or physics (photolysis). This is in accordance withDevlin et. al. (1992) who reported that thedegradation of sulfonylurea herbicides, such as AllyClassic and Glean, is mostly caused by hydrolysis.It is supported by a research conducted by Manna(2015), which reported that the main mechanism ofchemical degradation of sulfonylurea herbicides iscaused by hydrolysis.

3.3 The Levels of Methyl MetsulfuronResidue in Seepage

Based on the results of HPLC analysis, it was foundthat the residual level of metsulfuron methyl inseepage was 7.7 µg/L in the treatment of 0% huskbiochar and 6.8 µg/L in the treatment of 5% huskbiochar. Whereas, there was no metsulfuron methylresidue was found in seepage at 10% husk biocharand 15% husk biochar(table 2). This shows that thelevel of residual metsulfuron methyl in seepage watertends to decrease with the increasing amount of ricehusk biochar applied.

Table 2: Level of metsulfuron methyl residues in seepagewater

TreatmentMetsulfuron MethylRetTime(minute)

Area(mAU*s)

ResidualLevel(µg/L)

0% huskbiochar

5.365 1745.06 7.68

5% huskbiochar

5.357 1533.71 6.75

10%huskbiochar

5.391 0 0

15%huskbiochar

5.391 0 0

The authors believe that this tendency occureddue to the adsorption by rice husk biochar applied

in the soil, preventingmetsulfuron methyl from beingleached. Hence, it can be concluded that the additionof rice husk biochar in this research is very effectiveto prevent metsulfuron methyl from leaching. As aresult, it can reduce the negative impacts that arise inthe water ecosystem around it.

This research finding is in accordance with thatof by Zhelezova et al. (2017) who reported thatadding wood charcoal to sandy and clay soils causethe adsorption of diuron herbicides increased. Theincreasing of diuron adsorption in line with theaddition of charcoal, because charcoal has manyabsorbent surfaces that can bind non-polar herbicidesso it can reduce the risk of leaching. Jing et al. (2018)investigated that the addition of rice husk biocharcould slow the loss of ethyl phenoxaprop herbicidein the soil.

The prevention of metsulfuron methyl leachingcan certainly be used as a solution to preventthe contamination of active substance of herbicidesreaching to underground water and other waterecosystems such as rivers and lakes.

A very low residual level of metsulfuronmethyl does not mean have no negative impacton the environment. Fairchild (1995) reportedthat metsulfuron methyl could cause the reductionof 50% of the number of Lemna minor leavesin a period of 14 days with an EC50 0.4µg/L. If it accumulates continuously over a longperiod of time, it is not impossible that otheraquatic organisms can be affected, including:algae (Selenastrumcapricornutum, EbC50 3.9 mg/L),crustaceans (Daphnia magna, EC50> 150 mg/L), andfish (Bluegill sunfish, LC50> 150 mg/L).

4 CONCLUSIONS

Metsulfuron methyl was completely degraded 28 daysafter herbicide application regardless the applicationof rice huskbiochar, which is assumed to be causedby hydrolysis as the main factor.

The residual metsulfuron methyl was found inseepage water in the treatment of 0% husk biocharasmuch as 7.7 µg/L and in the treatment of 5% huskbiochar as much as 6.8 µg/L, while the treatment of10% and 15% husk biochar was 0 µg/L. This indicatesthat the addition of rice husk charcoal ameliorantis very effective in absorbing and breaking downmetsulfuron methyl in the soil, so that the furthercontamination of herbicide metsulfuron methyl intothe surrounding water environment can be avoided.

The Effectiveness of Rice Husk Biochar Application to Metsulfuron Methyl Persistence

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ACKNOWLEDGMENTS

The authors wish to thank Universitas Islam Riaufor funding this publication and Centre for EarthSciences and Environment, Faculty of Science andTechnology, Universiti Kebangsaan Malaysia forproviding technical guidance and research fasilities.

REFERENCES

Devlin, D. L., Peterson, D. E., and Regehr, D. L. 1992.Residual Herbicides, Degradation and RecroppingInterval.

Fairchild, J. F., Ruessier, D. S., Lovely, P. A., Whites,D. A., and Heine, P. R. 1995. An AquaticPlant Risk Assessment of Sixteen Herbicides UsingToxicity Tests with Selenastrumcapricornutum andLemna minor.

Gevao, B., Semple, K. T., and Jones, K. C. 2000. BoundPesticide Residue in Soils: A review. EnvironmentalPollution, 108:3–14.

Jansar, K. M. and Sahid, I. B. (20). 2016. ResidueDetermination and Monitoring of The Levels ofMetsulfuron Methyl in Selected Rivers at TasikChiniPahang Malaysia. Malaysian Journal of AnalyticalSciences 20.

Jing, X., Wang, T., Yang, J., Wang, Y., and Xu, H.2018. Effect of Biochar on The Fate and Toxicity ofHerbicide Fenoxaprop-Ethyl in Soil. R. Soc. Open Sci,5:171875.

Pons, N. and Baniuso, E. 1998. Fate of metsulfuron-methylin soils in relation to pedo-climatic conditions. Pestic.Sci, 53:311–323.

PT. (20). DuPont Agricultural Products Indonesia. LembarData Keselamatan Ally 20 WDG.

Rao, V. S. (2000). Principle of Weed Science 2nd Eds.Science Publisher, Inc.

S., M. (2015). Effect of Biochar Amendments on Fate ofPyrazosulfuron-Ethyl in Soil.

Sudirja, R., Arifin, M., and Joy, B. 2015.AdsorpsiParaquatdanSifat Tanah padaTigaSubgrupTanah AkibatPemberianAmelioran.JurnalAgrikultura, 26.

Wang, H. Z., Xu, J. M., Xie, Z. M., and Ye, Q. F. 2002.Dynamics of bound residues of metsulfuron-methyl insoil humus. Acta Sci. Curcum. 22, 22.

Xu, J. M., Wang, H. Z., Xie, Z. M., and Chen, Z. L. 2002.Distribution of bound residues of metsulfuron-methylin soil combined humus. China Environ. Sci. 22, 22.

Zanini, G. P., Maneiro, C., Waiman, C., Galantini, J. A., andRosell, R. A. 2009. Adsorption of Metsulfuron Methylon Soils under No-Till System in Semiarid PampeanRegion, Argentina. Geoderma, 149:110–115.

Zhelezova, A., Cederlund, H., and Stenstrom, J. 2017.Effect of Biochar Amendment and Ageing onAdsorption and Degradation of Two Herbicides.Water Air Soil Pollut, 228:216.


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Digital Forensics: Acquisition and Analysis on CCTV Digital Evidenceusing Static Forensic Method based on ISO /IEC 27037:2014

Rizdqi Akbar Ramadhan1, Desti Mualfah2 and Dedy Hariyadi31Department of Informatics, Universitas Islam Riau, Pekanbaru, Indonesia

2Department of Computer Science, Universitas Muhammadiyah Riau, Pekanbaru, Indonesia3Jenderal Achmad Yani University of Yogyakarta


Keywords: Digital, Evidence, Forensic, Law, Acquisition, Multimedia.

Abstract: Conventional crime has existed since the beginning of human civilization where evidence and artifacts can beused as assumptions to prove crime. Every criminal who is proven to have committed a certain crime will beconvicted in accordance with the stipulated law. In this paper, there is a conventional crime case that can beproven to be a crime with digital technology, namely CCTV. Digital evidence obtained from CCTV footagecan be used as an assumption of the extent of crimes committed by criminals. Unfortunately, the quality of therecording is not easy to analyze due to the lack of resolution of the video recording and the lack of lightingin certain conditions. The analysis that will be carried out in this case uses visual manipulation tools calledAdobe Lightroom and other supporting tools. Digital forensic implementation and digital evidence handlingprocedures are used to handle this case using the forensic static method.

1 INTRODUCTION

Forensic digital science began to show its contribu-tion in today’s digital era. In contrast to other foren-sic sciences which are mostly related to dissecting andsearching for artifacts in living things, digital forensicis the practice of dissecting digital devices to look forfacts needed for legal purposes. In this case, the foren-sic static method is used in handling evidence in theform of CCTV (Closed Circuit Television). In han-dling this digital evidence there is an essential thingcalled the chain of custody. In Digital forensic thereare two categories of evidence declared, namely Phys-ical Evidence and Digital Evidence. In this case, thereare two terms that are almost the same, i.e. elec-tronic evidence and digital evidence. Electronic ev-idence has a physical form and can be identified vi-sually (computer, mobile phone, camera, CD, harddisk, etc.), while digital evidence is evidence that isextracted or recovered from electronic evidence (canbe a file, email, short message, image, video, log,text). Chain of custody is an effort to maintain and en-sure integrity in digital evidence and the procedure fordocumenting chronologically the evidence (Prayudiand Sn, 2015). The characteristics of digital evidenceaffect the level of difficulty of handling digital evi-dence with a predetermined method.Digital evidence

has a number of characteristics, such as easy to be du-plicated and transmitted, very susceptible to be mod-ified and removed, easily contaminated by new data,and time sensitive. Digital evidence is also very possi-ble to cross countries and legal jurisdictions. For thisreason, according to (Schatz, 2007) the handling ofchain of custody of digital evidence is much more dif-ficult than the handling of physical evidence, in gen-eral. In contrast to physical evidence, digital evidenceis very dependent on the interpretation of its content.Therefore, the integrity of the evidence and the abilityof the expert to interpret the evidence will be influen-tial in sorting digital documents available to serve asevidence.

Digital forensic generally implements 5w1hwhich is what, where, when, why, who, how. Whatis a form of crime committed, where is the placed thecrime is committed, when is the time when the crimeis committed, why is it the reason and motive of thecrime that occurred, who is the suspect in the crimeand the victims of a crime related, and how is themethod of crime carried out from the perspective ofcriminals and how, procedures, methods of analysis,legal access rights to handle evidence from the per-spective of the investigator. In digital forensic chal-lenges that often arise are about how to classify evi-dence (Turner, 2005), rebuild, rearrange, clarify evi-

Ramadhan, R., Mualfah, D. and Hariyadi, D.Digital Forensics: Acquisition and Analysis on CCTV Digital Evidence using Static Forensic Method based on ISO /IEC 27037:2014.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 85-89ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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dence both systemally and visually human, and howto use a standard and comprehensive communicationlanguage in court presentations Classification of dig-ital evidence is a very important because authenticityand integrity must be maintained in accordance withthe conditions when they were first discovered andthen presented at law court proceedings (Cosic et al.,2011) According on the facts and problems related todigital forensic and the handling described above, inthis case the author will describe the practice of acqui-sition and analysis of digital evidence in the form ofCCTV footage that displays conditions of recordingwith inadequate lighting using forensic static meth-ods.

Figure 1: Resolution on Frames

Another polemic found in handling this case isthat human objects recorded in CCTV are differentfrom suspected human objects in real life in anatom-ical aspects of body size. In real life the size of thesuspected weight is in the range of around 90kg butwhen viewed on CCTV the object’s weight is in therange of 60-75kg. The aspect ratio and reslolution onCCTV footage is an issue in this polemic. There arevarious aspect ratio figures in digital visualization.

Figure 2: Aspect Ratio

In simple terms, the first step taken is the ac-quisition process which is taking physical evidenceof CCTV devices that are labeled by implementingthe principle of chain of custody (Giova, 2011) be-cause the evidence must be maintained based on in-tegrity and authenticity in accordance with the con-ditions when it was first discovered will be submit-ted to court. The next acquisition step is the practice

of taking digital evidence from video recording datafrom CCTV file system storage. The next step of thispractice is to calculate the hash value of the video file,scene and frame classification, metadata analysis, dig-ital manipulation examination, and reporting.

2 METHOD AND MATERIAL

Referring to the previous forensic protocol compo-nent, there are general steps that can be defined ab-stractly to produce models that are not dependent oncertain technologies or electronic crime. Static Foren-sic analysis has limitations that is it cannot describeevents accurately in accordance with their actual con-ditions (Mrdovic et al., 2009). The basis of thismodel is to determine the key aspects of the proto-col mentioned above and ideas from traditional foren-sics, specifically the protocol for physical crime scenesearches (Reith et al., 2002). Handling Digital Evi-dence with systems related to CCTV is increasinglycomplex. This is influenced by digital and opticalsystems that have developed from year to year.Thecrime scene in this case is very crucial because itwill have a significant effect on the course of inves-tigation. the onion skin route is implemented in thecrime scene related case. In the research of (Hariyadiet al., ), the CCTV acquisition model was divided intotwo stages, namely pre-acquisition and core acquisi-tion. Pre-acquisition is a problem that investigatorsmust consider when he is at the scene. In the Pre-acquisition phase it emphasizes the preparation andidentification of all matters relating to CCTV systems.Things to note are in the following figure 3:

Integrity and confidentiality are the main valuesof Pre-Acquisition aspect. In simple terms, handlingphysical evidence or digital evidence based on SNIISO / IEC 27037: 2014 were as follows (Nasional,2014):• Minimize handling of the original digital device

or potential digital evidence.• Account for any changes and actions into a com-

prehensive documentation• Comply and match with local rules and law.• The Digital Evidence First Responder and Digi-

tal EvidenceSpecialist should not take actions be-yond their competence.

3 RESEARCH METHOD

Based on literature studies and literature reviews,in the process of digital forensic investigations in this


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Figure 3: Pre-Acquisition

case requires a method of pre-acquisition. After im-plementing the pre-acquisition, the core-acquisitionprocess will be mapped on the chart following figure4:

Figure 4: Pre-Acquisition

This analysis stages requires contributions fromthird-party tools applications. These tools assist inaccomplishing some of forensic steps, primarily thesystematic search for evidence (Reith et al., 2002). At

the following table 1 are some tools that used in thiscase:

Table 1: Third-party tools

Tools UsabilityMacHAsh Calculate Hash VAlueExifTool Metadata Processing

Adobe Premiere Video EditorAdobe Lightroom Visual Tuner

3.1 Imaging

Imaging stages at core acquisition are the first step inthis step. Imaging is one of the essence in the foren-sic static method. Calculation of hash values is alsoone of the elements of this stage.Forensic data is ac-quired by using different kinds of external deviceslike USBs, external hard derives etc. or CD,DVDsand then this data is brought into the forensic labfor investigators to perform different kinds of oper-ations/steps to forensically analyze evidentiary data(Rafique and Khan, 2013). The application for calcu-lating hash values in this case is Mac Hash which runson Macintosh operating systems

3.2 Collection

At the collection stage all files that have finished theimaging process will be collected and then sorted.This stage is also a crucial stage in CCTV foren-sics because (Perrott et al., 2002) there are so manyrecorded video files as long as the CCTV operates(Cucchiara, 2005). In this case there are 3 cameraswith suspicious objects. In this study the authors tooksamples from the 3 cameras. Calculation of (Kerr andvan Schyndel, 2014) hash values is also done at thisstage. The following results of the hash value calcu-lation are in table 2:

3.3 Analysis

3.3.1 Metadata

At the analysis stage begins by processing metadatausing Exiftool. The process of analyzing metadata isimplemented to see the composition and characteris-tics of the file to be analyzed in this case is a typefile .AVI. The following figure 5 is an example of theoutput from Exiftool:

3.3.2 Multimedia Tools

Implementing multmedia tools contributes to thisanalysis. The (Zhou et al., 2011) contribution given

Digital Forensics: Acquisition and Analysis on CCTV Digital Evidence using Static Forensic Method based on ISO /IEC 27037:2014

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Table 2: Third-party tools

File Name Hash Value25 01 R 20170626050000 (VIDEO CAM 1) 740709CD749F975183B4B85026B822DD24 02 R 20170626040000 (VIDEO CAM 2) 15AF1C78BA8401ACB84E968EC26F9ADD25 07 R 20170626050000 (VIDEO CAM 7 E091E024C497C499C0B04A6A8E1D0C85

Table 3: Time Stamp

Cam Device Date on Device (yy-mm-dd) Time as Suspicious Object AppearedCamera 1 2017-06-26 05.01.39 up to 05.02.04Camera 2 2017-06-26 04.11.24 up to 04.25.59Camera 7 2017-06-26 05.02.02 up to 05.02.28

Figure 5: Metadata in Exiftool interface

is the ability to manipulate the visual aspects of thisdigital evidence. Adobe Premiere is used to groupand cut (if needed) and screenshots when a suspiciousobject has been found in the entire video file on theevidence. The next step is to display the screenshotin Adobe Lightroom. The Adobe Lightroom appli-cation in this case contributes as a tool for adjustingimages or objects if the original evidence cannot beanalyzed naturally because of the visual limitationsthat come from CCTV recording devices. Apart fromstatements related to the use of multimedia tools inanalyzing digital evidence, analysis and manipulationof these files must use files that have been duplicatedso that the original digital evidence is not contami-nated and change the hash values that have been cal-culated. Changing the hash value means that it haseliminated the integrity of the acquisition of digitalevidence in forensic investigations. Here is an exam-ple of duplicated digital evidence manipulation in theform of a visual file using Adobe Lightroom:

Figure 6: Visual manipulation on Adobe tools

3.3.3 Report

At the reporting stage the content attached containsthe whole investigation from beginning to end, allcharts, forms of evidence, methodology and conclu-sions (Stephenson, 2003). In this study the authoronly emphasizes the essential aspects of the TimeStamp aspect. Time stamp is the writing of impor-tant times where the evidence in the form of CCTV isrecording suspicious objects. The following table 3 isan example of the time stamp in this case:

4 CONCLUSION

Pre-Acquisition and Core-Acquisition are the mainstages in the investigation and analysis of digital ev-


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idence. In the analysis of digital forensic investiga-tions requires the integrity of the authenticity of theevidence from the time it is found, acquired, ana-lyzed until the reporting stage in accordance with theprinciple of the chain of custody. Technically the in-tegrity and authenticity of the evidence can be provenby calculating the hash value. In this case with evi-dence in the form of CCTV, it also requires the abil-ity to use multimedia aspect to analyze digital evi-dence. This digital forensic analysis cannot convicta crime but only reinforces actual expectations. Theweakness in this study is that multimedia manipula-tion can only clarify objects with poor light but can-not accurately compare the composition of objects onthe screen with objects in the real world.

ACKNOWLEDGEMENTS

This paper was supported by Universitas Islam Riau.

REFERENCES

Cosic, J., Cosic, Z., and Baca, M. (2011). An ontologicalapproach to study and manage digital chain of custodyof digital evidence. Journal of Information and Orga-nizational Sciences, 35(1):1–13.

Cucchiara, R. (2005). Multimedia surveillance systems. InProceedings of the third ACM international workshopon Video surveillance & sensor networks, pages 3–10.ACM.

Giova, G. (2011). Improving chain of custody in forensicinvestigation of electronic digital systems. Interna-tional Journal of Computer Science and Network Se-curity, 11(1):1–9.

Hariyadi, D., Nastiti, F. E., and Aini, F. N. Frameworkfor acquisition of cctv evidence based on acpo and sniiso/iec 27037: 2014.

Kerr, M. and van Schyndel, R. (2014). Adapting law en-forcement frameworks to address the ethical problemsof cctv product propagation. IEEE Security & Pri-vacy, 12(4):14–21.

Mrdovic, S., Huseinovic, A., and Zajko, E. (2009). Com-bining static and live digital forensic analysis in vir-tual environment. In 2009 XXII International Sympo-sium on Information, Communication and AutomationTechnologies, pages 1–6. IEEE.

Nasional, B. S. (2014). Pedoman identifikasi, pengumpu-lan, akuisisi dan preservasi bukti digital (iso/iec27037: 2012, idt).

Perrott, A., Lindsay, A. T., and Parkes, A. P. (2002). Real-time multimedia tagging and content-based retrievalfor cctv surveillance systems. In Internet MultimediaManagement Systems III, volume 4862, pages 40–49.International Society for Optics and Photonics.

Prayudi, Y. and Sn, A. (2015). Digital chain of custody:State of the art. International Journal of ComputerApplications, 114(5).

Rafique, M. and Khan, M. (2013). Exploring static andlive digital forensics: Methods, practices and tools.International Journal of Scientific & Engineering Re-search, 4(10):1048–1056.

Reith, M., Carr, C., and Gunsch, G. (2002). An examinationof digital forensic models. International Journal ofDigital Evidence, 1(3):1–12.

Schatz, B. L. (2007). Digital evidence: representationand assurance. PhD thesis, Queensland University ofTechnology.

Stephenson, P. (2003). A comprehensive approach to digitalincident investigation. Information Security TechnicalReport, 8(2):42–54.

Turner, P. (2005). Unification of digital evidence from dis-parate sources (digital evidence bags). Digital Inves-tigation, 2(3):223–228.

Zhou, L., Chao, H.-C., and Vasilakos, A. V. (2011). Jointforensics-scheduling strategy for delay-sensitive mul-timedia applications over heterogeneous networks.IEEE Journal on Selected Areas in Communications,29(7):1358–1367.

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Testing the Role of Fish Consumption Intention as Mediator

Junaidi1, Desi Ilona2, Zaitul3, and Harfiandri Damanhuri11Faculty of Fisheries and Marine, Universitas Bung Hatta, Indonesia

2Faculty of Economic, Universitas Putra Indonesia YPTK, Padang, Indonesia3Faculty of Economic, Universitas Bung Hatta, Indonesia

[email protected], [email protected], [email protected], [email protected]

Keywords: Theory Of Plan Behaviour, Consumption Behaviour.

Abstract: This research investigate the role of an intention to consume fish as mediating variables between six variables(three variables from theory of plan behaviour and others from (Tomic, Matulic, and Jelic 2016). Theory ofplan behaviour is applied to understand the phenomena’s. The data is analysed using the structural equationmodel (SEM). The finding show that an intention to consume fish is succeeding in mediating relationshipbetween attitude toward fish consumption and consumption behaviour. However, the effect of other variables(subjective norm, perceived behavioural control, healthy, availability and responsibility) on consumptionbehaviour is not successfully mediated by an intention to consume fish. This study has theoretical and practicalimplication and they are discussed in this paper.

1 BACKGROUND OF STUDY

Consumption of sea food has been varyingsubstantialyacross countries, family and individually(Olsen 2004).In country level, European countryconsume fish 20 kg per capita and 39 kg inIndonesia (Tran et al. 2017). In addition, Olsen(2003) identified the stream of research regardingto the individual fish consumption behaviour:socio-economics and demographic perspectives,and psychologicalperspective. From psychologicalperspective, food consumption behaviour and choiceis explained by psychological constructs, such associal norm, belief, attitude, motivation, knowledgeand other psychological variables (Shepherd andRaats 1996). Fish consumption has several reasons,such as diet, nutrition, and etc.(Carlucci et al., 2015).In fact, fresh fish consumption at least twice a weekhave a positively effect on health (Sioen et al.,2008). The research question regarding to the fishconsumption behaviour is why the fish consumptionbehaviour varies.

There are several previous researchesinvestigating the fish consumption behaviour amongindividual (Tomic et al., 2016; Badr et al., 2015;Thorsdottir et al., 2012; Murray et al., 2017; Khanet al., 2018; Birch and Lawley, 2012; Milosevic et al.,2012; Cardoso et al., 2013; Grieger et al., 2012).From the previous studies, there is a lack of studies

investigating the fish consumption behaviour usingthe Indonesia’s data. further, there is limited studiesdetermining the role of an intention to consume fishas mediating variable between attitude, subjectivenorm, perceived behavioural control (Ajzen, 1991)and other variables are being tested by (Tomic,Matulic, and Jelic 2016): healthy, availability andresponsibility. Therefore, this study investigatesthe mediating role of an intention to consume fishbetween six variables and consumption behaviour.Therefore, we test six hypotheses:

H1: Intention to consume fish mediate therelationship between attitude and fishconsumption behaviour

H2: Intention to consume fish mediate therelationship between subjective norm andfish consumption behaviour

H3: Intention to consume fish mediate therelationship between perceived behaviourcontrol and fish consumption behaviour

H4: Intention to consume fish mediate therelationship between healthy and fishconsumption behaviour

H5: Intention to consume fish mediate therelationship between availability and fishconsumption behaviour

H6: Intention to consume fish mediate the

90Junaidi, Ilona, D., Zaitul and Damanhuri, H.Testing the Role of Fish Consumption Intention as Mediator.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 90-97ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

relationship between responsibility and fishconsumption behaviour

This paper is organised into four sessions. Firstsession is discussed about the research background.Method and material is in second session. It isfollowed finding and discussion as third session.Finally, this paper is closed by conclusion andrecommendations.

2 METHOD AND MATERIAL

Academics staffs working in private university inPadang is research object. There are 301 questionersdistributed to respondent, 18.27% of respondentsreturned the questioner. Primary data is appliedby using survey method (on-line). There arethree type of latent variables used here: latentdependent variable (fish consumption behaviour),latent independent variables (attitude towardfish consumption, availability, fish consumptionbehaviour, healthy, perceived behavioural control,responsibility, and subjective norm), and latentmediating variable (intention to consume fish).Fish consumption behaviour refers to how oftenrespondent consume fish the last few month (Tomic,Matulic, and Jelic 2016). In addition, intention toconsume fish has two items adopted from (Ajzen1991). Further, attitude toward fish consumption ismeasured by five items where two items adoptedfrom (Tomic, Matulic, and Jelic 2016) and other threeitems was taken from (Verbeke and Vackier 2005).Thus, subjective norm has four items suggested by(Verbeke and Vackier 2005). Moreover, perceivedbehaviour control is measured by three items takenfrom (Verbeke and Vackier 2005).

Healthy (involvement in health) has three itemstaken from (Altintzoglou et al., 2011). Fishavailability is measured by three items from (Myrlandet al., 2000). Finally, three item is used to measure theresponsibility (moral obligation) taken from (Verbekeand Vackier, 2005). All constructs are assessedusing the 5-point Likert scale (1=strongly disagree,5=strongly agree). SEM-PLS is applied to analyse theresearch data (Chin 1998; Vinzi et al. 2010). In thiscase, smart-pls is used (Hair et al., ). Two assessmentis conducted to gain the confirmed measurementmodel and rigorous structural model (J. Hair et al.2014). In measurement model, we have to assess twotypes of validity: convergent validity and discriminantvalidity (J. F. Hair et al. 2013). Structural model isaimed for test the relationship (Joseph F Hair et al.2017). Mediation role is tested using (Zhao et al.,2010)’s mechanism.


3.1 Demographic Data

Data demography is classified into four types:gender, age, position and income. figure 1 showrespondentgender and age. Regarding to respondentage, 49% of respondent is female and the rest ismale (51%). In addition, respondent with age of26-30-year-old is about 5%. Thus, 20% of respondentis with age of 36-40 years old. Further, respondentwith age of 36-40 years old is 5% and followedby 35% of respondent with age of 41-50 yearsold. Moreover, respondent with age more than 50years old is 35%. On other two demographic data

Figure 1: Demographic data: gender and Age

is respondent career position and income. Figure2 provide us with the percentage of position andincome of respondents. There are four type of lectureposition: lecturer (24%), senior lecturer (38%),associate professor (31%) and professor(7%). Inaddition, respondent with income of less than Rp. 3million is 16% and followed by 33% respondent withincome of Rp. 3.1- Rp. 6 million. Thus, respondentwith Rp. 6.1 –Rp. 9 million of income is 35% andfinally 16% respondent is with income of more thanRp. 6 million.


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Figure 2: Demographic Data: Position And Income

3.2 Measurement Model Assessment

as mention in the previous session, thereare two assessments while using smart-pls:measurement model assessment and structuralmodel assessment(Joseph F Hair et al. 2017).Table 1 demonstrate the result of measurementmodel assessment for convergent validity. There arefour smart-pls properties used here: outer loading,Cronbach’s alpha, composite reliability and averagevariance extracted (AVE). All items have an outerloading greater than 0.700 for first algorism, exceptfor item of perceived behavioural control (pbc2, andpbc3). Having deleted these two items, the secondalgorism has been run and thereafter, all items havean outer loading greater than 0.700. therefore, itreached the convergentvalidity requirement (Hulland1999). Second convergent validity assessment isCronbach’s Alpha (CA) and Composite reliability(CR) and their value must exceed 0.700 (Bagozzi andYi, 1988). As indicated by value of CA and CR (5thand 6th Colum), their values are above the smart-plsrequirement: above 0.70. Finally, average varianceextracted (AVE)’s value should be greater than 0.500.the result show that all constructs have AVE’s valueabove 0.500 and therefore, it can be concluded that itachieves the cut off value.

Discriminant validity is the second assessmentfor measurement model. There are three type ofassessment for discriminant validity: Fornell-Lackercriterion (Fornell and Larcker, 1981), cross loading(Jorg Henseler, Ringle, and Sinkovics 2009) andHeterotrait-Monotrait ratio (Jorg Henseler, Ringle,and Sarstedt 2015). Table 2 demonstrate the result of

Table 1: Measurement Model Assessment Convergentvalidity

construct Item OL CA CR AVE

attitude toward fish

atf1 0.94

0.94 0.96 0.81

atf2 0.91atf3 0.83atf4 0.93atf5 0.9

availabilityava1 0.87

0.89 0.91 0.79ava2 0.81ava3 0.96

fish con beh fcb 1 1 1 1

healthyh1 0.88

0.79 0.87 0.7h2 0.76h3 0.87

intention to consume fishicf1 0.99

0.98 0.99 0.97icf2 0.98icf3 0.98

subjective norm

nor1 0.9

0.86 0.9 0.71

nor2 0.73nor3 0.9nor4 0.81

perceived behaviour control pbc1 1 1 1 1

responsibilityres1 0.95

0.94 0.96 0.9res2 0.97res3 0.92

discriminant validity using Fornell-Lacker criterion.Square root AVE of a construct should be higherthan the correlation between that construct with otherconstruct. For example, square root AVE of ICF(0.984) is greater than its correlation with otherconstruct (0.517 with ATF, 0.032 with AVA andetc). Therefore, it can be concluded that discriminantvalidity requirement using Fornell-Lacker criterion isachieved (Fornell and Larcker, 1981).

Table 2: Measurement Model Assessment Discriminantvalidity-Fornel-Lacker Criterion

cons ICF ATF AVA FCB H PBC RES NORICF 0.98ATF 0.52 0.9AVA 0.03 0.12 0.88FCB 0.43 0.72 -0.07 1

H 0.25 0.63 0.09 0.38 0.84PBC 0.17 0 0.31 -0.05 -0.17 1RES 0.28 0.63 0.09 0.5 0.52 -0.05 0.95NOR 0.23 0.57 0.21 0.41 0.54 -0.13 0.76 0.84Note: ICF (intention to consume fish), ATF (attitude toward fishconsumption), AVA (avalaibality), (FCB) fish consumption behaviour, H(healthy), PBC (perceived behavioural control), RES (responsibility), andNOR (subejctive norm).

Second assesment for discriminant validity iscross loading (Wong 2013). The result ofcross-loading can be seen in Table 3 below.Thecross-loading refers to loading an indicator shouldbe higher to its assigned construct (Jorg Henseler,Ringle, and Sinkovics 2009). For example, itemsfor ICF construct is higher loading to ICF (bold)compared to other construct (non-bold). It alsohappens to other items. Therefore, the discriminantvalidity using cross-loading is reached.


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Table 3: Measurement Model Assessment Discriminantvalidity-Cross Loading

Items ICF AVA FCB H ICF PBC RES NORatf1 0.94 0.08 0.72 0.61 0.54 -0.03 0.54 0.5atf2 0.91 0.02 0.7 0.52 0.49 0 0.51 0.41atf3 0.83 0.2 0.56 0.6 0.36 0.1 0.57 0.48atf4 0.93 0.17 0.62 0.58 0.45 0.01 0.65 0.61atf5 0.9 0.19 0.63 0.53 0.43 -0.05 0.59 0.57ava1 0.1 0.87 0.01 0.16 0.02 0.2 0.11 0.21ava2 0.17 0.82 -0.02 0.21 0.01 0.32 0.17 0.23ava3 0.11 0.96 -0.1 0.03 0.04 0.33 0.06 0.19fcb 0.72 -0.07 1 0.38 0.43 -0.05 0.5 0.41h1 0.56 0.1 0.3 0.88 0.23 0.02 0.52 0.45h2 0.41 -0.07 0.29 0.76 0.18 -0.3 0.24 0.4h3 0.58 0.16 0.38 0.87 0.23 -0.17 0.51 0.5icf1 0.52 0.03 0.41 0.29 0.99 0.14 0.29 0.24icf2 0.49 0.02 0.42 0.22 0.98 0.19 0.27 0.21icf3 0.51 0.04 0.44 0.24 0.98 0.17 0.27 0.23nor1 0.53 0.21 0.34 0.48 0.21 -0.18 0.71 0.9nor2 0.45 0.29 0.38 0.47 0.17 -0.04 0.55 0.73nor3 0.51 0.13 0.4 0.38 0.18 -0.16 0.72 0.9nor4 0.41 0.1 0.28 0.51 0.2 -0.04 0.56 0.81pbc1 0 0.31 -0.05 -0.16 0.17 1 -0.05 -0.13res1 0.59 0.03 0.46 0.5 0.27 -0.03 0.95 0.71res2 0.62 0.08 0.51 0.53 0.32 -0.11 0.97 0.74res3 0.58 0.16 0.45 0.45 0.19 0.04 0.92 0.71Note: ICF (intention to consume fish), ATF (attitude toward fishconsumption), AVA (availability), (FCB) fish consumption behaviour, H(healthy), PBC (perceived behavioural control), RES (responsibility), andNOR (subjective norm).

Third assessment for discriminantvalidity is Heterotrait-Monotrait ratio(HTMT). The ratio is resulted from averageheterotrait-heteromethod correlations relative to theaverage monotrait-heteromethod correlation (JorgHenseler, Ringle, and Sarstedt 2015; Joseph F Hairet al. 2017). (Kline 2011) argue that HTMT ratiobelow 0.85 indicate that discriminant validity isachieved. Table 4 provide us with the result ofHeterotrait-Monotrait ratio and all values are below0.85 and it can be concluded that discriminantvalidity is achieved.

Table 4: Measurement Model Assessment Discriminantvalidity- Heterotrait-Monotrait ratio (HTMT)

cons ICF ATF AVA FCB H PBC RES NORATFAVA 0.16FCB 0.74 0.05

H 0.72 0.21 0.43ICF 0.53 0.03 0.44 0.29PBC 0.04 0.33 0.05 0.22 0.17RES 0.67 0.14 0.52 0.58 0.28 0.06NOR 0.64 0.27 0.45 0.65 0.25 0.13 0.84Note: ICF (intention to consume fish), ATF (attitude toward fishconsumption), AVA (availability), (FCB) fish consumption behaviour, H(healthy), PBC (perceived behavioural control), RES (responsibility), andNOR (subjective norm).

3.3 Structural Model Assessment

Having assessed the measurement model, assessmentfor structural model is conducted. Structural modelassessment is for hypothesis testing and deals with

relationship between latent variables(Joseph F Hair etal. 2017). before testing for hypothesis, it first looksfor predictive relevant and predictive power of model.Q square is used to see the predictive relevance ofmodel and its value should be higher than 0.000.both endogenous constructs have Q square above0.000. in fact, FCB and ICF have Q square 0.113 and0.254 respectively. Therefore, they are classified asmedium predictive relevance (Jorg Henseler, Ringle,and Sinkovics 2009). Second, R square is used to seethe predictive power of structural model. The valueof R square is 0.174 and 0.222 for FCB and ICFrespectively. Thus, predictive power is below 0.33and it is categorised as weak predicative power (Chin1998).

Table 5: Assessment of Structural Modelendogenous construct Q square decision R square decisionFCB 0.11 Medium 0.17 WeakICF 0.25 Medium 0.22 Weakrelationship Coef. t stat p value decisionATF −> ICF 0.59 3.3 0.00*** supportedAVA −> ICF -0.09 0.52 0.6 not supportedH −> ICF -0.05 0.36 0.722 not supportedICF −> FCB 0.43 3.44 0.00*** supportedPBC −> ICF 0.19 1.38 0.17 not supportedRES −> ICF -0.04 0.26 0.8 not supportedNOR −> ICF 0 0.01 0.99 not supportedNote: ICF (intention to consume fish), ATF (attitude toward fishconsumption), AVA (availability), (FCB) fish consumption behaviour, H(healthy), PBC (perceived behavioural control), RES (responsibility), andNOR (subjective norm).

the significant determinants of fish consumptionintention are attitude toward fish consumption(β=0.587, p-value=0.001). other variables (AVA, H,PBC, RES, and NOR) do not have a significant effecton fish consumption intention due to their p valueabove 0.05. In addition, fish consumption intentionhas a significant relationship with fish consumptionbehaviour (β=0.434, p-value=0.001). therefore, thehigher the fish consumption intention, the greater fishconsumption behaviour. Figure 4 show the structuralmodel.

To answer whether fish consumption intentionmediating relationship between determinants and fishconsumption behaviour, the assessment of directeffect and indirect effect are conducted. Table 6demonstrate the result of direct effect and out of sixdeterminants, only attitude toward fish consumptionhas a significant relationship with fish consumptionbehaviour (β=0.702, p-value=0.000). thus, it meansthat the higher the attitude toward fish consumption,the higher fish consumption behaviour. Othervariables do not have a significant effect due to theirp value above 0.05.

Next analysis is indirect effect assessment. Thereare six indirect effect are assessed and only indirecteffect (ATF− >ICF− >FCB) has a positive effect


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Figure 3: Structure Model

Table 6: Assessment of direct effectdirect effect coef. t stat p value decision

ATF −> FCB 0.7 3.63 0.00*** supportedAVA −> FCB -0.19 1.55 0.12 not supportedH −> FCB -0.13 0.93 0.36 not supportedPBC −> FCB -0.02 0.15 0.88 not supportedRES −> FCB 0.09 0.5 0.62 not supportedNOR −> FCB 0.04 0.26 0.8 not supportedNote: ICF (intention to consume fish), ATF (attitude toward fishconsumption), AVA (availability), (FCB) fish consumption behaviour, H(healthy), PBC (perceived behavioural control), RES (responsibility), andNOR (subjective norm).

(β=0.255, p-value=0.058) at α=10% (see table 7).Other variables have p value above 0.05. (Zhao,Lynch, and Chen 2010) argue that there should beonly one requirement to establish (i.e. indirect effect(axb) is significant) and it does not need for significanteffect to be mediated (path c). However, if itsindirect effect and direct effect are significant andthey have same direction, the mediation is fallen intocomplementary mediation(Zhao, Lynch, and Chen

2010). In this case, direct and indirect effect aresignificant and they have the same direction (positive)and we can conclude that there is a complementarymediation role of fish consumption intention (ICF)between attitude toward fish consumption (ATF) andfish consumption behaviour (FCB). Figure 4 provideus with complex structural model of research.

Table 7: Assessment of indirect effectindirect effect Coef. t stat p value decision

ATF −> ICF −> FCB 0.26 1.9 0.06* supportedAVA −> ICF −> FCB -0.04 0.52 0.6 not supportedH −> ICF −> FCB -0.02 0.34 0.73 not supportedPBC −> ICF −> FCB 0.08 1.49 0.3 not supportedRES −> ICF −> FCB -0.02 0.24 0.81 not supportedNOR −> ICF −> FCB 0 0.01 0.99 not supportedNote: ICF (intention to consume fish), ATF (attitude toward fishconsumption), AVA (availability), (FCB) fish consumption behaviour, H(healthy), PBC (perceived behavioural control), RES (responsibility), andNOR (subjective norm).


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Figure 4: Structure Model

4 CONCLUSION ANDRECOMENDATION

The important of fish has been documented by severalexperts. Due to benefit of fish, studies investigatingfactor effected fish consumption behaviour hasbeen largely done. However, there is a limitedstudy investigating using Indonesia’s data. Infact, there is also lack of studies determine therole of an intention to consume as mediatingvariables between antecendents of intention toconsume fish (attitude, norm, perceived behaviouralcontrol, healthy, availability, and responsibility)and consuming behaviour. The finding show

that intention to consume fish is succesfullymediated the relationship between attitude toward fishconsumption and fish consumption behaviour.

5 CONCLUSIONS

Process integration has a fairly high risk andcan have an impact on objectives. Therefore, itis necessary to mature planning and identify therisks that may occur either during managementsystem process integration.The identified risks mustbe managed by defining their causes and impacts.Once known cause and impact, it can be proposed


95

preventive measures to prevent occurrence andcorrective action in response if the impact occurs.

Based on this study, there are 10 highest risks inmanagement system process integration and 5 risksoccuring in scope component/clause.

ACKNOWLEDGMENTS


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Segmentation of Palm Oil Leaf Disease usingZoning Feature Extraction

Ause Labellapansa, Ana Yulianti and Agus YulianiDepartment of Informatics,Universitas Islam Riau, Pekanbaru, Indonesiaause.labella, [email protected], [email protected]

Keywords: Palm oil, Pests, Digital Image Processing, Zoning, Fitur Extraction.

Abstract: Oil palm (Elaeis) is an industrial plant that produces large profits, especially in Indonesia. One of the factorsthat can affect the yield of this plant is destructive pests including Limacodidae and Psychidae. Delay indealing with pest problems can cause poor results. This study uses the help of digital image processing toinentify two types of pests found on palm oil leaves of pests. Segmentation will be carried out to determinethe characteristics of Limacodidae and Psychidae pests. The image processing method used is the zoningfeature ecstasy. It is expected that knowing the types of pests suffered by oil palm trees can accelerate therecovery of oil palm trees so as to produce good quality of fruit.

1 INTRODUCTION

Indonesia is the world’s largest Palm Oil producer.It is spread out from Aceh region, the East Coast ofSumatra, Java, Kalimantan and all the way to Su-lawesi (Ermawati and Saptia, 2013). One of the fac-tors that can affect the yield of palm oil is destructivepests.

(Pribadi and Anggraeni, 2011) states that if plantsare in low humidity environment conditions, they willbe easily attacked by pests and diseases. This is sus-pected due to saponin compounds found in plants(which act as self-defense from insect attacks) willdecrease qualitatively and quantitatively so that theplants will easily be harmed by pests.

Some of the destructive pests that attack the oilpalm plantations are Limacodidae and Psychidae.The potential loss of yield caused by these two pestscan reach 35% (Wood et al., 1973). Limacodidae is apalm-leaf-eating pest that often harms oil palm plan-tations in North Sumatra.

The attack of the caterpillar pest which is a palm-leaf-eating caterpillar has caused many problems.This causes the loss of leaves of the plants which hasa direct impact on the decrease in production so thisindicates how serious the caterpillar attack is (Pahan,2008).

To overcome this problem, computer system assis-tance is needed by utilizing image processing knowl-edge to identify these two types of pests. (Harahapet al., 2018) identified oil palm leaf disease using the

Support Vector Machine method with an accuracy of90% and (Aji et al., 2013) did the same thing usingartificial neural networks and produced an accuracyvalue of 87.75%. Feature extraction for finding dis-ease in leaves was carried out by (Arivazhagan et al.,2013). The use of a deep convolution neural networkwas carried out by (Sladojevic et al., 2016) to identify13 leaf diseases with a precision level of 91% to 98%.Detecting and classifying the plant leaf diseases basedby using GLCM and SVM on the Apple leaf has beenconducted by Sivakamasundari, G., & Seenivasagam(Sivakamasundari and Seenivasagam, 2018) with ac-curacy level about 92%. Our research is preliminaryresearch by identifying the image of palm oil leavesand has not entered the classification stage.

2 RESEARCH METHODOLOGY

The steps in this study are shown in Figure 1. Theimage acquisition process is carried out by taking pic-tures of leaves attacked by destructive pests. The im-age will be processed from the original image to there-measurement stage by shrinking the pixel size to600x250 pixels and followed by binery processing.

Zoning Feature Extraction will divide the leaf im-age into several regions or zones of the same size, thevalue of the features obtained from the method willbe used to determine the results of the image value ofpalm oil leaves affected by Limacodidae and Psychi-

98Labellapansa, A., Yulianti, A. and Yuliani, A.Segmentation of Palm Oil Leaf Disease using Zoning Feature Extraction.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 98-101ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

Figure 1: Research Scheme

dae pests. Zoning is one of the most popular methodsused for optical character document characterization(Hegadi, 2012). The zoning calculation process is asfollows:

• Counting the number of black pixels per zone.

• Counting the zone that has the highest number ofpixels. Figure 2 and 3 is the number of Black Pix-els in Each Zone affected by Limacodidae Imageand Psychidae

Figure 2: The Number of Each Zone for Limacodidae

Figure 3: The Number of Each Zone for Psychidae

• Calculating the feature value of each zone. Thefeature values of each zone in the Limacodidaeaffected are:

z1 =z1z3

=13= 0,3 (1)

z2 =z2z3

=03= 0 (2)

z3 =z3z3

=33= 1 (3)

z4 =z4z3

=03= 0 (4)

While the feature values of each zone in the Psy-chidae affected are:

z1 =z1z1

=44= 1 (5)

z2 =z2z1

=04= 0 (6)

z3 =z3z1

=44= 1 (7)

z4 =z4z1

=34= 0,75 (8)

Figure 4: Image Causes by Limacodidae Pest

Figure 5: Image Causes by Psychidae Pest

Figure 6: Image from the Resizing process Caused by Li-macodidae Pests

Figure 7: Image from the Resizing process Caused by Psy-chidae Pests

Figure 4 is an image caused by the LimacodidaePest and figure 5 by the Psychidae Pest. The resizingprocess is shown in Figures 6 and 7. The next stage,the image of the leaf is changed to a grayscale image.Then that grayscale image will undergo a process ofconversion to binaries using a threshold value. In thistechnique, digital images will be classified into twoparts, namely objects and background.

Segmentation of Palm Oil Leaf Disease using Zoning Feature Extraction

99

The solution to the matrix of caterpillar impactreference image with a threshold value is 122 for Li-macodidae (Formula 9) and 88.5 for Psychidae (For-mula 10)

f (x,y) =

255, i f f (x,y)≥ 1220, i f f (x,y)< 122 (9)

f (x,y) =

255, i f f (x,y)≥ 88,50, i f f (x,y)< 88,5 (10)

Figure 8 is the image of the impact of Limacodi-dae binary process and Figure 9 is the image of theimpact of Psychidae binary process.

Figure 8: Result of Binary Process by Limacodidae Pests

Figure 9: Result of Binary Process by Psychidae Pestss

The next step is to use the zone extraction featurewhere the image of the leaf will be divided into sev-eral regions or zones of the same size. The featurevalues obtained from the method will be used to deter-mine the results of the image values of palm oil leavesaffected by Limacodidae and Psychidae. Zoning isone of the most popular methods used for documentoptical characterization (Hegadi, 2012). The calcula-tion process in the zoning method is as follows:

• Count the number of black pixels per zone.

• Calculates zones that have the highest number ofpixels.

• Calculates the feature value of each zone from thefeature value


Figure 10 is the result of zoning. Image 1 and 2 arethe images of Caterpillar Pests and image 3 and 4 are

Figure 10: Zoning Images

Figure 11: (Cont.) Zoning Images

images of Psychidae Pests. Each image will produce4 regions.

Table 1 is the value data for Figure 10. The zona-tion values of Figure 1 are 1, 0.40, 016, and 0. It canbe seen in Table 1 that there are significant differencesin zones 2 and 3.

Table 1: This caption has one line so it is centered.

Images Value ClassZone

1Zone

2Zone

3Zone

4

Image 1 1 0,40 0,16 0 Limacodidae

Image 2 0,92 0,96 0,28 1 Limacodidae

Image 3 0,33 0,16 1 0 Psychidae

Image 4 1 0,17 0 0 Psychidae


100

4 CONCLUSION

In research that has been done by using zoning featureextraction, values can be taken from each zone in theimage. The results of zoning can be developed intothe classification stage using k-NN, SVM, or artificialneural networks. The brightness, contrast, and back-ground of the image greatly affect the results that willbe processed by the zoning feature extraction.

REFERENCES

Aji, A. F., Munajat, Q., Pratama, A. P., Kalamullah, H.,Setiyawan, J., and Arymurthy, A. M. (2013). Detec-tion of palm oil leaf disease with image processing andneural network classification on mobile device. Inter-national Journal of Computer Theory and Engineer-ing, 5(3):528.

Arivazhagan, S., Shebiah, R. N., Ananthi, S., and Varthini,S. V. (2013). Detection of unhealthy region of plantleaves and classification of plant leaf diseases usingtexture features. Agricultural Engineering Interna-tional: CIGR Journal, 15(1):211–217.

Ermawati, T. and Saptia, Y. (2013). Kinerja ekspor minyakkelapa sawit indonesia the export performance of in-donesia’s palm oil. Buletin Ilmiah Litbang Perdagan-gan, 7(2):129–148.

Harahap, L. A., Fajri, R. I., Syahputra, M. F., Rahmat,R. F., and Nababan, E. B. (2018). Identifikasi penyakitdaun tanaman kelapa sawit dengan teknologi imageprocessing menggunakan aplikasi support vector ma-chine. In Talenta Conference Series: Agricultural andNatural Resources (ANR), volume 1, pages 53–59.

Hegadi, R. S. (2012). Recognition of printed kannada nu-merals based on zoning method. International Journalof Computer Applications, 975:8878.

Pahan, I. (2008). Paduan Lengkap Kelapa Sawit. NiagaSwadaya.

Pribadi, A. and Anggraeni, I. (2011). Pengaruh temper-atur dan kelembaban terhadap tingkat kerusakan daunjabon (anthocephalus cadamba) oleh arthrochista hila-ralis. Jurnal Penelitian Hutan Tanaman, 8(1):1–7.

Sivakamasundari, G. and Seenivasagam, V. (2018). Classi-fication of leaf diseases in apple using support vectormachine. International Journal of Advanced Researchin Computer Science, 9(1).

Sladojevic, S., Arsenovic, M., Anderla, A., Culibrk, D., andStefanovic, D. (2016). Deep neural networks basedrecognition of plant diseases by leaf image classifi-cation. Computational intelligence and neuroscience,2016.

Wood, B., Corley, R., Goh, K., et al. (1973). Studies on theeffect of pest damage on oil palm yield. Studies on theeffect of pest damage on oil palm yield., (58).

Segmentation of Palm Oil Leaf Disease using Zoning Feature Extraction

101

Analysis of Economy in the Improvement of Oil Production usingHydraulic Pumping Unit in X Field

Muhammad Ariyon, Novia Rita and Tribowo SetiawanDepartment of Petroleum Engineering, Universitas Islam Riau, Pekanbaru, Indonesiaaryonmuhammad, [email protected], [email protected]

Keywords: Hydraulic Pumping Unit, Efisiensi Volumetris NPV, IRR, POT, DPI.

Abstract: The wells of X fields are vertical wells with installed pumps being the Hydraulic Pumping Unit. The wells canstill be optimized by improving the performance of N and SL by trial and error method. Based on optimationanalysis result at well BM 1 by changing SPM and SL parameters on pump which installed with N 6 SPM andSL 100 inch got Qt equal to 144 bfpd, then converted to N 7 SPM and SL 100 inch so that there increase ofQt become equal to 199 bfpd And pump efficiency from 67% to 80%. While in the well BM 2 by changingthe parameters of SPM and SL on pumps installed with N 8 SPM and SL 100 inch obtained Qt of 284 bfpd,then converted to N 10 SPM and SL 110 inch so that there is an increase of Qt to equal to 583 bfpd pumpefficiency of 65% to 90%. In the economic analysis with Production Sharing Contract system can be knownwith non-capital investment of MMUS $ 0.150, obtained NPV contractor MUS $ 451.07, IRR> MARR,POT< 1 year and DPI 4.00.

1 INTRODUCTION

The oil production process by using the HydraulicPumping Unit (HPU) on the X field does not alwayswork optimally so that the oil flow rate cannot be fullyproduced optimally and makes the economic resultsof the production not obtained. According to thediscussion of (Brown, 1984), the ability of a well toproduce can be known by calculating the productivityof wells using IPR curves based on actual data in thefield. Optimization of the production rate can be doneby conducting a trial and error method for changes inStroke Per Minute (SPM) and Stroke Length (SL) ofthe pump.

The purpose of this study is to evaluate theproduction performance of the installed hydraulicpumping unit, to optimize the HPU to increase therate of production (Babbitt and Vincent, 2012; Beard,2013; Pickford and Morris, 1989). Analyze theeconomy of the HPU after obtaining a new productionrate.

2 METHOD

This research was conducted at X Field.Administratively, X Field is located in Siak SriIndrapura Regency, Riau Province, Indonesia.

Geologically, the X field is located in the CentralSumatra Basin. X Field has a very large oil contentand shallow well depth where Original Oil In Placeis 101.4 MMSTB with Recovery Factor 47.48%.Thewell type on X Field is vertical well and directionalwell. The wells to be examined in this research areBM # 1 and BM # 2 Wells.

Figure 1: Research sites

The research method used is field research orthis research use data from oil field. The data

102Ariyon, M., Rita, N. and Setiawan, T.Analysis of Economy in the Improvement of Oil Production using Hydraulic Pumping Unit in X Field.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 102-108ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

used are secondary data provided by field guides,expert opinions, principles and theories of guaranteedliterature.

Figure 2: Research flowchart.


3.1 Determination of Well Performanceand Maximum Flow Rate (Qmax)with Vogel Method

In knowing whether 4 wells in the X field can beoptimized, it is necessary to know the maximumflow rate (Qmax) in 4 wells with the HPU installed.The method used in determining Qmax is the Vogelmethod because the reservoir fluid flowing in the wellis 2 phase and 50-80% water cut (WC) (Chase andShaver, 2009; Ogunleye, 2012).

Table 1: The calculation results determine Sg Fluid,Gradient Fluid, Pr and Pwf.

WELL Specificgravity fluid(SgFluid).

Gradientfluid (Gf)

Reservoirpressure(Pr)

Bottom wellflow pressure(Pwf)

BM 1 0.92 0.400 146 78BM 2 0.97 0.420 55 41BM 3 0.977 0.423 84 33BM 4 0.94 0.407 50.8 5.6

After obtaining Sg fluid, Gradient fluid, Pr andPwf in table 1, the calculation of the vogel method is

carried out to obtain the maximum flow rate (Qmax),the following results are obtained.

Table 2: Maximum flow rate in the well on the use of theinstalled HPU.

WELL FluidFlowRate (Qt)BBL/D

OptFlowRate ofoil (Qo)

Max FlowRate (Qmax)BBL/D

WC % PI

BM 1 144 65 216 50 2.10BM 2 284 57 696 80 1.94BM 3 55 8 69 85 1.07BM 4 88 30 90 69 1.80

Based on production table 2, it can be seen thatfrom the 4 wells it has a fluid flow rate (Qt) which hasapproached Qmax, that is BM3 and BM5 wells whileBM4 wells have reached the economic limit. For thisreason, only 2 wells can be researched to optimize andanalyze the economics of BM1 and BM2 wells.

After finding out which wells to be optimized,the BM1 and BM2 wells then need to use the InflowPerformance Relationship curve to describe changesin the price of the well bottom flow pressure (Pwf)versus the flow rate (Q) produced. Then the resultsof changes in the bottom well pressure are obtainedfrom the flow rate in table 3.

Table 3: Results of changes in bottom well flow pressure toflow rate.

Well Pwf (psi)Q,

WellPwf Q

(Bfpd) (psi) (bfpd)146 0

BM 2

55 0125 52 50 109105 95 45 20995 114 40 30085 132 35 38175 148 30 454

BM 1 65 162 25 51755 175 20 57145 186 15 61630 199 10 65115 209 8 66310 212 5 6780 216 0 696

HPU performance known by making IPR curvesusing the vogel method which aims to determine themaximum pump flow rate, because in field X has atwo-phase flow, where (Wiggins et al., 1996) statesthe vogel method is usually used to determine themaximum flow rate of two fluid phases.

After obtaining Pwf against Q by assuming Pwfin table 3, the IPR curve (Inflow PerformanceRelationship) plot can be performed on BM1 and BM2 wells.

After knowing the Qmax and Pwf assumptionstowards each Q, then the next step is to know thevolumetric efficiency of the HPU installed in wellsBM1 and BM2.

Analysis of Economy in the Improvement of Oil Production using Hydraulic Pumping Unit in X Field

103

Figure 3: Pwf vs Q IPR curve in BM 1 well.

Figure 4: Pwf vs Q IPR curve in BM 2 well.

3.2 Volumetric Efficiency of HPUInstalled in BM1 and BM2 Wells

The procedure in determining the design of the HPUpump uses the (Jennings et al., 1989) procedure wherethe author determines the Pump Depth (L) price ofPlunger area (Ap), rod area (Ar), tubing area (Ar),plunger constant (K) and rod weight (Wr) and theprice of the pump speed (N). In BM1 and BM2 wells,the fluid flow lane (Qt) is obtained, namely BM1 wellswith 144 BFPD and BM2 with 284 BFPD.

Pump efficiency is performed to determine theoptimal pump performance in BM1 and BM2 wellsor not by looking at parameters such as Pump Size /Plunger diameter (Dp), Pump speed (N, SPM), Pumpstep length (SL, In), Acceleration factor (a), Plungerover travel (ep), Tubing (et) extension, Rod string (er),Effective plunger stroke (Sp), Pump constant (K),Pump capacity (V) and Pump volumetric efficiency(Ev) (Cui et al., 2014; Wang et al., 1995; Ye et al.,2017), then the results in Table 4 are obtained.

Based on Table 4, it can be analyzed that BM1wells with the use of 6 SPM (Stroke per minute) and100 SL (Stroke length) and the use of 1.75 in. Plungerdiameter obtained 213 bfpd pump capacity, while Qtin BM1 wells was 144 bfpd, volumetric efficiencywas obtained the pump is 67.40% While for BM2wells with the use of 8 SPM (Stroke per minute)

Table 4: Results of pump volumetric efficiency installed inBM 1 and BM 2 wells.

WELL BM1 WELL BM2PumpSize /diameterplunger

1.75PumpSize /diameterplunger

2.25

(dp, In) (dp, In)PumpSpeed 6

PumpSpeed 8

(N, SPM) (N, SPM)PumpSteplength

100PumpSteplength

100

(SL, In) (SL, In)Acceleration factor 0.05

Acceleration factor 0.09

(a) (a)PlungerOverTravel(ep, In)

0.02 PlungerOverTravel(ep, In)

0.06

Extentionof Tubing(et, In)

0.04 Extentionof Tubing(et, In)

0.09

RodString 0.18

RodString 0.40

(er, In) (er, In)EffectifPlunger 99.80

EffectifPlunger 99.58

Stroke Stroke(Sp, In) (Sp, In)Pumpconstant 0.36

Pumpconstant 0.59

(K) (K)PumpCapacity 213.40

PumpCapacity 469.80

(V, Bfpd) (V, Bfpd)VolumetricPumpEfficiency(Ev, %)

67.40 VolumetricPumpEfficiency(Ev, %)

60.45

and 100 SL (Stroke length) and the use of plungerdiameter of 2.25 in, the pump capacity of 469 bfpdwas obtained, while Qt in BM2 wells was 284 bfpd,the pump obtained a volumetric efficiency of 60%.

Based on the parameters in Table 4 and theQmax in 2 wells is quite large, the researcher triedto do optimization by changing the SPM and SLparameters in the hope of increasing Qt and thevolumetric efficiency of the installed pump becomingmore optimal than previously installed.


104

3.3 Optimization of BM1 and BM 2Wells

Optimization was carried out to increase theproduction flow rate in both wells using the trialand error method. the concept of trial and erroris to change the parameters of SPM and SL onthe installed pump in the hope of increasing thevolumetric efficiency of the pump as well as thefluid flow rate in wells BM1 and BM2. Next is theefficiency of the pump installed before optimization.

Table 5: The results of pump efficiency are installed beforeoptimization.

Well N (SPM)S

Qt (BFPD)Ev WC

(in) (%) (%)BM1

6 100 144 67.4 50

BM2

8 100 284 60.4 80

After that, optimization is done by changing theparameters of SPM and SL using the trial and errormethod. Then, it is obtained in table 6 below

Table 6: The results of installed pump efficiency afteroptimization.

Well N (SPM)S

Qt (BFPD)Ev WC

(in) (%) (%)BM1

7 100 199 80 50

BM2

10 110 583 90.4 80

Based on the results of the optimization in Table6 in BM1 wells by changing the SPM and SLparameters on the installed pumps with N 6 SPM andSL 100 in, Qt is 144 bfpd, then converted to N 7 SPMand SL 100, in this case, there is an increase in Qtto 199 bfpd and pump efficiency from 67% to 80%,While the results of the optimization in table 6 in theBM2 well by changing the SPM and SL parameterson the installed pump with N 8 SPM and SL 100 in, Qtis 284 bfpd, then converted to N 10 SPM and SL 110,there is an increase in Qt to 583 bfpd pump efficiencyfrom 65% to 90%.

After obtaining the optimum production flow rate,to determine the bottom well flow pressure (Pwf) inBM1 and BM2 wells is by plotting the productionflow rate on the IPR curve in each well, the resultsare shown in the figures 5 and 6.

Based on the results of plotting the IPR curves inFigures 3 and 4 to determine the bottom well flowpressure (Pwf) with the optimal production flow (Qt)the results in table 7 on well BM1 with Qt 182 bfpd

Figure 5: IPR curve determination of Pwf against Qt beforeand after optimization in BM 1 wells.

Figure 6: IPR curve determination of Pwf against Qt beforeand after optimization in BM 2 wells.

obtained pwf 30 psi while the BM2 wells with Qt583 bfpd obtained pwf 19 psi. Based on the resultsof increasing production flow rates in BM1 and BM2wells, the next step is to forecast with Decline Curveto find out when the production performance will bein the future.

3.4 Decline Curve Analysis (DCA)Forecasting

After optimizing and obtaining a new oil productionflow rate. Then it is necessary to do economiccalculations at the new flow rate to find out what theprofits are (Hong et al., 2018; John, 1996).

At the new production flow rate, it is predictedthat the production rate will decline in the future.Decreasing the rate of production is seen by using

Table 7: Results of PWF by plotting the optimal IPR curveagainst Qt.

WellQt Pwf Qt Pwf

Qmax, BfpdBeforeoptimization bfpd

Beforeoptimization psi

Afteroptimization bfpd

Afteroptimization psi

BM1 144 78 199 30 216BM2 284 41 583 19 696


105

Fekete software. Production history data on BM1and BM2 wells are input to Fekete and exponentialdecline types are chosen. The selection of exponentialtypes is seen from the production history in the last 4years. Decline obtained on BM1 wells is 11% / yearand BM2 is 17% / year. Then assuming the watercut does not change and decreasing the productionrate of each well can be known. After that, economiccalculations were carried out on two wells after beingoptimized for BM1 and BM2 wells.

Declining forecasting for production is carried outfor the next 2 years, from March 2017 to March 2019.The reason why the next 2 years are adjusted to therental period of the pump from the company withthe contractor, which is per 2 years leasing. Basedon the results total production for the next 2 yearsincreased after the optimization of pumps in BM1wells in the first year of 31121.2 bbl and the secondyear 29663.4 bbl for 2 years and in the first year BM2wells 42418.35 bbl and the second year 35501.7 bblfor 2 years. Optimization is needed to get greaterprofits.

Table 8: The results of total production forecasting in thenext 2 years.

DATEWellBM1

WellBM2

(BBL/Y) (BBL/Y)March 2017 – March2018

31121.2 42418.3

April 2018 – March2019

29663.4 35501.7

Total Production 138.704 BBL

3.5 Economic Analysis

Some economic indicators used to analyze theproduction results of the flow rates for the next 2 yearson the BM1 and BM2 wells in the 6th generation PSC(Production sharing contract) system are: Net PresentValue (NPV); Pay Out Time (POT); Rate of Return(ROR); Discounted Profit to Investment Ratio (DPIR)and Economic sensitivity.

According to (Lubiantara, 2012) FTP or firsttranche petroleum is the Government and thecontractor is entitled to first take 20% of productionbefore deducting returns or recovery of operationalcosts (cost recovery). The DMO is basically thecontractor’s obligation to supply a certain volumeof domestic needs. For the first five years (moreprecisely the first 60 months when production begins,the volume for this DMO is valued at the marketprice of the crude oil, known as the DMO holiday.

After the DMO holiday period, the price of the DMOoil will be discounted as stated in the contract , 10%,15% or 25% of the crude oil market price.

Parameters and Assumptions Used

• Based on the contract model between theContractor and the Government assumptions areused in calculating the production flow rate forthe next 2 years in wells BM1 and BM2Price of1 BBL of US $ 52 / Bbl.

• The Contractor’s portion is 26.7857% (after tax).

• Government portion is 73.2143% (after tax).

• Government tax is determined at 44%.

• FTP = 20%.

• Cost recovery = 100%.

• DMO = 25%.

• DMO fee = 15%.

• Operating costs are considered fixed at US $ 20 /Bbl

• Pump rental costs = US $ 103 / d

Based on Production sharing contract model,investment parameters, calculation assumptions, andincremental production Scenarios, the economicevaluation of the use of the HPU on the BM1 andBM2 wells in the X field was conducted. Completeresults of economic calculations are presented inTable 9.

Based on the calculation and results of table 9,it can be seen that the production for the next 2years on BM 1 and BM 2 wells in accordance withthe HPU rental time is 0.136 MMBBL multipliedby the oil price of US $ 50 / Bbl MMUS $ 7,213.The PSC system can be identified by non-capitalinvestment amounting to MMUS $ 0.150, obtainedNPV contractor MUS $ 451.07, IRR¿ MARR, POT<1 year and DPI 4.00. Based on these results, theoptimization results of production in BM 1 and BM 2wells for the next 2 years are still very economical toproduce.

3.6 Sensitivity Analysis

Sensitivity analysis on the NPV of the contractoris used to see what parameters affect NPV. Theparameters used are: a) Oil prices; b) Production costand c) Production results.

Based on the Tables 10, 11, 12 above, a plot iscarried out on the curve to see which parameters affectNPV.


106

Table 9: Summary of Calculation Results The Economics of BM1 and BM2 wells.

No. Parameter Unit Total1 Oil Production MMBBL 0.1392 Time oil production Year 23 Price (Bbl) US$/Bbl 524 Gross Revenue MMUS$ 7.213

5

FTP MMUS$ 1.443Contractor FTP MMUS$ 0.386

Government FTP MMUS$ 1.056

6

Investment MMUS$ 0.150Tangible MMUS$ 0.000

Intangible MMUS$ 0.150

7Operating cost Operation MMUS$ 2.774

Abandonment MMUS$ -

8

Cost Recovery MMUS$ 2.924(% Gross Revenue) % 41%

Unrecovered Cost -(% Gross Revenue) % 0%

9 Investment Credit (IC) 10% MMUS$ -

10

Equity to be Split MMUS$ 2.846Contractor Equity MMUS$ 0.762GovernmentEquity

MMUS$ 2.083

11

Contractor TakeNet Cash Flow MMUS$ 0.553

(% Gross Revenue) % 8%IRR % ¿ MARR

NPV @15% MUS$ 451.07POT Year ¡ 1

12

DPI Fraction 4.00Government Take

FTP + Equity MMUS$ 3.140Tax MMUS$ 0.434

Net Cash Flow MMUS$ 3.736(% Gross Revenue) % 52%

NPV @10% MUS$ 3,05

Table 10: Sensitivity analysis to oil prices

Sensitivity(%)

Oilprice(US$)

NPV atDiscountfactor 15%(US$)

80 41 296.0190 46 380.59

100 52 451.07110 57 521.55120 62 592.03

4 CONCLUSIONS

Optimization of installed pumps by changing SL andSPM on BM1 wells from N = 6 and SL = 100 to

Table 11: Sensitivity analysis to operational costs.

Sensitivity(%)

Oilprice(US$)

NPV atDiscountfactor 15%(US$)

80 16 504.5790 18 477.82100 20 451.07110 22 424.32120 24 397.97

N = 7 and SL 100 production rates increased from144 BFPD to 199 BFPD with EV = 80% while inwell BM2 from N = 8 and SL = 100 to N = 10


107

Table 12: Sensitivity analysis to production.

Years80% 90% 100% 110% 120%

(Bbl/Y) (Bbl/Y) (Bbl/Y) (Bbl/Y) (Bbl/Y)2017 58830 66190 73540 80890 882502018 52130 58650 65170 71680 78200NPV

357.97 404.52 451.07 497.62 544.17@15%

Figure 7: Sensitivity analysis.

and SL = 110 the production rate increased from284 BFPD to 583 BFPD with EV = 90%. Basedon the results of production optimization for the next2 years according to the time of HPU leasing, oilproduction is 0.139 MMBBL, if it is assumed thatoil prices of US 52/BblareMMUS 7,213. Basedon the revenue sharing using the PSC system withnon-capital investments of MUS $ 0.150, the NPVcontractor MUS $ 451.07, IRR¿ MARR, POT <1year and DPI 4.00 are obtained. From these results,it can be seen for the next 2 years BM 1 and BM 2wells are still economical to produce.

ACKNOWLEDGEMENTS

Thank you very much for supported by UniversitasIslam Riau and BOB PT. BSP Pertamina Hulu.

REFERENCES

Babbitt, J. A. and Vincent, K. (2012). Hydraulic PumpingUnits Proving Very Successful in Deliquifying GasWells in East Texas. SPE Annual TechnicalConference and Exhibition.

Beard, D. (2013). Hydraulic pumping units provingvery successful in deliquifying gas wells in EastTexas. Society of Petroleum Engineers - North AfricaTechnical Conference and Exhibition 2013, NATC2013, 2.

Brown, K. E. (1984). The technology of artificial liftmethods, volume 4.

Chase, R. W. and Shaver, C. A. (2009). Optimal use ofvogel’s dimensionless ipr curve to predict current andfuture inflow performance of oil wells. SPE EasternRegional Meeting, 295(5).

Cui, J., Xiao, W., Feng, H., Dong, W., Zhang, Y., and Wang,Z. (2014). Long Stroke Pumping Unit Driven byLow-Speed Permanent Magnet Synchronous Motor.SPE Middle East Artificial Lift Conference andExhibition.

Hong, A., Bratvold, R. B., Lake, L. W., Maraggi,R., and M., L. (2018). Integrating modeluncertainty in probabilistic decline curve analysisfor unconventional oil production forecasting.SPE/AAPG/SEG Unconventional ResourcesTechnology Conference 2018, URTC 2018, (October2018), 23–25.

Jennings, J. W. et al. (1989). The design of sucker rodpump systems. In SPE Centennial Symposium at NewMexico Tech. Society of Petroleum Engineers.

John, L. (1996). Decline Curve Analysis for Gas Wells.Texas A&M University, College Station Texas.

Lubiantara, B. (2012). Ekonomi Migas Tinjauan AspekKomersial Kontrak Migas. Grasindo.

Ogunleye, A. O. (2012). Development of a Vogel type InflowPerformance Relationship (IPR) for Horizontal wells.SPE Annual Technical Conference and Exhibition.

Pickford, K. H. and Morris, B. J. (1989). Hydraulic rodpumping units in offshore artificial lift applications.SPE Production Engineering.

Wang, D. F., Cui, X. M., Gao, G. Y., Huang, Z. Z., and Hu,B. Z. (1995). A New Long Stroke Pumping Unit withHigh Speed. SPE Production Operations Symposium.

Wiggins, M. L., Russell, J. E., Jennings, J. W., et al.(1996). Analytical development of vogel-typeinflow performance relationships. SPE Journal,1(04):355–362.

Ye, Q., Wang, F., Wang, Y., Zhu, Y., Xu, J., Li, X.,and Yang, G. (2017). Development and applicationof pulley-free directly-connected hydraulic pumpingunit. Society of Petroleum Engineers - SPE/IATMIAsia Pacific Oil and Gas Conference and Exhibition2017.


108

Construction Design and Performance of Dry Leaf Shredder withVertical Rotation for Compost Fertilizer

SyawaldiDepartment of Mechanical Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

[email protected]

Keywords: Machine, Leaf , Crusher, disposal

Abstract: One of the large private universities (PTS) in Riau Province is known as Universitas Islam Riau (UIR). UIRis a large university and has extensive land infrastructure that is planted with a variety of green plants suchas trees and flowers. These trees have encountered many problems, namely producing leaf litter and causingproblems. Lots of leaf litter is collected and disposed of at the final disposal site. Some can be processedinto compost manually and some are burned. In the composting process, the processing time is too long, so itis necessary to design a construction machine for crushing dry leaves. This machine consists of an inlet andoutlet, a tube made of drums, a five-level shredder and with an electric motor. From the results of the design ofthe construction size length 60 cm width 60 cm and height 100 cm made of angle iron L profile size 40 x 40 x4 cm with a power of 1

2 HP and 1400 rpm motor drive rotation. From the results of engine performance tests,the production capacity of 40 kg/hr in the form of final process chips size of 5-10 mm and 92% efficiency.From the results of this machine design can accelerate the process of making compost and can be used bystudents in developing the entrepreneurship unit of the Faculty of Engineering students.

1 INTRODUCTION

One of the private Universitas Islam Riau (UIR). UIRis the oldest university in Riau Province. In addition,the university has large land and green land. So thatmany found in the rubbish foliage. This garbage is aproblem that is collected every day by campus clean-liness. This the garbage is disposed of at the finaldisposal site. Some can be processed into fertilizermanually and some are burned. So the waste has notbeen used much for the more efficient once such ascompost.

The use of waste from leaves can be used as com-post, known as leaf compost. This can be a good andcreative solution so that the campus becomes clean,it also empowers the community and students to be-come Student Entrepreneurship Enterprises. (Setyan-ingsih et al., 2017).

As for organic waste such as fallen leaves, wastefrom agricultural residues, garbage from kitchen veg-etables, and other types of organic waste. Can be pro-cessed by the community itself into compost, whichwill certainly provide more benefits to the commu-nity and students (Nasution et al., 2013; Yamin et al.,2008). One of the processing must use technologyto speed up work. This technology has also been and

many are made in the form of chopped /flake. Besidestechnology also helps the composting process (Hande& Deshpande, 2014; Kumar & Kumar, 2015).

In managing traditionally destroying leaves andorganic waste by the community, there are those whodo it by manually storing up the tones. Traditionalmanagement requires large labor and long time. Thedesign of a leaf chopper in increasing the business ofmaking compost. The special garbage shredder forthe leaves has not been sold in the market. Existingmachines are made in multi-use so that the price ofthe machine is quite expensive. In addition, the re-search into the manufacture of dry leaf shredder hasbeen carefully studied by several researchers (Handeet al., 2015). In addition, research on the manufactureof dry leaf shredder has been studied thoroughly byseveral researchers (Nithyananth et al., 2014).

The purpose of this study is to design a shredderto form flakes / fine grains to facilitate and speed upthe process of making compost. Besides that, fromthe design results in the form of leaf crusher in or-der to build a compost processing center in the En-trepreneurship Unit of the Faculty of Engineering,Universitas Islam Riau.

SyawaldiConstruction Design and Performance of Dry Leaf Shredder with Vertical Rotation for Compost Fertilizer.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 109-113ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

109

2 LITERATURE REVIEW

Garbage from the campus field or yard is generallyrubbish from leaves (organic waste). Where waste ismanaged properly will get high benefits. Waste fromleaves is very good to be used as compost fertilizer.Compost will be able to fertilize the agricultural areain the form of land acquisition (Budihardjo, 2006;Sulistyorini, 2005).

The leave are of the leaves are burned by the com-munity, which also causes air pollution. The man-agement of these leaves if done properly through anappropriate process will have a positive impact in theform of compost (Nasution et al., 2013; Setyaningsihet al., 2017). The management process is by con-structing a technology to destroy leaves. The resultsof the work process of the machine depends on theresults of the design (Nwakaire et al., 2011). Muchresearch has been done on the design and construc-tion of machinery related to demolition (Hassan et al.,2009). In the process of crushing the engine compo-nents are needed to produce power.(Nwakaire et al.,2011). Power can be determined by the followingequation:

Power,P = work done/second

= work done/time

= (Force x distance)/time

= Force x velocity

P = F.V (1)

Where, P = Power (Nms−1), F = Force of crushing(N), and Velocity is , V = r.ω (m/s).

Force required to thresh the leaf is given by

F = m.ω2.r (2)

Where F is the force needed to chop leaves in con-tainers, m is the mass of the chopper, ω the angularvelocity on the shaft with equation 2.π. N / 60, wheren is the round per minute. Power on the shaft can beF.ω.r. For the motor drive, the electric motor is de-termined based on the power contained in the shaft.(Suga et al., 2004). The relation of the pulley to theone driven through the driving force is:

N1D1 = N2D2 (3)

Where N1 is the driving speed, the driven N2speed, D1 the drive pulley diameter and D2 are thedriven pulley diameters. The mass weight (m) of pul-leys in the shaft can be determined,

m = ρv (4)

where ρ pulle density and v are pulley volume.Pulley weight,

W p = ρ× (π.d2/4)× lp (5)

Where d is the pulley diameter and lp pulley length.If the pull on the pull side and the slack side of thepulley are F1 and F2 respectively, then the magnitudeof the tensile is effective (Fe),

Fe = F1 −F2 (6)

Ts p (torque on the shaft) is:

Tsp = F × r (7)

where F force works counting leaves, this is thesame as torque (Ts) in the system.

Ts = F × r (8)

Where Tm (motor torque) = F × rwhere

Ts = Tm (9)

Power required,

Pm = ω.Tm (10)

Tensile is effective Fe is

Fe = Pm/(ω.r) (11)

MT (torque moment) = (F1 −F2) r1. The powertransferred to the belt is:

P = (F1 −F2).V (12)

Where, V (Velocity)

V = (π.D.n)/60 (13)

Also

F1/F2 = exp(µ θ) (14)

Where θ the contact angle of the belt on the driv-ing pulley groove, and µ is the real friction coefficientbetween the belt and pulley, the dry surface µ = 0.3.The magnitude of the contact angle on the drive beltis ;

θ = 180− (57(D1 −D2)/C) (15)

Determining the pulley length is as follows,

L = 2C+π/2(D+d)+1/4C(D−d)2 (16)

The minimum diameter of the shaft can be deter-mined:


110

d3 = [(5,1/τa)KtCbT ]1/3 (17)Where d is the shaft diameter, Kt collision correc-

tion factor (1.0) if the load is applied subtly (1.0-1.5)if there are a few surprises and collisions and (1.5-3.0)if the load is subjected to a shock or a large collision.If indeed it is expected that usage will occur with aflexible load, it can be considered the use of the Cbfactor (1.2-2.3). For general use on a shaft with astrength marked with a permit voltage τa are:

τa(kg/mm2) = σB/(S f1xS f2) (18)Where :S f1 (6,0)S f2 (1,3-3,0)is safety factor.The leaf chopping machine is tested to determine

the effectiveness of the equipment performance in itsuse with respect to engine performance. One of theperformance carried out is the production ability ofQT = WT/tT , where WT is the weight of the processand tT is the process work time in units (kg/hr)

3 MATERIALS AND METHODS

3.1 Design Considerations

The method used in the construction design consistsof:• Field survey• Coordination with related institutions and the

cleanliness of the field at Riau Islamic University.• Coordination with student entrepreneurship units.

3.2 Calculating Design

The spin speed of the dry leaf chopper knife is 1866revolution per minute (rpm), with a counter force of13.05 Newton is blades, angular velocity (ω) 195.3radians per second.

3.3 Description of Machine Parts

In the figure 1.1. explained that some machine andconstruction parts of the design.• The Main Frame

The main frame work functions as a buffer forcomponents or machine elements that work. Thiscounter frame is made of structural steel with asize (60 mm x 60 mm x 100 mm) and a right an-gle iron profile (40 mm x 40 mm x 4 mm).

• The HopperThe hopper function is where the channel en-ters the leaves into the drum for the destruc-tion/enumeration process. Where this carriage hasa diameter of 27.5 mm and a height of 25 mmwhich is made of carbon steel while being shapedsheet plate with a thickness of 2 mm. The positionof the design hopper is placed at the top of the tub.

• The ScreenThe Screen located inside serves to filter or sep-arate granules and debris from the results of enu-meration by the chopper knife. The results willcome out through the outlet in fine grains and witha size of 5-10 mm.

• The OutletThe outlet is designed as a place to exit the resultsof the leaves counting. Where the design is madeof steel plate sheets with a size of 2mm thick.

• Shaft DesignShaft is a very important element in machinemovement in moving power and rotation. Usuallyon installed shafts such as gears, pulleys, sprocketand other engine elements. The shaft is madefrom ST 37 Steel with a length of 65 cm and adiameter of 19 mm and is mounted on the middleside of a leaf chopping tool using a bearing. Thebottom and middle end of the bearing is attachedand the upper end of the blade is attached on po-sition vertical.

• The CutterThe knife is a machine element for choppingleaves. The design of this knife is used as manyas 5 (five) levels (as shown in figure 2). The bladematerial is made of steel plate from the spring ofthe vehicle. This knife is connected by weldingand in the middle is given a hole to insert the shaftand locked.

• The Pulley

– Drive Pulley, The drive pulley is enabled tocontinue the 1400 rotation per minute and thepower of the 1

2 HP Electric motor drive. Whereis the size of the pulley diameter of the 75 mmdrive made of aluminum.

– Movable pulleys, The driven pulley is used torotate the shaft to chop leaves of leaves. In thepulley there is a rotation of 1400 rpm to 1866rpm with a diameter of 100 mm and made ofaluminum.

– The Bearings Bearings are the main parts of theengine component. It functions as a rotatingand stationary shaft position. From the results

Construction Design and Performance of Dry Leaf Shredder with Vertical Rotation for Compost Fertilizer

111

Figure 1: Orthographic view Constructions of the machine

of the design the bearing has a hole diameter of19 mm. Where these bearings are mounted onthe bottom of the engine shells.

– The Prime Mover The starting drive functionsto divide the power and rotation to the shaft,which is moved through the pulley. The powerand rotation of the machine are used to cut leafleaves to produce products in the form of finegrains and flakes. The drive used is an Electricmotor with 1

2 hp and 1400 rpm.– The Transmission System The transmission

system on the leaf counter machine consistsof an Electric motor as a driver, drive pulleys,driven pulleys, v-belts and shafts. The aim isto regulate the distribution of power and rota-tion needed in the process of counting leaves.Transmission system as shown in Figure 1.2.

4 DESIGN CALCULATION ANDRESULTS

Machines designed using drives are electric mo-tors with 1

2 HP power and 1400 rpm rotation. Wherethe rotation is changed from 1400 rpm to 1866 rev-olution per minute. The average rotational speed ofthe engine shaft is 1866 rpm, then the results of otherengine components with a shaft size of 19 mm, shaftmass and blade is 2.5 kg, with a length of 65 cm, onthe shaft there are 5 level crushing blades with sizewith crushing force 24,5 N.

Figure 2: Orthographic view Constructions of the machine

5 PERFORMANCE TEST

Based on the results of testing the design of dried fo-liage leaf chopper, the production capacity of 40 kg/ day with flake-shaped size of 5 to 10 mm and effi-ciency of 92% is obtained. In addition there is alsovibration in the construction due to the absence of abalance of force between the contraction and the ro-tating force on the shaft. In addition, the results of theenumeration work process production capacity is stilllow. Based on the results of testing the design of adry leaf chopper machine using 5 levels/10 knives, aproduction capacity of 40 kg/hr in the form of flakesmeasuring 5 to 10 mm and 92% efficiency. This iscompared to a machine that is almost similar to us-ing a chopper as many as 40 knives (Akbar, 2015).Besides that, the corn thresher can efficient of 79.3%(Chuan-udom et al., 2013).

6 CONCLUSION

From the results above, the design of the dried foliageleaf enumeration machine has been successfully madeand tested as the central need of the Student BusinessUnit at the Universitas Islam Riau and the commu-nity of making compost fertilizer. Where this ma-chine is easy to use and carry because it has wheels.In addition, usage can be arranged for approximately


112

8 hours/day. Electricity saving is only 350 watts.

REFERENCES

Akbar, K. (2015). Rancang Bangun Mesin Pencacah Sam-pah Organik (PROSES PEMBUATAN). PhD thesis,Politeknik Negeri Sriwijaya.

Budihardjo, M. A. (2006). Studi potensi pengomposansampah kota sebagai salah satu alternatif pengelolaansampah di tpa dengan mengunakan aktivator em4 (ef-fective microorganism). Jurnal Presipitasi, 1(1), 25–30.

Chuan-udom, S. et al. (2013). Operating factors ofthai threshers affecting corn shelling losses. Songk-lanakarin Journal of Science and Technology, 35(1),63–67.

Hande, A. S. & Deshpande, A. (2014). Methodology fordesign & fabrication of portable organic waste chop-ping machine to obtain compost-a review. Interna-tional Journal for Innovative Research in Science &Technology, 1(7), 1–4.

Hande, A. S., Padole, V., Hande, A. S., & Padole, V. (2015).Design & fabrication of portable organic waste chop-ping machine to obtain compost. International Jour-nal, 2, 1–8.

Hassan, A. B., Abolarin, M. S., Olugboji, O. A., Ugwuoke,I. C., et al. (2009). The design and construction ofmaize threshing machine. Au JT, 12(3), 199–206.

Kumar, I. S. & Kumar, H. (2015). Design and developmentof agricultural waste shredder machine. InternationalJournal of Innovative Science, Engineering & Tech-nology, 2(10), 164–172.

Nasution, F. J., Mawarni, L., & Meiriani, M. (2013). Ap-likasi pupuk organik padat dan cair dari kulit pisangkepok untuk pertumbuhan dan produksi sawi (brassicajuncea l.). AGROEKOTEKNOLOGI, 2(3).

Nithyananth, S., Samuel, L., Mathew, N., & Suraj, S.(2014). Design of waste shredder machine. Interna-tional Journal of Engineering Research and Applica-tions, 4, 487–491.

Nwakaire, J., Ugwuishiwu, B., & Ohagwu, C. (2011).Design, construction, and performance analysis of amaize thresher for rural dweller. Nigerian Journal ofTechnology, 30(2), 49–54.

Setyaningsih, E., Astuti, D. S., & Astuti, R. (2017). Kom-pos daun solusi kreatif pengendali limbah. Bioeksper-imen: Jurnal Penelitian Biologi, 3(2), 45–51.

Suga, K.-S., Perencanaan, D., & Mesin, P. E. (2004). Ptpradnyaparamita.

Sulistyorini, L. (2005). Pengelolaan sampah dengan caramenjadikannya kompos. Jurnal Kesehatan Lingkun-gan, 2(1).

Yamin, M., Satyadarma, D., & Naipospos, P. (2008). Peran-cangan mesin pencacah sampah type crusher. In Pro-ceeding, Seminar Ilmiah Nasional Komputer dan Sis-tem Intelijen (KOMMIT 2008): Gunadarma Univer-sity.

Construction Design and Performance of Dry Leaf Shredder with Vertical Rotation for Compost Fertilizer

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The Impact of Additively Coal Fly Ash toward Compressive Strengthand Shear Bond Strength in Drilling Cement G Class

Novrianti, Dori Winaldi and Muhammad Ridho EfrasDepartment of Petroleum Engineering , Universitas Islam Riau, Pekanbaru, [email protected], [email protected], [email protected]

Keywords: Fly Ash, Pozzolan, Compressive Strength, Shear Bond Strength, Hydraulic Press.

Abstract: The successful of cementing process in petroleum is indicated by the strength value consisting of the compres-sive stress value and the shear bond strength value. The value of compressive strength permitted in drillingis 500 psi while for shear bond strength is 100 psi. To increase the strength of cement is done by addingpozzolanic additives. One alternative pozzolan that can be used and derived from inorganic waste is coal flyash. Indonesia has reserves of around 38.9 billion tons of coal with annual production reaching 435 milliontons, resulting in a large amount of coal fly ash. The silica contained in coal fly ash is pozzolan which canincrease the strength of cement and can reduce costs because it does not need to use additives from industryand can also reduce environmental pollution from fly ash. This study was conducted to determine the value ofcompressive strength and shear bond strength by using coal fly ash additives with variations in concentrationsof 2.5%, 5%, 7.5%, 10%, 12.5% and 15% by weight of cement (BWOC). Making cement suspension samplesis done by mixing water, bentonite, polypropylene glycol, CaCl2, and coal fly ash softens the mixer, then it ispoured in a mold and left in the water bath. The residence is carried out for 24 hours with temperature 600C.Compressive strength and shear bond strength test can be done by utilizing hydraulic pressure. The additionof coal ash can increase the strength of cement. The optimal compressive strength and shear bond strength isobtained on 7.5% BWOC additively ash coal with the value of compressive strength obtained is 1680.39 psiand the shear bond strength is 138.88 psi.

1 INTRODUCTION

Coal is one of the energy sources in Indonesia withestimated reserves of 38.9 billion tons (Suwandi andSuyartono, 2001) Coal is used as a steam power plant(SPP). Coal burning in SPP on the one hand providesbenefits for energy availability but on the other handcan have a negative impact because it causes pollu-tants that can pollute the environment and the healthimpacts of the population (Finahari et al., 2007).

Burning coal from the boiler will produce wastein the form of fly ash and bottom ash (Suarnita,2011). It contains silica which can increase thestrength of drilling cement which consists of com-pressive strength and shear bond structure, where thestrength of drilling cement is very influential on thesuccess of oil and gas well drilling operations.

Compressive strength is the strength for handlingthe pressures from the formation and casing, whilethe shear bond strength is the strength for holdingthe weight of casing (Prasetyo and Lisantono, 2017).Compressive strength withstands pressures in the hor-

izontal direction and cement strength shear bonds re-sist pressure from the vertical direction (Samura et al.,2018).

Coal fly ash has pozzolanic properties whichcontain reactive silica which can reduce free lime(Ca(OH)2) (Salain, 2015). The result of this reactionresults in a bond of calcium silica hydrate (C – S – H)which is the nature of cement (Safitri and Djumari,2010).

Utilizing fly ash on cement has been done fre-quently. fly ash is gained by coal-burning and burn-ing palm oil. The use of fly ash varies in number butis usually used ¡25% (Roskos et al., 2011). In addi-tion, fly ash can be used as a substitute for cement forconcrete compressive strength. In research (Erviantoet al., 2016) the optimum compressive strength is ob-tained by 7.5% fly ash.

This research aims to determine the impact of coalfly ash on the strength of drilling cement. It was cho-sen in this study because the amount is widely avail-able and can reduce pollutant waste which can pollutethe environment. This research was also conducted

114Novrianti, Winaldi, D. and Efras, M.The Impact of Additively Coal Fly Ash toward Compressive Strength and Shear Bond Strength in Drilling Cement G Class.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 114-119ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

to determine the composition of optimal coal fly ashwhich will produce the value of compressive stressand shear bond optimum structure.

2 RESEARCH ANDMETHODOLOGY

This research was conducted at the Petroleum Engi-neering Drilling Laboratory of the Islamic Universityof Riau. The first step that must be prepared beforeconducting this research is the preparation of toolsand materials, the main material of this research iscoal fly ash obtained from the SPP Makmur SejahteraWisesa in South Kalimantan.

Fly ash coal contains a chemical composition ofsilica oxide (SiO2) 74.20%, iron oxide ( 2O3) 14.40%and aluminum oxide (AL2O3) 5.70% can be used as amixture of cement since it is pozzolanic. Pozzolanwhich consists of silica and aluminum which reactchemically with calcium hydroxide at ordinary tem-peratures forms compounds that are cementitious orbinding (Dembovska et al., 2017). The chemical com-position of coal fly ash can be seen in the table 1, be-low:

Table 1: Coal Chemical Composition of Fly Ash.

Chemical Composition (%)SiO2 74.20

Al2O3 5.70Fe2O3 14.40CaO 2.40MgO 2.03K2O 0.260a2O 0.06TiO2 0.47P2O5 0.051Mn304 0.160SO3 -

Source: (Haryanti, 2014)

In addition to coal fly ash the materials usedin this study are cement, water, bentonite, Calciumcloride (CaCl2), Polypropolin e Glycol (PPG). Whilethe equipment used is Digital Lead, Constant SpeedMixer, Water Bath Temperature Controller, samplemold and Hydraulic Press.

Fly ash sample preparation refers to ASTM C 117-03 where Fly ash coal is filtered with filter numbers200 mesh (Theodorus et al., 2008). So that when thestirring process can be mixed with other ingredients.Then, the next step is to make cement samples basedon IS : 9013 – 1978 Where in this study the sample

made consisted of basic cement without fly ash andbasic cement using fly ash with concentration 2.5%,5%, 7.5%, 10%, 12.5% and 15% as found in table 2.Cement powder with bentonite additives, CaCl2, andCoal fly ash is mixed in dry conditions, while water ismixed with PPG.

The mixture of water and PPG was stirred in amixture with a speed of 4000 rpm after which the ce-ment mixture was also put into a mixer and stirred ata speed of 1200 rpm for 3 minutes. The sample wasthen poured into a mold and wrapped using aluminumfoil. Compressive Strenght and Shear Bond Strenghtare tested within temperature of 600C.

The equations used to calculate compressivestrength and shear bond strength are as follows:

CS = K ×P(A1A2

)

Where:

CS =Cement Compressive Strength, psiK =Coe f f icient f actor, f unction o f high

comparison (h) toward diameter (d)P = Maximum loading, psi

A1 =Cross section o f block bearing, inch2

A2 = Sur f ace area o f cement samples, inch2

The equation used to calculate Shear bond Strength :

SBS = K ×P(A1

π×D×h)

Where:

SBS = Shear bond strength o f cement, psiK = Factor Coe f f icient, a f unction o f the ratio

o f the height(h) to diameter(d)P = Maximum loading, psi

A1 =Cross section o f block bearing, inch2

d = Inner diameter o f sample casing (cement),inch

Testing of compressive strength and shear bondstrength test is carried out by using hydraulic pressaccording to SNI03-1974-1990 standards.The valuesof compressive strength and shear bond strength thathave obtained were inputted in the minitab of soft-ware to determine correlation and regression analysis.

The Impact of Additively Coal Fly Ash toward Compressive Strength and Shear Bond Strength in Drilling Cement G Class

115

Table 2: Composition of drilling cement samples

No Sample Cement Suspension Compo-sition

1 S0 Cement (C)2 S1 C + 2.5 Coal fly ash3 S2 C + 5 Coal fly ash4 S3 C + 7.5 Coal fly ash5 S4 C + 10 Coal fly ash6 S5 C + 12.5 Coal fly ash7 S6 C + 15 Coal fly ash


3.1 Compressive Strength

Testing of compressive strength on basic cement andcement that added to the concentration of fly ash coalconsisting of concentration 2.5%, 5%, 7.5%, 10%,12.5% and 15% bwoc can be seen in the Table 3 andFigure 1 below:

Table 3: Calculation results of the value of Basic Cementcompressive strength plus coal fly ash

Cement Suspension(CS) Composition

Value CS (psi)

Cement (C) 790.11C + 2.5 Coal fly ash 996.61C + 5 Coal fly ash 1140.11C + 7.5 Coal fly ash 1680.39C + 10 Coal fly ash 960.61C + 12.5 Coal fly ash 703.02C + 15 Coal fly ash 378.00

Figure 1: Value of Compressive Strength

Figure 1 shows coal fly ash affects the compres-sive strength value. Where the composition of coal flyash within the concentration of 2,5%, 5% and 7.5%

increases the value of the compressive drilling cementstructure. However, the addition of fly ashcoal at aconcentration of 10%, 12.5% and 15% causes a de-crease in the value of compressive strength, the opti-mum compressive strength value is obtained within aconcentration of 7.5% is the concentration that pro-duces.

The improvement in the value of compressivestrength in coal fly ash is caused by fly ash beingone of the pozzolanic ingredients (ASTM, 2001). Ac-cording to Salain (Salain, 2015) with the presence ofpozzolanic properties on fly ash containing reactivesilica, it can function to reduce free lime (Ca(OH)2).The result of this reaction results in a bond of cal-cium silica hydrate (C – S – H) which is the natureof cement. With composition C – S – H the rightstrength of cement will increase (Safitri and Djumari,2010). While the decrease in the value of compressivestrength ash coal in concentrations above 10% is dueto imperfect pozzolanic reactions. This is because thehigher the concentration of coal fly ash, the less theamount of cement, so the amount of tricalcium sil-icate (C3S) and dicalcium silicate (C2S) which is acompound that is responsible for the strength of ce-ment decreases and the bonding power does not runperfectly (Munir, 2008). According to Safitri & Dju-mari (Safitri and Djumari, 2010). The addition of alot of coal fly ash will cause many silica elements thatcannot react with calcium. So the bond C – S – Himperfect results in a low grade of cement strength.

3.2 Shear Bond Strength

Shear Bond Strength testing was done on the base ce-ment and cement added with the concentration of flyash coal consisting of the addition of fly ash coal asmuch as 2.5%, 5%, 7.5%, 10%, 12.5% and 15% bwocand the results can be seen in table 4 and figure 2 be-low:

Table 4: Results Calculation of shear bond strength of BasicCement plus coal Fly Ash

Cement SuspensionComposition

Value SBS (psi)

Cement (C) 92.58C + 2.5 Coal fly ash 98.20C + 5 Coal fly ash 112.42C + 7.5 Coal fly ash 138.48C + 10 Coal fly ash 133.95C + 12.5 Coal fly ash 120.09C + 15 Coal fly ash 94.18

In figure 2 shows that the addition of coal fly ashalso affects the value of the drilling cement shear


116

Figure 2: Value of Shear Bond Strength.

bond structure. As the compressive stress test results,the results of the BPD shear test test also show thesame results where the addition of coal fly ash at aconcentration of 2.5%, 5%, and 7.5% increases thedrilling cement shear bond value while increasing theconcentration of coal fly ash with a concentration of10%, 12.5% and 15% cause a decrease in the value ofdrilling cement shear bond structure. Therefore, it canbe concluded that the 7.5% of coal fly ash concentra-tion can produce the optimum shear bond value.

3.3 Regression Analysis andCorrelation between TestParameters against Concentration

3.3.1 Compressive Strength againstConcentration 0-7.5% of Coal Fly Ash

The concentrations used in this study were 0, 2.5%,5%, 7.5%, 10%, 12.5% and 15% coal fly ash. Fromthe concentration testing, regression testing and cor-relation to the results of compressive strength werecarried out. The following are the results of regres-sion analysis and correlation on 0- 7.5% of coal flyash concentrations against compressive strength.

Judging from the software output above in theanalysis of variance, the p-value is 0.045, whichmeans that it is smaller than the value of the signifi-cant criteria used by the evidence level of 95% so thatthe α value is 5% or 0.05. In the probability value ap-proach (p-value) if the value of probability (p-value)is smaller or equal to the level of significance (α) thenthe zero hypothesis is accepted. But if the probabilityvalue is greater than the significance level, the zerohypothesis is rejected (Gio et al., 2016). Value of p-value is 0.045 which means smaller than the signifi-

Figure 3: Fitted Line Plot Versus Compressive StrengthConcentration.

Figure 4: Regression Analysis compressive strength versusconcentration.

cance value (α) which means that the linear regressionmodel meets the linearity criteria.

Value of R-sq (adj) obtained is 86.7% whichmeans that the compressive strength variable can beexplained by 86.7% by the concentration variable.The remaining 14.3% is explained by other variablesother than concentration. The equation obtained iscompressive strength = 729.7 + 112.6 concentrationmeans that an increase of 1 concentration has a posi-tive effect on compressive strength of 112.6.

3.3.2 Shear Bond Strength againstConcentrations of 0- 7.5% Coal Fly Ash

The following are the results of regression analysisand correlation on concentrations of 0-7.5% coal flyash against shear bond strength. Judging from thesoftware output above in the analysis of variance, asignificance value or p is obtained which is equal to


117

0.043, which means that it is smaller than the signifi-cant criterion value, which is used a confidence levelof 95% or 0.05. This means that the value of the P-value smaller than 0.05 indicates that the linear re-gression model meets the linearity criteria.

Figure 5: Regression Analysis Shear Bond strength versusconcentration.

Figure 6: Regression Analysis Shear bond strength versusconcentration.

Then get the value of R-sq (adj) 87.3%, whichmeans that the variable shear bond strength can be ex-plained by 87.3% by the concentration variable. Theremaining 13.7% is explained by other variables otherthan concentration. The equation obtained was shearbond strength = 87.62 + 6.056 concentration, mean-ing that the increase in 1 concentration gave a positiveeffect on the shear bond strength which was equal to6.056.

4 CONCLUSIONS

Addition of coal fly ash has an effect on the value ofcompressive strength and shear bond drilling cementstructure. Based on the results of the research thevalue of optimum compressive strength was obtainedat a variation of 7.5% concentration of 1680.39 Psi.The optimum shear bond strength value was also ob-tained at a variation of 7.5% concentration of 138.48Psi. From the results of laboratory tests using Minitabsoftware for concentrations of 0-7.5% coal fly ashthe compressive strength equation = 729.7 + 112.6concentrations was obtained, the correlation value of0.995, P-value 0.045. The value of the linear regres-sion results for shear bond strength with a concen-tration of 0-7.5% found that the shear bond strengthequation = 87.62 + 6.056 concentrations, the correla-tion value of 0.957, P-value 0.043.

ACKNOWLEDGEMENTS

Thank you to the Petroleum Engineering Study Pro-gram drilling laboratory, Faculty of Engineering, theIslamic University of Riau which has provided timeand opportunity to conduct research.

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Dembovska, L., Bajare, D., Pundiene, I., and Vitola, L.(2017). Effect of pozzolanic additives on the strengthdevelopment of high performance concrete. ProcediaEngineering, 172:202–210.

Ervianto, M., Saleh, F., and Prayuda, H. (2016). Kuat tekanbeton mutu tinggi menggunakan bahan tambah abutterbang (fly ash) dan zat adiktif (bestmittel). Sinergi:Jurnal Teknik Mercu Buana, 20(3):199–206.

Finahari, I. N., Salimy, D. H., and Susiati, H. (2007). Gasc02 dan polutan radioaktif dari pltu batubara. JurnalPengembangan Energi Nuklir, 9(1).

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Haryanti, N. H. (2014). Uji abu terbang pltu asam asamsebagai bahan pembuatan bata ringan. Jurnal FisikaFLUX, 11:127–137.

Munir, M. (2008). Pemanfaatan abu batubara (fly ash)untuk hollow block yang bermutu dan aman bagilingkungan. PhD thesis, program Pascasarjana Uni-versitas Diponegoro.


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Prasetyo, A. M. A. and Lisantono, A. (2017). Compressiveand shear bond strength of oil well cement with cal-cium carbonate and silica fume. Jurnal Teknik Sipil,13(4):255–259.

Roskos, C., Cross, D., Berry, M., and Stephens, J. (2011).Identification and verification of self–cementing flyash binders for ‘green’concrete. In proceedings of the2011 world of coal ash (WOCA) conference—May 9–12, 2011 in Denver CO, USA.

Safitri, E. and Djumari, D. (2010). Kajian teknis danekonomis pemanfaatan limbah batu bara (fly ash) padaproduksi paving block. Media Teknik Sipil, 9(1):36–39.

Salain, I. m. A. K. (2015). Perekat Berupa Campuran Se-men Portland Tipe I. Prosiding Seminar NasionalTeknik Sipil 1 (SeNaTS 1), 1(April):113–118.

Samura, L. et al. (2018). Pengujian compressive strengthdan thickening time pada semen pemboran kelas gdengan penambahan additif retader. Petro, 6(2):49–54.

Suarnita, I. W. (2011). Kuat tekan beton dengan aditif flyash ex. pltu mpanau tavaeli. SMARTek, 9(1).

Suwandi and Suyartono (2001). Hidup dengan batubara(dari kebijakan hingga pemanfaatan).

Theodorus, A., Sugeng, B., Suratman, I., and Hermawan,R. (2008). Kajian efektifitas semen dan fly ash dalamcampuran soil cement memakai tanah lempung danpasir pulau timor. Journal of Civil Engineering,15(2):69–84.


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Impact of Vibration of Piling Hammer on Soil Deformation: Study Casein Highway Construction Section 5 Pekanbaru-Dumai

Firman Syarif1, Husnul Kausarian2 and Dewandra Bagus Eka Putra2

1Civil Engineering Department, Universitas Islam Riau, Pekanbaru, Indonesia2Geological Engineering Department, Universitas Islam Riau, Pekanbaru, Indonesia

firmansyarif, husnulkausarian, [email protected]

Keywords: Vibration, Soil Deofrmation, Piling Hammer.

Abstract: In the Pekanbaru-Dumai highway road construction in Section 5 will be built a bridge. The construction ofthe bridge is in the area of PT TGI gas pipeline. The construction of this bridge uses a pile foundation whosepile is carried out using a beating method using a hammer. The diameter of this pile is 60 cm with a hammerweight of 5 tons and a height of fall of 2.5 meters. This work method will produce vibrations that affect thecondition of the gas pipe. One of the aspects that are affected by vibration is the deformation of the soil aroundthe gas pipe. This soil deformation will affect the position of the gas pipe which, if it forms a fairly large slope,may cause gas pipelines to crack. The method used to determine the effect of vibration from the design of thegas pipeline is to use a vibration meter tool. vibration meter is a sensor device that is placed on the stake andon the ground above the gas pipe so that how much vibration and deformation of the soil can be seen. As aresult from the test using vibration meter, it was found that the greater the wave velocity due to the design, thegreater the deformation that occurs on the soil.

1 INTRODUCTION

Pile foundations are the part of a structure used tocarry and transfer the structure load of the buildingto the bearing ground located at some depth belowground surface. The main components of the foun-dation are the pile cap and the piles. Wood, steel andconcrete are the main types of materials used for piles.Piles made from these materials are driven, drilled orjacked into the ground and connected to Pile caps 1

(Muhammad, 2008).In past, theoretical and experimental studies were

undertaken by various investigators to evaluate thevertical load and lateral load carrying capacity of sin-gle and group piles embedded in different soil stra-tum. On pile foundations, structures like Buildings,towers, Bridges, Piers harbour and offshore structureare invariably constructed (Muhammad, 2008).

In the erection process a vibration will occur withthe potential damage to infrastructure and disturb thecomfort of humans around him. Of course the greaterthe vibration caused, the greater the potential dam-age caused. This is compounded with the increasingly

1API 1002 2013 “ Steel Pipeline Crossing Railroad andHighway”

narrow land in urban areas and in certain areas, so thepotential damage that might be caused by the piling ishigher because of it the distance to the object is get-ting closer. For this reason, an analysis will be con-ducted related to propagation vibrations on the groundas well as factors on the ground that affect it so thatvibrations are possible will occur due to predictablepile erection (Fitriyah et al., 2019; HH, 2014).

Rayleigh waves (ground roll) are waves that areknown as surface waves that are generated by a mo-mentary pressure at the ground surface that occurs asa result impact and interference between compressivewaves and shear waves constructively. The movementof particles on the face of the Rayleigh wave consistsof P waves and S waves in the horizontal plane. An-other characteristic of the Rayleigh wave is that itsamplitude decreases exponentially with the depth itgoes through, whereas on the surface the amplitudehardly affects its attenuation, it has a low frequencywith a not-so- sharp spectrum (Santoso, 2017; H., ;Muhammad, 2014).

The vibration wave generated in vibrating com-paction will quickly propagate from near to far on thesurface of ground. The incurred environmental vibra-tion not only generates vibration damage to engineer-ing structures, but also brings unfavorable influences

120Syarif, F., Kausarian, H. and Eka Putra, D.Impact of Vibration of Piling Hammer on Soil Deformation: Study Case in Highway Construction Section 5 Pekanbaru-Dumai.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 120-124ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

on production and the lives of residents around theconstruction site. If enough safety protection mea-sures fail to be taken, the vibrating compaction con-struction may lead to cracking of subgrade retain-ing wall, culvert and bridge abutment, disturb normallife of surrounding residents, affect safe production ofthe neighboring industrial and mining enterprises, anddamage normal use and safety of surrounding build-ings (Chen et al., 2019; Maizir, 2015; Muhammad,2008).

The structural work of the Pekanbaru-Dumaihighway road is designed crossing with the PT TGIpipeline position, the highway road works are con-structed with pile foundations. The vibration causedby the erection felt quite large, so PT TGI was worriedthat there would be an impact on their gas pipeline dueto the work of the pile. Therefore testing was carriedout to determine how big of the impact of the vibra-tion on the PT TGI gas pipeline.

2 LITERATURE REVIEW

2.1 Vibration Test

Ground vibration is seismic movement on the groundcaused by rock blasting, pole erection, traffic, excava-tion, vibration due to compaction etc., which is a formof energy transport through the soil, can damage adja-cent structures when vibrations reach a certain level.Some types of energy released from blasting prop-agate in all directions from explosive holes as seis-mic waves with different frequencies. Energy fromseismic waves is dampened by distance and waveswith the highest frequency being muffled faster. Thismeans that the propagation of the dominant frequencyfrom an explosion is a high frequency in a short dis-tance and a lower frequency at a greater distance 2.

Ground vibration measurements are usually car-ried out at one or several points on the ground. Fortotal analysis, the practice is to measure in three di-rections: vertical, longitudinal and transverse. Usu-ally the vertical component is dominant at shorter dis-tances. Therefore it is usually sufficient to measure inthe vertical direction. For vibration analysis of mea-sured values, vibration phenomena can be recorded asa function of history over time. Then displacement,particle velocity and acceleration can be recorded.The basic rule is that vibration velocity is measured

2Ground Vibration Dalam Kegiatan Blasting Batuan.Viewed in 04 April 2019. http://studi- kelayakan-tambang.blogspot.com/2017/03/groundvibration-dalam-kegiatan.html

on building structures etc. by geophone and accel-eration on computer installations etc (Syahidi, 2017;Sukiman and Yakin, 2017). with an accelerometer.If vibration velocity is measured, acceleration can becalculated and vice versa. The most interesting pa-rameter to pay attention to is the damage structure cri-teria that need to be protected from vibration (HA., ;Santoso, 2017; Sukiman and Yakin, 2017).

2.2 Effect of Ground Vibration onGeological Factors

Soil and rock are porous material with a relativelyrigid base mass. The pores are filled with water or air.Soil is a mass consisting of mineral grains that havefriction and cohesiveness between materials. In ce-mented mineral granular sedimentary rocks togetherwith magma rocks and metamorphous mineral rocksit has crystallized in rock masses which usually con-tain water gaps and joints. In practice it may be diffi-cult to assess accurate propagation velocity of seismicwaves in different soils and rocks seen in Figure 1.

Figure 1: Propagation velocity of seismic waves in differentsoils and rocks 3

Each geological environment has the characteris-tics of each ground vibration that influences the prop-agation of vibration waves. The characteristics ofground vibration depend on the following properties:

• Elastic soil constants (elastic and shearing mod-uli) which determine the wave propagation speed

• The type and depth of the soil that determines thedominant range of frequencies and types of waves

• Soil moisture and groundwater level

• Topography and morphology, which can focus onseismic waves

• Damping characteristics from the soil

Impact of Vibration of Piling Hammer on Soil Deformation: Study Case in Highway Construction Section 5 Pekanbaru-Dumai

121

2.3 Potential Damage Caused ByVibration

When planning a project, where driven piles or sheetpiles are to be used, the design engineer must iden-tify potentially vulnerable structures and installationsin the vicinity of the project site and propose limitingvalues of ground vibrations. As part of this task, therisks must be assessed of vibration damage to struc-tures and vibration-susceptible installations or envi-ronmental aspects affecting occupants of buildings.As the prediction of building damage can be com-plex, theoretical methods have low reliability. How-ever, it is possible to assess the potential damage tobuildings based on statistical observations. This ap-proach is used in codes and standards but is limitedto the specific conditions in the region where the ob-servations were made. Therefore, local building stan-dards should be applied with caution in other regions,where pile driving methods, geological conditions,and building standards may be different.

The damage potential of pile-driving vibrationsdepends on the displacement and the frequency of thevibration. Neither of these two characteristics alonewill damage a structure. Concerning displacement,it is common knowledge that a structure can be uni-formly jacked through several feet without causingdamage. Likewise, with regard to frequency, normalsound, in pa ssing through a wall, can vibrate the wallat high frequencies (several thousand cycles per sec-ond) without causing damage. It is a combinationof displacement (amount of motion) and frequencywhich causes damage. The particle velocity of earth-borne vibration is the best measure of damage poten-tial because it combines displacement and frequencyin the most significant manner. The relation betweenVelocity and Frequency seen in figure 2.

Several investigators have found that particle ve-locities in excess of 4. 0 in. I sec are required tocause plaster cracks in dwellings. Figure 3 shows acomparison of the results of several of the investiga-tions. With appropriate conservatism, the investiga-tors agree that a vibration level of 2. 0 in. /sec (par-ticle velocity) is safe with regard to plaster cracks inresidential-type structures

The effect of ground motion on an engineeredstructure can be computed by commonly used meth-ods in the earthquake engineering field. The structureis considered a lumped mass-spring dashpot system,and its response to a series of impacts can be calcu-lated. Based on observation and experience, it can bestated that ground motion particle velocities below 4.0 in. /sec are well within the safe range for engineerstructures.

Figure 2: Propagation velocity of seismic waves in differentsoils and rocks 4

Figure 3: A comparison of the results of several of the in-vestigations about the effect of particle velocity to structuraldamaged

3 RESEARCH METHOD

This research was conducted with the aim of know-ing how much the vibrational impact on soil defor-mation at the PT TGI gas pipeline location. The re-search locations are STA 78 + 448 Titian Antui Vil-lage, Madau District, Bengkalis Regency - Riau andPipeline: Grissik - Duri Section.

This research was conducted in 3 stages:

1. Initial Investigationthe initial investigation was carried out to lookback on the problems that occurred in the fieldbased on information from the informants. From


122

Figure 4: Research Location on STA 78 + 448 Titian AntuiVillage, Madau District, Bengkalis Regency - Riau

the initials of this investigation, the data is ob-tained in the form of data and current conditionswith visualization of photos and other supportingdata.

2. Soil Investigation

soil investigation is a model of general investiga-tion that must be done in looking at the problemsthat occur in a structure above the ground. Fromthis soil investigation, soil data was obtained re-lated to the physical and mechanical properties ofthe soil.

3. Vibration Test With Vibration Meter

This vibration test equipment consists of threesensors that read vibrations produced by piles of3 directions as seen in figure 4, namely:

(a) 1V vibration is in vertical direction

(b) 2L vibration is in longitudinal direction

(c) 3T vibration is in transversal direction

This sensor is installed on the stake and on the gaspipe. with the aim when the pile works vibration thatoccurs due to erection will be read on the sensor thatworks and is read on a computer device as shown inthe figure 5.

Figure 5: The Direction of The Sensor

Figure 6: The Instalation of The Vibration Meter Sensor


4.1 Soil Investigations Result

From the results of soil investigation, it was foundthat the type of soil at the position of the gas pipewas soft clay with high plasticity.Fine-grained soilsare cohesive soils (Sukiman and Yakin, 2017). Oneof the problems in the geotechnical field is cohesivesoil which is usually soft soil. Soft soil can expand orshrink due to the entry or discharge of water. Givinga load on soft soil, will cause an increase in the volt-age acting on the soil. Additional stress that works onsoft soil will initially be bear by pore water due to the

Impact of Vibration of Piling Hammer on Soil Deformation: Study Case in Highway Construction Section 5 Pekanbaru-Dumai

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Table 1: Result of Vibration Test

Lokasi Pengujian Velocity (mm/s) Displacement/Amplitude (mm)Vertical Longitudinal Tranversal Vertical Longitudinal Tranversal

test 1 4.9017 0.9328 2.6744 0.0869 0.0135 0.0422test 2 2.7704 1.3061 1.6897 0.0374 0.018 0.0229test 3 12.7969 3.6527 12.5259 0.1535 0.02 0.1518test4 14.202 3.8665 15.2374 0.1653 0.0384 0.1759

incompressible nature of water. This will cause ex-cess pore water to arise. This excess pore water willbe dissipated by the release of soil pore water throughthe soil pores, while the additional stress is

Initially the pore is gradually transferred to solidsoil particles. This will result in a reduction in thevolume of the land, resulting in increasing of the de-formation of the soil.

4.2 Vibration Test Result

From the vibration test the results are obtained asshown in Table 1. From the results we can concludeif the velocity of the vibration from piling is high thedeformation of the soil also high, like in the test 1in vertical wave the velocity is 4,9017 mm/s and de-formation is 0,0869mm, in the test 2 the velocity islower than test 1 2.7704 mm/s and the deformationalso lower than test 1 0.0374 mm. this situation hap-pen because the velocity of vibration can produce en-ergy and also force, so the force from the velocity canaffect the soil like a load. If the velocity become highthe deformation of soil also high.

5 CONCLUSIONS

From this research we can conclude : Cohesive soil(clay) has a high deformation because of the mechan-ical aspect of this soil that have pore, initially the poreis gradually transferred to solid soil particles. Thiswill result in a reduction in the volume of the land,resulting in increasing of the deformation of the soil.The higher wave velocity due to the design, the higherdeformation that occurs on the soil.

ACKNOWLEDGEMENTS

I would like to gratitude to my parent whose alwaysmotivate me, also to my wife and children my inspi-ration. Secondly I would like to say thanks to allthe team that help me in this research, PT HKI, PTTONAMA and PT TGI.

REFERENCES

Chen, A., Cheng, F., Wu, D., and Tang, X. (2019). Groundvibration propagation and attenuation of vibratingcompaction. Journal of Vibroengineering, 21(5).

Fitriyah, D., Propika, J., Lestari, L., Istiono, H., Pertiwi,D., and Sekartadji, R. (2019). Pile foundation anal-ysis on high–rise building using finite element-springmethod on sandy clay soil. In IOP Conference Series:Materials Science and Engineering, volume 462, page012045. IOP Publishing.

H., G. et al (2017). Pengaruh Tinggi, Kedalaman Pon-dasi Mesin Jenis Blok Dan Parameter Tanah Berbu-tir Halus Terhadap Amplitudo. e-Jurnal MATRIKSTEKNIK SIPIL/September, 2017/777.

HA., S. (2013), Kajian Analitik Pengaruh Rambatan EnergiGempa Terhadap Perilaku Benturan Gedung, Konfer-ensi Nasional Teknik Sipil 7 (KoNTekS 7) UniversitasSebelas Maret (UNS) - Surakarta.

HH, S. (2014). Measurement of mechanical vibrations inresidential areas due to the construction of the sabo-magelang dam with standard bs 6472-2:2008. JournalInstrumentasi, 38(2).

Maizir (2015). Evaluasi Daya Dukung Tiang PancangBerdasarkan Metode Dinamik. Annual Civil Engi-neering Seminar 2015, Pekanbaru ISBN: 978-979-792-636-6.

Muhammad, H. (2014). et al. Studi Pengaruh Diameter DanPanjang Tiang Pancang Terhadap Amplitudo GetaranPada Perencanaan Pondasi Alternatif Turbin Gas, Jur-nal Teknik POMITS.

Muhammad, R. (2008). Pengaruh getaran pemasangan pon-dasi tiang pancang terhadap lingkungan permukiman.Jurnal Permukiman, 3(1).

Santoso, H. H. (2017). Pengukuran getaran mekanik padadaerah permukiman akibat konstruksi pembangunanbendungan sabo-magelang dengan standard bs6472-2: 2008. Instrumentasi, 38(2):43–52.

Sukiman, N. A. and Yakin, Y. A. (2017). Analisis deformasidan tekanan air pori ekses pada tanah lempung lunakakibat beban timbunan (hal. 1-12). RekaRacana: Jur-nal Teknil Sipil, 3(2):1.

Syahidi (2017). Pengaruh Luas Penampang Pondasi MesinJenis Blok Dan Parameter Tanah Berbutir HalusTerhadap Amplitudo. e-Jurnal MATRIKS TEKNIKSIPIL/Juni 2017/491.


124

Combination Playfair Cipher Algorithm and LSB Steganography forData Text Protection

Apri Siswanto, Sri Wahyuni and Yudhi ArtaDepartment of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia


Keywords: Cryptography, Steganography, Playfair Cipher, Grayscale, Least Significant Bit (LSB).

Abstract: Encryption and steganography are needed to ensure the integrity and confidentiality of data in the process ofsending data on the internet. In this paper, there are two stages to securing the message. The first step isto randomize messages to be sent with Polygram cipher substitution. The second step is to avoid messagesfrom third party suspicions that can be done with the steganography process. The message used in this studyis text. In the cryptographic process, the message in the form of text will be encrypted with the PlayfairCipher method, and then the encrypted message will be carried out in the LSB steganography process ona gray scale 8-bit digital image on a scale of 0-255. This study shows that by using Playfair Cipher andcryptographic Steganography in insertion, encrypted messages will be difficult to return to original messagesby unauthorized parties. The result of this application is that you can insert hidden messages in text form intoPNG format digital image files and can extract hidden messages from the image (stego-image).

1 INTRODUCTION

Encryption is one way to secure data, namely by en-coding the original message (plaintext) into a secretmessage (ciphertext). This security process involvesalgorithms and keys. The encryption key can easilyrestore the plaintext from the ciphertext. Therefore,we need a strong encryption algorithm. With the de-velopment of encoding, people can easily obtain en-cryption keys in various ways (Schneier, 1996).

Therefore the development of cryptographicmethods needs to be extended to use which is notonly limited to encoding in the form of text but alsoin the type of images, audio and video (Soplanitand Bandaria, 2007). There are two techniques usedfor encoding data/images i.e., classical cryptographyand modern cryptography. Encryption using classi-cal cryptography is a method for converting originaldata (plain text) to a secret message (ciphertext) us-ing the same key. While modern cryptography usedtwo keys, one key called a public key that can be pub-lished, while another key called the private key mustbe kept secret (Stinson, 2005).

Playfair Cipher is one of the methods classifiedin classic cryptography. The encryption process usedprocessing in the form of very large blocks. Play-fair treats diagrams in the plaintext as single units andtranslates these units into ciphertext diagrams. The

Playfair algorithm is based on the use of a 5x5 matrixof letters constructed using a keyword. The rules forfilling in this 5x5 matrix are: L to R, top to bottom,first with keyword after duplicate letters have been re-moved, and then with the remain letters, with I/J usedas a single letter (Desai and Rathod, ).

This method is one way to overcome the weak-nesses of other classic cryptographic methods that areeasily guessed because there is a one-on-one corre-spondence between plaintext and ciphertext. Like textmessages in maintaining confidentiality, text mes-sages also require encryption techniques that are assimple as possible but difficult to solve. The pro-cess of securing messages can be done by encryptingmessages into images with certain algorithms. Thisis possible considering a message can be representedin a matrix containing integers (Rahim and Ikhwan,2016).

Furthermore, steganography is the science and artof hiding secret messages in a way so that no one sus-pects the existence of the message. The aim is howto hide the message so that the presence not detectedby third parties to avoid conspicuous suspicions (Mu-nir, 2016). The development of computer capabili-ties, the internet is accompanied by the developmentof digital signal processing, information theory, cryp-tography and steganography has transformed digitalmedia (Siswanto et al., 2018). In this realm digi-

Siswanto, A., Wahyuni, S. and Arta, Y.Combination Playfair Cipher Algorithm and LSB Steganography for Data Text Protection.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 125-129ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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tal steganography has created an atmosphere wherecompanies develop attractive applications, so the evo-lution of this field is guaranteed. One of the earlymethods of discussing digital steganography was putforward (Kurak and McHugh, 1992). They proposeda method which breaks down and adds information atleast significant bits (LSB). They study images at thelower level and insert new information now known asimage-based steganography.

LSB is a technique commonly used in encryp-tion and decryption of confidential information. LSBworks by changing the redundant bits of the cover im-age that have no significant effect on the bits of thesecret message (Pelosi et al., 2018). Figure 1 belowshows the mechanism of the LSB method in 8-bit im-ages by utilizing 4 bits LSB.

Figure 1: LSB Mechanism

In this paper, the Playfair Cipher method imple-mented to encode a text message into a form of animage to maintain secrecy with the increasingly broadcomposition of cybercrime. Then the ciphertext willbe processed with LSB Steganography.

2 RELATED RESEARCH

Hatta, Ardi, and Maharani (2017) researched howto maintain message security when sent via an SMS(Short Message Service) network. The problem inthis study is that someone who carries a message tothe other person wants it can be read-only by the legalperson. Encryption is needed to solve this problemto maintain message confidentiality. The researcherproposed an SMS cryptographic application on anAndroid-based Smart Phone using the Playfair ciphermethod. It can be sent cipher SMS messages and re-ceive encrypted text messages then also can be de-crypted in the receiver side. This application performscryptography in the form of text letters. The key usedis in the way of letters. The results of this study isan Android-based application that can send encryptedSMS messages using the Playfair cipher method so

that the confidentiality of the message can be pro-tected .

Then MU’MI (2017) proposed a cryptographicapplication to counteract the dangers of theft and mes-sage manipulation. The method used is hybrid Play-fair cipher and caesar cipher method and steganogra-phy on message insertion. The Playfair cipher methodis used in the encryption process, followed by theCaesar cipher method. The results of encryptionfrom a combination of the two ways are inserted intothe image (embedding process). Insertion SimulationThe encrypted message is simulated with MATLABas a computing aid. The simulated image is saved inthe bitmap (.bmp) format. The results of this studyindicate that by using a combination of Playfair ci-pher and Caesar cipher in encryption, encrypted mes-sages are increasingly difficult to return to originalmessages by unauthorized parties. Inserting it into theimage makes the observer not aware of the informa-tion embedded in the image that acts as a message.

Furthermore, Simbolon (2016) discussed how tokeep the secret of the student academic transcript.The problem in this study is that someone who sendsa message wants the message to be secure and reachesthe right person. To solve this problem, an encryptionsystem is needed that can maintain the confidentialityof the message by using Playfair cipher cryptographyand LSB steganography technique. A combinationof cryptography and steganography can enhance themessage security. In this study, Playfair ciphers areincluded in the Polygram Cipher. This algorithm en-crypts the alphabet pair (bigram) in the plaintext. Intheir research, they proposed the Playfair matrix tableused is a 6x6 matrix. Steganography used is a spatialdomain method with the Least Significant Bit (LSB)technique which consists of 2 parts, namely LSB Em-bedding Process and LSB Extracting Process. Thisresearch used a quantitative research method. The re-sults obtained from this study are in the form of 8-bitgrayscale bitmap image files per pixel with a scale of0 to 255, or with the binary format. The successful se-cret message is fully returned to the original messagewith the decryption process.

3 RESEARCH METHOD

Playfair Cipher, and LSB Steganography algorithmsare implemented using the PHP programming lan-guage. The encryption process is done step by stepfor each message that will be embedded in variousmedia. The first step is the text message will be en-crypted with the Playfair Cipher method, and then thetext cipher will be steganography on 8-bit grayscale


126

digital images on a scale of 0-255, with the Least Sig-nificant Bit (LSB) method. The encryption process isas shown Figure 2.

Figure 2: Encryption and decryption process

The Playfair cipher pseudo-code algorithm is asfollows :1. A plaintext message is split into pairs of two let-

ters (digraphs). If there is an odd number of let-ters, a Z is added to the last letter

2. The rules of encryption are3. If both the letters are in the same column, take the

letter below each one (going back to the top if atthe bottom)

4. If both letters are in the same row, take the letterto the right of each one (going back to the left ifat the farthest right)

5. If neither of the preceding two rules is true, forma rectangle with the two letters and take the letterson the horizontal opposite corner of the rectangle


The results obtained after the coding implementationwith php like Figure 3. The first process that is doneis the message input, key and original image.

Figure 3: Embedding process

After inputting the message and key, the systemwill proceed with the encryption process. Ciphertextencryption results later Inserted in the image. The laststep is saving the stego image in the database. Thesystem showed the MSE (Mean Square Error) andPNSR (Peak Signal to Noise Ratio) normal results.MSE valued between the original image and the ma-nipulated image. In the case of steganography; MSEis the mean square error value between the originalimage (plain image) with the cipher image. PSNRis usually measured in decibels (dB) (Mohsin et al.,2018). PSNR is used to find out the comparison of thequality of the plain image and cipher image (Challitaand Farhat, 2011). PSNR is defined as:

PSNR = 10log10

(C2 maxMSE

)(1)

To determine the PSNR, the MSE (Mean SquareError) value must first be determined. MSE is definedas (Joshi et al., 2016):

MSE =1

MN

M

∑X=1

N

∑y=1

(Sxy −Cxy)2 (2)

Extraction Menu System Testing The first step isto select the image that was processed previously.Then input the same key during the encryption pro-cess. Can be seen in Figure 4.

After embedding and extraction the next step isthe result of the embedding and extraction processcontained in the data menu can be seen in table 1.

Based on the results from table 1, it shows thatthere is no significant change in the stego image fromplain image that has been inserted a secret message.

Combination Playfair Cipher Algorithm and LSB Steganography for Data Text Protection

127

Figure 4: Extraction processTable 1: MSE and PSNR result

MessagePlainImage

CipherImage

MSE PSNR

IA LANU TAMA

flower1.jpg

flwcipher1.jpg

1.02881e-005

1.4533e+011

SE MOGA BERH ASIL

Flower2.jpg

Flwcipher2.jpg

1.7683e-005

8.46721e+010

PL AYFA IR

Flower3.jpg

Flwcipher3.jpg

1.32681e-005

1.12847e+011

5 CONCLUSIONS

Based on the results of analysis and testing, acombination of Playfair Cipher Cryptography andSteganography with LSB for Text Data Security, sev-eral conclusions can be drawn, i.e.:1. Combination system Cryptography and Steganog-

raphy can help users maintain the confidentialityof a message so that it reaches the rightful person.

2. Can block attacks carried out by cryptanalysts byusing Cryptography and Steganography

3. The results of the program simulation, namely the

initial image before the message is inserted andafter the message is inserted in plain view is diffi-cult to distinguish.

For future research is expected to develop this systemfor mobile devices. Review further about the combi-nation of cryptographic algorithms with methods anddata other than text, such as images, videos or audio.

REFERENCES

Challita, K. and Farhat, H. (2011). Combining steganogra-phy and cryptography: new directions. InternationalJournal on New Computer Architectures and TheirApplications (IJNCAA), 1(1):199–208.

Desai, S. and Rathod, Y. Analysis of cryptography tech-niques.

Hatta, H. R., Ardi, M., and Maharani, S. (2017). Aplikasikriptografi pesan short message service pada smart-phone berbasis android dengan metode playfair ci-pher. Klik-kumpulan jurnal ilmu komputer, 4(1):24–37.

Joshi, K., Yadav, R., and Allwadhi, S. (2016). Psnr andmse based investigation of lsb. Paper presented atthe 2016 International Conference on ComputationalTechniques in Information and Communication Tech-nologies (ICCTICT).

Kurak, C. and McHugh, J. (1992). A cautionary note onimage downgrading. Paper presented at the 1992 Pro-ceedings Eighth Annual Computer Security Applica-tion Conference.

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Combination Playfair Cipher Algorithm and LSB Steganography for Data Text Protection

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Fire Detection System in Peatland Area Using LoRa WANCommunication

Evizal Abdul Kadir1, Hitoshi Irie2, and Sri Listia Rosa1

1Department of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Center for Environmental Remote Sensing (CEReS) Chiba University Chiba, Japan

evizal, [email protected], [email protected]

Keywords: Smart Sensor Node, WSNs, Pollution, River Water.

Abstract: Land and forest fires are one of the threats in a tropical country, especially in Indonesia with forestry land andadditional caused of type of land which peatland that easy to getting fire in the summer season. Currently,many techniques to detect fire hotspot and land fire but some of the technique can not apply in peatland case.This research proposes a new technique that can be applied to this case in Riau province, Indonesia which theland with peat type. Long Range Wide Area Network (LoRa WAN) used in the detection land and forest fire,with advantages of low power and long-range transmission in LoRA WAN very applicable in this detectionof fire with the distance of fore hotspot very far and large of an area. The simulation result shows goodperformance and verification used mathematical modeling to check that the system is working and applicationto implement. The sensors deployed in the area which indicate for a forest fire in the simulated distance todetect the potential of fire then the information sent to the monitoring system in the data center. The proposedLoRa WAN method gives good response and recommended to implement in the peatland area which locatedin Riau Province, Indonesia.

1 INTRODUCTION

The significant emerging and development of tech-nology in wireless network has expressively changedand enhance the natural environment control systemcompared to current methods that use satellite grounddetection methods, such as wireless sensor networks.thread (WSN) (Khajuria and Gupta, 2015). This sys-tem can provide new data for environmental and po-tentially fatal warning applications such as land andforest research and flood detection. The benefits ofground level detection can be divided into three as-pects (Chee-Yee and Kumar, 2003; Boubiche et al.,2018; Jie et al., 2015).

Sensor button; low cost, low power, strong, lowpollution and environmental disturbance; communi-cation; low data rate, remote detection and correctionand errors; Information processing; nodes, microcon-trollers and small operating systems for low powersystems. With the advent of IoT technology and LongRange (LoRa) (Wixted et al., 2016; Lavric and Pe-trariu, 2018; Carvalho et al., 2018), WSN and connec-tivity are becoming more reliable, stronger and faster.With this technology it is possible to develop intelli-gent monitoring systems to detect forest and land fires

(Lee and Ke, 2018; Kadir, 2017; Kadir et al., 2018).Therefore, this research focuses on developing in-

telligent fire detection systems, especially in the peatfield, based on the detection and monitoring of envi-ronmental behavior in terms of temperature, humid-ity and gas. To provide new methods and technolo-gies for detection and surveillance systems that uselow-power wireless data communications with LoRaWAN technology. Sensor integration with LoRaWAN technology affects local communities whereusers have access to real-time database informationat any time.

The method for detecting the surface of the earthwill be used in other regions, regions and regions inIndonesia. This solution is a faster and cheaper al-ternative to obtaining satellite data currently in use,which will certainly benefit social welfare and eco-nomic development. In addition, developing real-time perception will require some support from pol-icy makers to understand how the system works andat the same time to understand the outcome models totake appropriate action.

130Kadir, E., Irie, H. and Rosa, S.Fire Detection System in Peatland Area using LoRa WAN Communication.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 130-134ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

2 LORA WAN DETECTION ANDMONITORING SYSTEM

Detection and monitoring systems are widely used forobjects or parameters that require continuous time.Currently, many types of monitoring systems arebased on the objectives and parameters to be moni-tored. Fire detection and environmental monitoringare carried out in different organizations or organi-zations to verify the current environmental situation.Commonly used technology is the use of satellite datato detect fire points.

This technology has a number of drawbacks andlimitations, including proper fire detection and, insome cases, no possibility of satellite imagery pass-ing through the clouds. The new method proposed inthis system is designed to detect smoke, temperature,particle changes, etc. LoRa sensor. He uses the LoRaWAN, where he is placed in a high risk fire area tocollect data. Figure 1 shows a series of hot spots inRiau province.

Figure 1: A map of Riau province with number of firehotspots used satellite images.

That information collect by the sensor is sent tothe sensor gateway as base station to transmit datahave been collect by the monitoring system, becauseof the distance between the sensor and the base stationof the monitoring system. is far enough in some ar-eas. For correct data, a large numbers of WAN LoRasensors are installed in the area because external sen-sors can transmit up to 15 km. In addition to the LoRaWAN sensor, it is mounted on each base station with ahigh-resolution camera to analyze aerial imagery be-fore and after the fire, then train the data to analyzechanges in the image of the environment.

Selected sites likely to cause high forest fires havebeen identified in the peat area as shown in Figure

2, installed systems have been approved by local au-thorities such as the Local Council of Ria and theIndonesian Ministry of Agriculture. Browser. Envi-ronment and Forests. Again, the links between RiauIslamic University and local authorities should be in-tegrated into the decision-making process and facil-itate access to installation, monitoring, data analysisand communication. Improving forest fire monitor-ing with intelligent ground detection and LoRa WANtechnology can be an early indicator for better disas-ter risk reduction decision making. This project ben-efits from new designs and new developments thanksto the latest LoRa WAN technology and research onsignal transmission.

Configuring sensor base stations in different areasto gather information from the WAN LoRA sensornetwork being developed in the peat area. The infor-mation collected by the sensor base station is storedin an internal database and sent to the data center be-cause the sensor base station is located in remote ruralareas for more than 100 km. Sensors can be detectedand alerted immediately before a fire occurs with theresponsible agency for preventive measures. The nextstep will be to configure some sensors and base sta-tions that will cover the entire province of Riau andbuild this project as a prototype system in anotherIndonesian country. The proposed LoRa sensor sce-narios also allow analysis of the behavior and envi-ronment before and after the fire is analyzed througha new image processing method, particle detection,sensor data and system. the media. Data Figure 3shows a proposal to implement a data network schemeto monitor WAN and environmental sensors.

Figure 2: Actual condition of land and forest burn on thefield.

Fire Detection System in Peatland Area using LoRa WAN Communication

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Figure 3: LoRa WAN block diagram for forest fire monitor-ing system.

3 LORA WAN SOLUTION FORPEATLAND MONITORING

The recommended LoRa WAN solution uses a pow-erful LoRa module made by Semtech technology forlong-term transactions. It is a standard of the LoRaalliance that creates mechanisms for formatting, pro-visioning, access agent, message security and protec-tion, and device management. Figure 4 shows theLoR WAN that forms a star topology around the gate-way, which acts as a packet sender between the ter-minal and the core Network Server (NS). The NS isto control for manage the Medium Access Control(MAC) layer for processing and perform as a gate be-tween application that running to the end of devicesand application server. The standard of LoRa WANcan be define in three classes; so the final device canrespond to various scenarios such as network topol-ogy A, B and C (Abeele et al., 2017).

Class A devices often have their own transceiverin deep sleep conditions and rarely wake up to senddata to NS. Wireless media access in the WAN LoRaadheres to the ALOHA method, does not use listeningbefore speaking, and is therefore limited to most partsof the world when used. In Europe, in sample, the 868MHz band contains different subbands, with the CDRbetween 0.1% and 10% and 1% most common (Zainalet al., 2017).

3.1 LoRa WAN Networking

Recent technology for sensing system and networktechnology is introduced by LoRa WAN with capa-bility to send in long distance. Furthermore, the lowpower transmission make power long life and goodfor the maintenance device. As mention in the pre-vious section, the recommended scenario for network

architecture in this WAN loop is a level network ofarchitecture that meets traditional internet standards,such as Internet Protocol version 6 (IPv6). Expectrapid integration of all LoRa WAN systems and sys-tems. One-way nodes of the WAN ecosystem are fastand heavy. However, the transmission capacity of theWAN LoRa technology is very limited, which meansa limited throughput and a small package size. There-fore, it is not easy to integrate an IPv6 datagram di-rectly into LoRa-WAN packages and a compressionmechanism is required. The proposed solution pro-vides an IPv6 connection to the LoRa node usingthe LoRa WAN connection, while a multi-computer(MEC) -based architecture is used to achieve this in-tegration: network access, MEC node, bidirectionalflow can be created between LoRa and LoRa, asshown in FIG. IPv6 is responsible for translating com-pressed or uncompressed packages into network seg-ments. WAN and IPv6 (Sanchez-Iborra et al., 2018).

The proposed solution can contribute to the exten-sive LoRa network, including:

• A true extension of IPR6 in LoRa has been devel-oped and tested.

• LoRa WAN button LoRa is used in bank testing todeliver environmental data via IPv6 links to WANlinks.

• The LoR WAN environment for smart environ-ment detection is configured to be ready for users.

3.2 LoRa WAN Physical Error Model

Physical error is one of parameter have to check, afterchanging the Physical Signal Error Model (PHY), theoutput data is cleared to increase the entropy of thesource. Note that in a small simulation the Bit ErrorRate (BER) information is obtained from a balanceddistribution, and therefore the entropy of the sourceinformation is within the maximum limit. Before thebleached current is sent to the modulator, the modu-lator is mapped. It generates a whole sequence thatis sent to the LoRa WAN sensor button. At the LoRasensor node, the N number of the complex base se-quence sample is changed to N with the time createdby the phase accumulators indicated by (1), where Nis the sample with a base band symbol equivalent to2BF (fs. / BW) . An entire entry determines the timeshift (Abeele et al., 2017).

m(i) =

exp(− jπ), if i = 0m(i−1)exp( j f (i)), if i = 1, . . . ,N−1

(1)where the instantaneous of frequency can write as


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Figure 4: LoRa WAN overview in hierarchical architecture refer to Semtech technology.

Figure 5: The IPv6 Architecture of LoRa WAN networking solution stack.

f (i) is given by

f (i) =−π+iN

2π, for i = 1, . . . ,N−1 (2)

The number of samples in the WAN LoRa symbolwas then sent via Gaussian White Noise (AWGN) fora given SNR parameter

c(i) = m(i)+√

Es2SNR [N (0;1)+ jN (0;1)]

for i = 0, . . . ,N−1(3)

where N (0; 1) is the normal of standard distributionand SNR = 10SNRdB/10. Take note that the energy ineach symbol is one for the LoRa WAN sensor button.Finally, the LoRa WAN decoding uses a demodule-based relationship in decoding in which the receivesymbol as associated with all known LoRa symbols.Symbolic decisions are shown by choosing the LoRicon with the highest correlation value. The valueof correlation physical error to the model of LoRAWAN application in land and forest fire detection can

Fire Detection System in Peatland Area using LoRa WAN Communication

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be write as the number of area going to detect com-pare to the number of sensor nodes in LoRA WANdeploy.

4 CONCLUSIONS

A system for detection of land and forest fire useLoRa WAN technology is proposed. Results showthe simulation and mathematical modeling based oncalculation gives good response and the system ap-plicable to apply for the alert system in the detectionof the forest fire. LoRa WAN system can send in-formation in long-distance over than 10 miles, thusvery applicable in the detection of forest fire in largeof an area. The system can be integrating to the sev-eral sensing systems and collect the information to be-come a group of information to send to the data centerfor monitoring system.

ACKNOWLEDGEMENTS

Authors would like to say thank you very much toKEMENRISTEKDIKTI Indonesia for funding thisresearch and Universitas Islam Riau as well as ChibaUniversity to support the facilities.

REFERENCES

Abeele, F. V. D., Haxhibeqiri, J., Moerman, I., and Hoe-beke, J. (2017). Scalability analysis of large-scale lo-rawan networks in ns-3. IEEE Internet of Things Jour-nal, 4:2186–2198.

Boubiche, D. E., Pathan, A. S. K., Lloret, J., ZHOU, H.,Hong, S., Amin, S. O., and Feki, M. A. (2018). Ad-vanced industrial wireless sensor networks and intelli-gent iot. IEEE Communications Magazine, 56:14–15.

Carvalho, D. F., Depari, A., Ferrari, P., Flammini, A., Ri-naldi, S., and Sisinni, E. (2018). On the feasibilityof mobile sensing and tracking applications based onlpwan. IEEE Sensors Applications Symposium (SAS),pages 1–6.

Chee-Yee, C. and Kumar, S. P. (2003). Sensor networks:evolution, opportunities, and challenges. In Proceed-ings of the IEEE, volume 91, pages 1247–1256.

Jie, L., Ghayvat, H., and MUKHOPADHYAY, S. C. (2015).Introducing intel galileo as a development platform ofsmart sensor: Evolution, opportunities and challenges.In 2015 IEEE 10th Conference on Industrial Electron-ics and Applications (ICIEA), pages 1797–1802.

Kadir, E. A. (2017). A reconfigurable mimo antenna sys-tem for wireless communications. In 2017 4th Inter-national Conference on Electrical Engineering, Com-puter Science and Informatics (EECSI), pages 1–4.

Kadir, E. A., Irie, H., Rahim, S. K. A., Arta, Y., and Rosa,S. L. (2018). Reconfigurable mimo antenna for wire-less communication based on arduino microcontroller.In 2018 IEEE International RF and Microwave Con-ference (RFM), pages 119–122. IEEE.

Kakhandki, A. L., Hublikar, S., and Kumar, P. (2017).An efficient hop selection model to enhance lifetimeof wireless sensor network. In 2017 Innovationsin Power and Advanced Computing Technologies (i-PACT), pages 1–5. IEEE.

Khajuria, R. and Gupta, S. (2015). Energy optimization andlifetime enhancement techniques in wireless sensornetworks: A survey. In International Conference onComputing, Communication and Automation, pages396–402.

Lavric, A. and Petrariu, A. I. (2018). Lorawan communi-cation protocol: The new era of iot. In 2018 Inter-national Conference on Development and ApplicationSystems (DAS), pages 74–77.

Lee, H. C. and Ke, K. H. (2018). Monitoring of large-areaiot sensors using a lora wireless mesh network sys-tem: Design and evaluation. In IEEE Transactions onInstrumentation and Measurement, pages 1–11.

Sanchez-Iborra, R., Sanchez-Gomez, J., Santa, J., Fernan-dez, P. J., and Skarmeta, A. F. (2018). Ipv6 commu-nications over lora for future iov services. In 2018IEEE 4th World Forum on Internet of Things (WF-IoT), pages 92–97.

Wixted, A. J., Kinnaird, P., L. H., Tait, A., Ahmdinia, A.,and Strachan, N. (2016). Evaluation of lora and lo-rawan for wireless sensor networks. In 2016 IEEESENSORS, pages 1–3.

Zainal, N. A. B., H. M. H., Chowdhury, I., and Islam, M. R.(2017). Sensor node clutter distribution in lora lpwan.In 2017 IEEE 4th International Conference on SmartInstrumentation, Measurement and Application (IC-SIMA), pages 1–6.


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Forest Fire Monitoring System using WSNs Technology

Evizal Abdul Kadir1, Sri Listia Rosa1 and Mahmod Othman2

1Department of Informatics Engineering, Faculty of Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Department of Fundamental and Applied Science Universiti Teknologi PETRONAS Seri Iskandar, Perak, 32610, Malaysia

evizal, [email protected], [email protected]

Keywords: WSNs, Forest Fire, Sensors, Detection.

Abstract: Forest fires contribute to air pollution, which is one of the disasters, and adversely affects the environmentbecause foggy particles along with carbon particles in a fire. Forest fires in the dry season occur in most ofIndonesia’s forestry areas. Riau Province is located on the island of Sumatra, Indonesia, in an area with ahigh likelihood of forest fires due to typical peatlands. The purpose of this research is to design and contributeto new technologies for fire detection using Wireless Sensor Networks (WSNs) Technology and intelligentsoftware for accurate fire detection. This study proposes WSNs for the detection of forest fires in peat areasusing sensor nodes with several embedded sensors for accurate fire detection. The sensor node prototype wasdesigned and tested in a laboratory to check results and calibrate it to the real environment. Four sensorsare embedded with temperature and humidity sensors, fire and smoke detection sensors and particle sensors.It analyses with intelligent software to get accurate information and data from the fire, including location,detection of values from all sensors. The results show that WSNs sensor nodes can detect fires and sendinformation about all parameters that indicate forest fires. The design and development of WSN sensor nodesis to assist local governments or institutions to overcome existing problems, particularly in Riau Province andIndonesia, due to forest fires.

1 INTRODUCTION

In Indonesia forest fire is a disaster that incidentmost of every year occur, especially in dry season.According to the data, the total loss because of forestfire in year 1997 is USD2.45 billion (Yulianti et al.,2012), but this loss of data still less than compareto previous year in 1995, the total loss is USD19.1billion. Riau Province in Sumatera is one of the areaswith the greatest risk of suffering from this disasterdue to peat and types of flammable soil. Accordingto government agencies, the total loss in economic inyear 2016 for Riau province was due to forest firesof up to US $ 1,650 million. Apart from economiclosses, most activities stopped due to bad environment(fog) and the closure of all schools, and there were noactivities in government offices and other institutions.The forest fire impact applies is not only to Indonesiaor the Riau province, but also to other countries, suchas Singapore and Malaysia, because Riau directlylimits these countries. The satellite uses currentprocedures to obtain data on forest fires to identifycritical points, then the information collected is sentto the authorities and the team goes to a place to

take the steps needed to stop the fire; Because peatswamps can have their own fires in the area, they mustsocialize and campaign.

In this research focuses on development ofintelligent on the surface and level monitoringsystems for detection forest fires, WSN smartsensor nodes with new designs and smart systemsto collect accurate fire data. The integration ofWSN sensor nodes and information exchange willbenefit local communities and to local authoritiesto access the information through sophisticatedreal-time databases. He hopes this will be a fastand cheap solution then obtaining ordinary satellitedata, and this will certainly benefit to community andeconomic enhancement. Furthermore, developmentof a real-time monitoring system will involve thebacking of the government as the person responsiblefor policy formation to apprehend how does thesystem run and at the same time understand thebehavior of the results to take appropriate steps.

Kadir, E., Rosa, S. and Othman, M.Forest Fire Monitoring System using WSNs Technology.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 135-139ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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2 RELATED WORKS

WSNs applied for many uses, for exampleapplications in remote environments, automaticindustrial control, remote sensing and targets.Applications that are similar to environmentalmonitoring systems for forest fire detection arecapable of real time monitoring and detection. Inmost scenarios, WSNs consists of several smallnumber of nodes where the nodes are placed in farlocation and unreachable hostile locations or in largegeographical areas. A number of WSNs nodes todetect the changes in the environment and provideinformation to the master cluster node or sensor basestation, then through the gate and for data transferto the server, which should be easily maintained andscaled (Kadir et al., 2019; Kadir et al., 2018a).

A new method for action in the forest firemonitoring and detection as elaborate in (Liu et al.,2018) is using data aggregation in WSNs. Theproposed method can be providing a faster andmore effective reaction to forest fires by consumingvalidated WSNs energy that is confirmed in largenumber of experiments in simulation. WSNs candeliver better solutions for managing disaster andoperations rescue, such as alarm systems, flooddetection, earthquake detection, forest fire detection,and landslide detection, water level sensors used tomeasure various parameters. and discussed in (Pantet al., 2017; Aranzazu-Suescun and Cardei, 2017).

Several research on WSNs as discuss in (Kadiret al., 2018b), The WSN simulation addresses keydesign issue, such as the monitored area related tothe sensor’s initial position, the number of sensorrequired for a particular application and changes incoverage over time. WSN uses an algorithm toidentify the injection of malicious data and providemeasures that are unaffected to various sensor andeven when they are hide in attack. The methodologyfor applying this algorithm in this different contextsand also evaluation of results in three different datasets from different WSN distributions. (Illiano andLupu, 2015; Kadir et al., 2016).

Another research that already did in thisapplication of WSN in prediction of natural tragediessuch as hail, rainfall, fire etc. WSN is rare and alsostochastic (Kansal et al., 2015). WSN implementationin energy savings reduces delays in data transferand extends network life. The routing agent chain(CCMAR) is used for the adaptive hierarchy ofenergy saving clusters (LEACH) and energy savingcollections in sensor information systems (PEGASIS)(Sasirekha and Swamynathan, 2017).

3 WSN IN FOREST FIREDETECTION ANALYSIS

Some of the fictitious satellite forest fires observed inRiau province extend to most areas, especially in thesouth. Figure 1 shows the number of critical points inaccordance with the distribution plan distributed in allregions of Riau province.

Figure 1: Number of fire hotspots in Riau Province basedon satellite image.

The access point coverage estimate that a series ofWSNs sensors are installed in a environmental area inRiau province to monitoring this area. The functionof coverage is P given as:

P = f (x,y, t) = (x1,y1), ...(xn,yn),(xk,yk) = f (t),k = 1,2,3, ...,n

(1)

(x, y) is the sensor coordinates in the area ofmonitored and t is the time. This model uses 2Dspatial projection from the fire control area, 3Dsphere. In this issue, the networks do not move exceptthe WSN cellular sensor, but the position of the sensordepends on time, because the sensor node must stopworking from time to time. There may be differentreasons for completing this process: hardware failure,accident, battery consumption and accidental sensorremoval, etc.

Assume that you specify the scope of the IP matrixas a value of scalar that represents of percentage incoverage area observed in a certain time:

IP =area covered with sensors

the total area of the surveillance region100%

(2)The basic component of model can be write in

WSNs as sensor node for defined a vector:

S = (d,E(t)) (3)the area covered can write as d by radio signalsthat exchange data with neighboring nodes when the


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sensor is in the transmission range or transmissionrange. E (t) is the available energy to power thesensor. Assume that there is a homogeneous of sensornetwork to n integrated type sensors concentrators tocommunicate with distribution nodes (Kadir et al.,2019).

The parameters of network can be described in thevector as:

M = (n, f0,∆E) (4)

n can be defining as the number of sensor; fornormal transmission frequencies and the consumptionof energy per transmission and transmission. Assumethat the sensor node period sends to the collected ofdata to adjacent of nodes. Consumption of energy is∆E include the spent energy in data collection andprocess. In each node has 2 parts:

(a) feel the transmission and environmental data.

(b) receives data from the neighboring andforwarding nodes.

The function of WSNs sensor center nodes is tocollects data from each of sensor nodes then sendit to the data coordination center or base station.Data packets received and sent by the coordinatornode, which contains the measurement values andaddress (humidity, temperature, and CO2) of theoriginal sensor node. WSN central nodes haveuninterruptible power supplies and communicationchannels between the central node and the unlimitedcoordination center. Therefore, the simulation regardsthe sensor center as ”always available”. Main purposeof this simulation and measurement is for optimizingthe networks path to send data from the sensors nodeto the hub (Aksamovic et al., 2017).

4 DEVELOPMENT WSN NODEFOR FOREST FIREDETECTION

Forest fire is a natural or man-made events in severalcases throughout the global. Fire areas are foundmajor in climate, then the rainfall is high to providea important amount of vegetation, but in summer veryhot and in dry environments can create hazardousfuel loads. Global of warming will assist to growththe number of importance of this phenomena. Everydry season a forest fire is destroyed not only bythousands of hectares of forest land, but also by publicassets, goods, resources and facilities. In addition,firefighters and civilians face the risk of facing horrificvictims every year. Figure 2 shows a diagram of a

series of WSNs sensor used in the forest area for thedetection purposes of fire.

Figure 2: The sample of topology in the WSNs sensor nodesdeploy in a forest for disaster detection.

Forest fires are a common and active phenomenonthat can change their nature and behavior from oneplace to another and over time. The truth is that insome places there is limited fuel for forests, so firesthat continue to burn must spread to the nearest fuel.The achieved by spreading to the complex heating toneighboring in housing and community obtained fromthe complex behavior of the fire. Another case toapproach is based on the WSNs paradigm designedand developed in a research project involving all keyplayers in the forest and firefighters for operations.

Figure 3: A WSNs sensor nodes propose use ZigBeestandard.

Another scenario in Figure 3 illustrates theproposed schematic structure for multi sensorsnode, controllers, routers, cluster heads, and remoteservers for the application WSNs based systems


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for protection management and forest fire detectionand. Decision making This tree topology networkcluster structure proposes a project to reduce energyloss and data packets during transmission. Thestandard of ZigBee technique is a widely standardbased on IEEE 802.15.4, applicable to low-level PAN(Wireless). ZigBee is one of the wireless networkstandards for low-power sensors that is applied at868/915 MHz and multi-frequency 2.4 GHz. Thetechnical advantage recommended by ZigBee is thatZigBee offers a battery system that is durable, small,and low battery. Cost, automatic or semi-automaticinstallation, and high reliability. Therefore, in thedevelopment and of WSNs node design is used bymultisensory systems to get the most appropriatechoice for the detection and monitoring of forest fires(Kadir, 2017).

The hardware used to detect and monitor firesat WSN nodes is available in many kinds on themarket. Where humidity, smoke, temperature, andcarbon sensors are positioned at the node to detectall parameters that are strongly associated with forestfires. Figure 4 shows the actual formation of thesensor in the environmental parameter calibrationtest, before the sensor node is positioned in thefield, the sensor node must be configured accordingto design and requirements. All nodes send dataor messages to the coordinator WSNs, which hasthe function of receiving all information from thescattered nodes.

Figure 4: A Prototype of WSNs sensor nodes with multiplesensors use Arduino processor.

5 CONCLUSIONS

It has been proposed to develop a WSN node to detectfires and monitor from various sensors for correctdetection. Projects that include mathematical analysisand regional approaches must cover the entire Riauprovince. Sensors of humidity, temperature, smoke,and carbon are the focus of attention in this issueof these parameters are the main parameter forfire conditions both on land and in the forest.Recommended sensor nodes using the low-powerZigBee model, sensor nodes can be used as longbattery-powered nodes. At least in each region,a network coordinator must be formed to coverthe entire Riau province and the gateway must beavailable to hospital the server (cloud database) andmonitor the computer. The highly applicable WSNconcept proposed to detect forest of fires in provinceof Riau is very useful for preparing presentations.

ACKNOWLEDGEMENTS

Authors would like to say thank you very muchto KEMENRISTEKDIKTI Indonesia and UniversitiTeknologi Petronas, Malaysia for funding thisresearch as well as Universitas Islam Riau to supportthe facilities.

REFERENCES

Aksamovic, A., Hebibovic, M., and Boskovic, D. (2017).Forest fire early detection system design utilisingthe wsn simulator. In 2017 XXVI InternationalConference on Information, Communication andAutomation Technologies (ICAT), pages 1–5. IEEE.

Aranzazu-Suescun, C. and Cardei, M. (2017). Distributedalgorithms for event reporting in mobile-sink wsns forinternet of things. Tsinghua Science and Technology,22(4):413–426.

Illiano, V. P. and Lupu, E. C. (2015). Detecting maliciousdata injections in event detection wireless sensornetworks. IEEE Transactions on Network and servicemanagement, 12(3):496–510.

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Kadir, E. A., Rosa, S. L., and Yulianti, A. (2018b).Application of wsns for detection land and forest firein riau province indonesia. In 2018 InternationalConference on Electrical Engineering and ComputerScience (ICECOS), pages 25–28. IEEE.

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Multi Parameter of WSNs Sensor Node for River Water PollutionMonitoring System (Siak River, Riau-Indonesia)

Evizal Abdul Kadir1, Abdul Syukur1, Bahruddin Saad2 and Sri Listia Rosa1

1Department of Informatics Engineering, Faculty of Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Department of Fundamental and Applied Science Universiti Teknologi PETRONAS Seri Iskandar, Perak, 32610, Malaysia

evizal, abdulsyukur, [email protected], [email protected]

Keywords: WSNs, Smart Sensor Node, River Water, Pollution.

Abstract: Indonesia is one of the countries that have many rivers and lakes. It is situated, in South East Asia andenjoys tropical climate all year round. Riau province is located in the centre and middle of Sumatera Islandwhich in the heart of Sumatera. This province has more than five big rivers that are used by the communityevery day for their daily activities. The rapid economic development has significant impact to the regionwhere many industries operating along the river produce industrial wastes that pollutes the river water. Thischapter discusses the development of river water monitoring system where several relevant parameters aremonitored. The Wireless Sensor Networks (WSNs) applied in this research integrates sensor node that isembed to multi sensor consist of temperature, dissolved oxygen (DO), pH, and electrical conductivity. Thesystem for monitoring is specially design for ability to monitor level of river water, river water flow rate forenvironment and flood alert system. WSNs sensor nodes collects information from the multiple sensors andforwards to the WSNs sink nodes which embed to the microcontroller memory and unit as a local databasebefore send the information to the monitoring system. The monitoring system shows the vital informationthat can be monitored by institutions or local authorities. Prompt action will be can be taken if abnormality israised by the monitoring system. A prototype of this WSNs nodes designed and tested and the results showthat sensor nodes are reliable for the detection of polluted water parameters, water levels as well as river flowrate. Furthermore, sensor node was tested at the Siak river located in Riau Province the compare results withactual river water. All the data were keep in the database for recording of analysis and for future developmentof monitoring system.

1 INTRODUCTION

In some countries, especially the developing country,the rivers remain an significant facilities for dailyactivities such as transportation, as floating home,shower, washing, and even for cooking for somepeople. Economics enhancements are boosted bymany companies that operating near by the river forsupport company operation such as transportation andother operation process. In Riau Province has 6rivers and one of the river is the deepest in Indonesia.There are many industries operating around the rivercause severe water pollution and because of thewastes generated and often the unclean environmentaloperations. Polluted water may contain abnormalparameters.

The conventional methods to check river waterquality is testing the sample in laboratory of the riverwater samples. Though this methods, complete range

of laboratory tests including biological, physical, andchemical parameter are possible but not practical tomeasure in many points along the river (Zhuiykov,2012; Lambrou et al., 2012; Aisopou et al., 2012).Additionally, laboratory based tests may need moretimes to a few days to get the result of theample and for some parameter maybe the accuracyresults less than compare to the actual sample ofwater changes during testing. Real-time sensor forenvironment monitoring is start to become populardue to quick advancement in sensing technologies,especially in WSNs that can be adopt in many kindsof applications. The continue collect of river waterquality information and the real observation andmonitoring applied to check the status of the river andecosystem and determine the specifics relationship toevent detection (Li et al., 2018; Cloete et al., 2016;Kadir et al., 2018b).

Water pollutant monitoring done in previous

140Kadir, E., Syukur, A., Saad, B. and Rosa, S.Multi Parameter of WSNs Sensor Node for River Water Pollution Monitoring System (Siak River, Riau-Indonesia).In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 140-145ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

research is limit to several parameters and major ofmonitoring in basic water parameter only parameters(Lambrou et al., 2014; Jinghuan and Yi, 2010; Grossiet al., 2013).Water pollution monitoring systemproposed in (Randhawa et al., 2016; Li et al., 2017;Cheng et al., 2016) used multi sensors but limitedsensor that only cover basic parameter of water whichis temperature and pH, as well as the data keep in localmakes incompatible to online remote monitoring. Theanalysis of water quality using image recognition andby remotely for a long distance monitoring causedaccuracy problems (Dona et al., 2014; Olatinwo andJoubert, 2018). Use of robotics in water pollutantmonitoring in deep rivers and oceans has obviousadvantages but the cost is prohibitive and requiredskilful operators (Teixido et al., 2018; Kadir et al.,2018a).

In this research expected to achieve a newsystem in sensing technology for nodes of WSNssystem that ability to achieve multi parameter ofwater quality at a river in Riau Province, locatedin Indonesia. Furthermore, the real time basedmonitoring, system includes river water level andflowrate sensor, parameters that are vital for floodmanagements during rainy season. In this researchcontributes to new knowledge and offer new designfor river water pollutant monitoring system by datacollection, including a new sensor design that isable to collection accurate data. Proposed a newtechnique of communication from WSNs sensornodes to gateway via WSNs sink for effectivenessin data sharing and transmission is also an importantaim of this research. The use of local and remotedata monitoring, a complete monitoring system ofinterface implement to achieve historical data queries,the real time data and network state to display, dataanalytical and alarm for abnormal situations is madepossible.

2 THE PROPOSED DESIGN OFSENSOR NODES

The proposed new design of sensor nodes in theWSNs for the application in this river water pollutantmonitoring system is based in the analysis and initialsurvey to the field of the actual environmental inSiak river, in Riau Province. In this proposed designseveral sensors applied to achieve detection for all theparameters of the pollutant index and the river water.Figure 1 shows a scenery of the actual conditionof Siak river in Indonesia with activities for thecommunity in daily life such as washing, swimming,fishing and others on the river.

Figure 1: A photograph of Siak river in Riau Province.

The real situation and condition of the river waterand river of Siak River in Riau Province, Indonesiais in dirty condition and poses high risk to theecosystem around the river. Furthermore, people andcommunities use of river water in their daily activitiesis very high risk as well. Figure 3 shows of the actualcondition of river water polluted and contaminated bychemical and material caused by industries operatingaround the river (circle bottom left), some of kidsplaying and swimming in the river as seen in figure 3at top right. Based on these observations and analysisof water, indicator of some parameters in river waterquality is very urgent and required to do a monitoringsystem for example temperature, dissolved oxygen(DO), pH. and electrical conductivity. The monitoringof river water designed as not only for water pollutionmonitoring system, but more than that is to makea sensing node where additional sensors can beapply and added. In addition, water flowrate andlevel measurement is very important as indicator forflooding in the river. Most of rivers located in RiauProvince in Indonesia are at very high risk to theflooding because of high intensity of raining and lowlevel to the sea level. The system for flooding alertis very important for reminding the communities forpreventive action while water level arise and reachin a dangerous level. The smart of sensor node inWSNs consists of four indicators as indicated formeasurement pollutant water and water river statusand alert. The indicator as shows in table 1 thecomplete of indicator measurement with range ofsensors and also for the accuracy.

Table 1: Design Specification of the sensor nodes

Parameter Range Accuracy MethodTemperature 0 to 16 C ± 0.5 C ThermistorDO 0 to 20 mg/L ± 0.5 mg/L PolarographypH 0 to 14 ± 0.1 Glass Electrode

Salinity 0 to 50 % ± 0.5 ConductivityMeasurement

Multi Parameter of WSNs Sensor Node for River Water Pollution Monitoring System (Siak River, Riau-Indonesia)

141

Figure 2: The diagram block of system for smart sensor node in WSNs.

Figure 3: Water polluted by chemicals from an industryoperating along river.

In figure 2 shows a diagram block of the smartsensing node for a WSNs system, the data collectedby the sensor unit will be keeping in a local storageor database, and then all the analyzed data will beforwarded to central database center at the backendsystem.

3 MONITORING SYSTEM OFRIVER WATER POLLUTANT

The typical of WSNs in the possesses of the systemstructure with a new design and novel for the sensornodes, where simply to configure as an arbitrary of theparameter in the multi parameters in the monitoringnetwork. While compare to the conventional of rivermonitor system, it consists in the follow discussion:

• The node of sensor are attach with multi sensingand low in power with individual power inputused solar panel system.

• The parameter of monitoring are flexible; the

network in sensing on the monitoring area isself-organized

• the size of capacity in the network is very bigamount, and the distribution of node can be muchdeeper.

The information shared to the all of communities.A monitor with all the information related to the waterquality installed at the community center or at thepoint of common assembly of community for easy todelivery of information. Furthermore, all the peopleand community can have an access to informationshows including the status of river water levels. Basedon monitoring system then all the information isupdate for public service and knows the status of theriver.

3.1 WSNs System for Water Sensing

A packet of system for sensing complete to all thesensors for detection on how much river water havecontaminate installed at the river side in order toobtain, real data on the river flow. As shows in figure 4illustrate a sensor node that installed on the river sidewith individual power system which is solar panel.The sensor nodes are normally install with distancevery far to the location of monitoring area; thus inthis case power supply from normal public service isnot available. Thus, the solar powered system withbackup battery become very handy.

Large quantity of detection data is collect fromany of sensor system then contribute a large numberquantity, since the sensor nodes has a limited ofstorage data, the large data resulted in low of feedbackwhile sending the data to sink node. Multi sensorswill affected the sensor nodes performance and alsothe speed of response. Thus, a smart sensor nodesproposed to design in obtain quick response in case


142

of abnormal detection on river water monitoringintroduced. Introducing an algorithm for the sensornodes and the filtering of some data gives thesensors node to become smarter in the detection anddetermine of pollution of the river water. Figure4 shows a complete of WSNs sensing system forwater pollutant detection with all the parameters ofpolluted water. The system designed in integrated toall parameters including electrical and power supplywith individual from solar panel system.

Figure 4: A complete system on the river water side withWSNs node installed fort water pollution detection.

3.2 WSNs Sink Node andCommunication System

The common of average distance from the sensornodes is different to the based on early to the datacollection by geographical information and survey ofthe different kind of the river and also the number ofthe industries operated around the river. In addition,communities in the villages and the activity havecontributed to the pollution of river water, to achievemore accurate in data, the average nodes distancemust be install as near as possible to the base station.Figure 5 shows, the scenario of topology of thenetwork for the sensor system with the numbers ofsensor nodes, in every sensor node have their ownsink node to base station for data collecting in alocal host before sending to the station of monitoring.In this case, latest communication technology whichmobile network Fourth Generation (4G used for sinknode as communication to the monitoring station inorder for faster communication as well as real time

monitoring system, as so far most of area is a coverby 4G network in mobile cellular or GPRS data.

Figure 5: Communication of sensor nodes to the sink andbase station system.

4 RESULTS AND DISUCSSION

The simulation results give good response based ontest conducted in the laboratory. Data obtain in thetests use as initial as based parameter before theactual testing conducted and sensor installed. In thisscenario, initial test results very valuable informationin order to conform whether the propose sensornodes as the model is relevant to apply based on thedesign of parameter as set. Several of data werecompared to other sensors data set and literatureas references (Cloete et al., 2016). Result obtainof the temperature sensors as test were compareto conventional measurement which is thermometer(Figure 6).

The parameter of water which pH is another verysignificant indicator to measure the quality of thewater. In this case, the type of sensors uses forsensor nodes built on the glass electrode. The pHsensor design in special specification and precisionas in minimum 0.4 pH. There are two classificationsof test in conduct to observe the precision of theinstalled sensor of pH water. In figure 7 shows a waterpH sensor while test in the between measurement inthe laboratory environment versus to the theoreticalanalysis which obtain based on simulation andmathematical modeling. Both of results gives goodresponse and agreement and in this measurement candefine the pH sensor is working well.

5 CONCLUSIONS

The proposed design of intelligent sensor nodesfor WSNs have been done in multi sensor to domeasurement of all the parameters in the pollutedwater. Initial testing in the laboratory give goodresponse and some of sample test conducted to the


143

Figure 6: Temperature sensor results vs thermometer.

Figure 7: Water pH sensor test between theoretical and actual measurements.

river water, since there are many parameters andchemicals that were involved, thus various sensorssuch as water temperature were used. Water pHparameters that need to monitored and water DO.Measurement shows good result and achievement tocompared to the analysis and theoretical for all thesensor. Thus, the sensor node can be applied andready to be deployed to actual sites.

ACKNOWLEDGEMENTS

Thank you very much to KEMENRISTEKDIKTIIndonesia and Universiti Teknologi Petronas forfunding this research and Universitas Islam Riau tosupport the facilities.

REFERENCES

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Cheng, M., Guo, Z., Dang, H., He, Y., Zhi, G., Chen,J., Zhang, Y., Zhang, W., and Meng, F. (2016).Assessment of the evolution of nitrate deposition

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Cloete, N. A., Malekian, R., and Nair, L. (2016). Design ofsmart sensors for real-time water quality monitoring.IEEE Access, 4:3975–3990.

Dona, C., Sanchez, J. M., Caselles, V., Domınguez, J. A.,and Camacho, A. (2014). Empirical relationshipsfor monitoring water quality of lakes and reservoirsthrough multispectral images. IEEE Journal ofSelected Topics in Applied Earth Observations andRemote Sensing, 7(5):1632–1641.

Grossi, M., Lazzarini, R., Lanzoni, M., Pompei, A.,Matteuzzi, D., and Ricco, B. (2013). A portable sensorwith disposable electrodes for water bacterial qualityassessment. IEEE Sensors Journal, 13(5):1775–1782.

Jinghuan, T. and Yi, W. (2010). A novel waterpollution monitoring approach based on 3s technique.In 2010 International Conference on E-HealthNetworking Digital Ecosystems and Technologies(EDT), volume 1, pages 288–290. IEEE.

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Lambrou, T. P., Panayiotou, C. G., and Anastasiou, C. C.(2012). A low-cost system for real time monitoringand assessment of potable water quality at consumersites. In SENSORS, 2012 IEEE, pages 1–4. IEEE.

Li, L. Y., Jaafar, H., and Ramli, N. H. (2018). Preliminarystudy of water quality monitoring based on wsntechnology. In 2018 International Conference onComputational Approach in Smart Systems Designand Applications (ICASSDA), pages 1–7. IEEE.

Li, T., Xia, M., Chen, J., Zhao, Y., and De Silva, C. (2017).Automated water quality survey and evaluation usingan iot platform with mobile sensor nodes. Sensors,17(8):1735.

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Randhawa, S., Sandha, S. S., and Srivastava, B. (2016).A multi-sensor process for in-situ monitoring ofwater pollution in rivers or lakes for high-resolutionquantitative and qualitative water quality data. In2016 IEEE Intl Conference on Computational Scienceand Engineering (CSE) and IEEE Intl Conferenceon Embedded and Ubiquitous Computing (EUC) and15th Intl Symposium on Distributed Computing andApplications for Business Engineering (DCABES),pages 122–129. IEEE.

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145

Analysis for Gerund Entity Anomalies in Data Modeling

Des Suryani1, Yudhi Arta1 and Erdisna2

1Department of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Department of Information System, Universitas Putra Indonesia, Padang, Indonesia

des.suryani,[email protected], [email protected]

Keywords: Anomaly, Data Redundancy, Data Inconsistency, Gerund Entity, Entity Relationship Diagram.

Abstract: Data is the most important component of an information system development. Collected data that will beused in future needs should be kept well to make it easy to inquire. The data stored in a database consists ofseveral groups of data relations. These relations should be connected through fields which are unique to therelations linked. In designing database itself, it is very important to note how data is organized and stored tominimize data redundancy. The tools used in depiction of the relationship between tables or entities are EntityRelationship Diagram (ERD) that can have one to one, one to many and many to many relationships. Gerundentity will be formed if the relationship between the entities is many to many. However, the new entity is stilla possible anomaly. The reanalysis is needed to be free of anomalies. Gerund entity that still has an anomalywill form a new entity again, which in this case referred to as a sub gerund entity which is a derivative ofa gerund entity. The result of a good database design or free of anomalies will increase the optimization ofmemory usage, consistency and integrity of data.

1 INTRODUCTION

Database is the most important component in the de-velopment of Information Systems because it is aplace to accommodate and organize all data in the sys-tem, so that it can be explored to compile informationin various forms (Sutedjo and Oetomo, 2002). Thedata will be organized in such a way that there is nounnecessary duplication, so that it can be processedor explored quickly and easily to produce the infor-mation needed. From several existing database mod-eling, relational database modeling is still the mostused model by various Database Management Sys-tem (DBMS) software. This is because it is easy tomanage data (Barioni et al., 2011; Stonebraker andMoore, 1995).

Entity Relationship Diagram (ERD) is a modeldiagram that is used as a representation of databasestructure in which table information includes and theexistence of relationships between tables and the formof the relation itself based on existing standard nota-tions (Date, 1977). ERD is used to express the rela-tionship between an entity or object in the form of atable with another entity. In database design, logicallyis done by transforming an ER diagram developedduring conceptual design into a relational databasescheme (Ramakrishnan and Gehrke, 2000; Gehrke

and Ramakrishnan, 2003).Relationships that occur between entities have a

type of relationship: one-to-one (1: 1), one-to-many(1: N) and many-to-many (M: N). Based on the many-to-many relationship, it will form a new entity calledGerund Entity or Associative Entity. But in this case,the gerund entity still allows for irregularities (anoma-lies) in storing data, namely the occurrence of du-plication or waste of data. No writer has found astudy that examines the anomalies in the gerund en-tity yet, so that further analysis needs to be done sothat the database created is really in accordance withthe objectives of the database itself including avoid-ing or minimizing data redundancy, because the wasteof data will result in waste of memory usage andcan cause problems in the process of accessing datasuch as data inconsistency, longer access times andproblems in data integrity (Gehrke and Ramakrish-nan, 2003; Silberschatz et al., 1997).

2 DATA MODELLING

In describing ER diagrams, it takes the existence ofentities, attributes and relationships between entities.Entity is a set of objects in the real world whose ex-istence does not depend on others and has the same

146Suryani, D., Arta, Y. and ErdisnaAnalysis for Gerund Entity Anomalies in Data Modeling.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 146-150ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

property. Examples of objects in an entity that can beuniquely identified are called entity occurrence. Enti-ties can be something real, such as: Members, Films,Office Branch or abstract (concepts), such as: Rental,Registration, Role. (Kadir, 2000)

Transforming or mapping ER diagrams into rela-tions is a mechanical process, in the sense that theprocess has certain regularities. To transform fromthe ER diagram to the relational scheme there are 3(three) entities that need to be understood, namely(Kroenke and Dolan, 1983; Silberschatz et al., 1997):The document margins must be the following:• Ordinary entities (regular entities) are entities that

are independent of their existence and generallydescribe real objects in the real world. Ordinaryentities are often also called strong entities de-picted with four single-striped rectangles.

• Weak entities (week entity) are entities whose ex-istence depends on other entities (usually strongentities). Weak entities are represented by fourdouble-striped rectangles.

• Associative entities (associative entities) orgerund entities are generally formed from many tomany relationships between other entities. Asso-ciative entities are generally represented by rect-angles with parallelograms in them.

Types of relations can be classified as follows:• one-to-one (1: 1)• one-to-many (1: M)• many-to-many (M: N)

Gerund Entity or Associative Entity is formedfrom many to many relationships. Example: Studententity with the subject matter, Customer entity withthe Goods entity and so on.In logical database design, it can be done by:• Applying Normalization to a known table struc-

ture.• Directly create the Entity-Relationship (ER

model) model.Logical data model is a source of physical de-

sign information. This model provides designers witha vehicle for consideration in designing an efficientdatabase.

Physical database design is the process of produc-ing a description of database implementation on sec-ondary storage, describing storage structures and ac-cessing methods to improve access effectiveness. Atthis stage, physical design is intended for a particularDBMS. Physical level database design has been asso-ciated with database management systems and plat-forms where the database is implemented (Connollyand Begg, 2005).

Well-organized data can produce good informa-tion Organizing data to prevent unnecessary duplica-tion. Data that is organized and correlated each othercalled as a database, whereas to manage and orga-nize databases that are built in a system, a databasemanagement is called a database management system(DBMS). DBMS is software that will determine howdata is organized, stored, modified, retrieved, regu-lated data security mechanisms, and mechanisms forsharing data together (Date, 1983).

2.1 Role of Normalization in DatabaseDesign

Normalization is a formal technique that can be usedin database design. The main purpose of normaliza-tion is to identify the suitability of relationships thatsupport data to meet the needs of a particular com-pany or institution. The role of normalization in thiscase is in the use of bottom-up approaches and vali-dation techniques. The validation technique is used tocheck whether the relation structure produced by theER model is good or not. For more details, it can beshown in figure 1.

Figure 1: Role of normalization in database design.

In Figure 1 it can be seen that the data source con-sists of users, specifications of various user require-ments, various forms or reports, data dictionary andenterprise data models. Then there is the top-downand bottom-up approach where the approach will re-sult in the design of relations, then the role of normal-ization on bottom up and validation techniques (In-drajani, 2011).


147

Figure 2: The relationship of many to many between mem-ber entity and book entity.


3.1 Entity Relationship Model

In relational data modelling using the ER diagram canbe described in figure 2.

If the entities relationship described as many tomany, then it will make a new entity called GerundEntity or Associative Entity. The field key which con-nected each entities should be there in the new entity.Then, it continues by more relevant attributes added.It can be seen in figure 3.

Figure 3: Gerund entity from the relationship of book entityto the member entity.

The diagram in figure 3 can be described more de-tail in figure 4.

Figure 4: New entity formed (gerund entity).

Based on diagram in figure 4, can be transformedinto tables/relations by sample data shown in table 1to table 3.

The Member relation in the table 1 can be savemember data with member id as primary key. Therelation doest not have redudancy data.

The member relation has the form:

Table 1: Member Relation

member id name address phone1001 John Sudirman 10 6545341002 Dannis Dt. Setia 15 7423451003 Betty M.Yamin 12 653421

Table 2: Book Relation

book id title Author Publisher year

C-001

Concepts of

Database

Management

Philip

J.Pratt,

Joseph J

Adamski

Course

Technology2012

C-002

Principles of

Distributed

Systems

M. Tamer

Ozsu,

Patrick

Valduriez

Springer 2015

A-002

Fundamental

Accounting

Principles

John J.

Wild, Ken

W.Shaw

Mc Grow

Hill2015

Member (member id, name, address, phone)The Book relation in the table 1 can be save book

data with book id as primary key. The relation alsodoes not have redudancy data.The book relation has the form:Book (book id, title, author, publisher, year)

Table 3: Borrowing Relation

borrowi

ng id

membe

r id

borrow

date

book i

d

due da

te

return

date

19001 100105/02/

2019C-001

05/09/

2019

05/08/

2019

19001 100105/02/

2019C-002

05/10/

2019

06/12/

2019

19004 100306/10/

2019C-002

06/15/

2019

06/10/

2019

Cardinality relation between member and book re-lation is many to many so it creates the new table asgerund entity. In this case is called borrowing rela-tion (shown in the table 3). Borrowing relation hasborrowing id as primary key while member id andbook id is a foreign key.The borrowing relation has the form:Borrowing (borrowing id, member id, book id,due date, return date)

3.2 Analysis Anomalies of GerundEntity

Analysis of anomalies in the Borrowing relation byusing normalization technique.


148


borrowi

ng id

membe

r id

borrow

date

book i

d

due da

te

return

date

19001 100105/02/

2019C-001

05/09/

2019

05/08/

2019

19001 100105/02/

2019C-002

05/10/

2019

06/12/

2019

19004 100306/10/

2019C-002

06/15/

2019

06/10/

2019

In the Borrowing table as gerund entity. This ta-ble has some anomalies. It can be seen a memberborrows 2 books at 05/02/2019. In here contain dataredundancy in member id and borrow date.• To insert the book of borrowing id 19004, we

must enter member id and borrow date repeat-edly.

• If we want to change the value of member id orborrow date for borrowing id ‘19001’, we mustupdate the rows of the borrowing id. If this mod-ification is not carried out on all the appropriaterows of the Borrowing relations, the database willbecome inconsistent. So that, the borrowing rela-tion should be separated as a new table that calledis Borrowing Detail relation.

The resulting normalization relation have the form:

Borrowing (borrowing id, member id, borrow date)

Borrowing Detail (borrowing date, book id,due date, return date)

The Borrowing and Borrowing Detail relations areshown in Table 5 and Table 6. The result of GerundEntity analysis from Borrowing relation can be shownER model in Figure 5.


borrowing id member id borrow date19001 1001 05/02/201919004 1003 06/10/2019

Table 6: Borrowing Detail Relation

borrowing id book id due date return date19001 C-001 05/09/2019 05/08/201919001 C-002 05/10/2019 06/12/201919004 C-002 06/15/2019 06/10/2019

The establishment of a new entity from the gerundentity above will minimize or eliminate data redun-dant that can improve optimization of memory usage,consistency and data integrity.

Figure 5: ERD from analysis of Gerund Entity.

4 CONCLUSIONS

Based on the results of the analysis that has been car-ried out it can be concluded as follows:In the gerund entity is still possible for an anomalyto occur, so that it will create a new entity again asa derivative of the gerund entity which in this casethe author called the sub gerund entity. In the gerundentity, it is necessary to provide a connecting field tothe unique sub gerund entity. The establishment ofa new entity from the gerund entity will minimize ornot even redundant the data so that it can improve op-timization of memory usage, consistency and data in-tegrity. For complex databases, anomalous analysisof sub gerund entities can still be continued to ensurethat the resulting relations are free from anomalies.

ACKNOWLEDGEMENTS

This research supported by Universitas Islam Riau.Thank you very much for supported by UIR.

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Connolly, T. M. and Begg, C. E. (2005). Database systems:a practical approach to design, implementation, andmanagement. Pearson Education.

Date, C. J. (1977). An introduction to database systems (Vol.1). Pearson Education India.

Date, C. J. (1983). n introduction to database systems, Vol.II. Reading, Mass.

Gehrke, J. and Ramakrishnan, R. (2003). Database man-agement systems. McGraw-Hill.

Indrajani, S. M. (2011). Pengantar dan Sistem Basis Data.Jakarta: PT Elex Media Komputindo.


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Kroenke, D. M. and Dolan, K. (1983). Database Process-ing: Fundamentals, Design. Implementation. author.

Ramakrishnan, R. and Gehrke, J. (2000). Database man-agement systems. McGraw Hill.

Silberschatz, A., Korth, H. F., and Sudarshan, S. (1997).Database system concepts (Vol. 4). McGraw-Hill NewYork.

Stonebraker, M. and Moore, D. (1995). Object-relationalDBMS-the next wave. Informix Software (Now Partof the IBM Corp. Family), Menlo Park, CA, 14.

Sutedjo, B. and Oetomo, D. (2002). Perencanaan dan Pem-bangunan Sistem Informasi. Yogyakarta: Andi Offset.


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The Incidence of Rhinoceros Beetle Outbreak in Public CoconutPlantation in Tanjung Simpang Village, Indragiri Hilir, Riau Province

Saripah Ulpah1, Nana Sutrisna2, Fahroji2, Suhendri Saputra2, Sri Swastika2

1Department of Agrotechnology, Universitas Islam Riau, Pekanbaru, Indonesia2Assessment Institute for Agricultural Technology (BPTP) Riau

[email protected], natrisna, saputra [email protected], fahroji83, [email protected]

Keywords: Oryctes Rhinoceros, Outbreak, Breeding Site, Replanting, Coconut Plant.

Abstract: Indragiri Hilir is a Regency in Riau Province where about 70% of its population depend on coconut plantation.In 2018, a devastating outbreak of a coconut pest, Oryctes rhinoceros has been reported from several locations.The pest explosion in Tanjung Simpang Village, Pelangiran sub-district, has aroused conflict between coconutpalm farmers and the oil palm plantation company in the area regarding the source of the pest infestation. Anindependent scientific investigation was conducted to address the problem. Steps carried out including survey,interview, field investigation, and trapping. Survey was carried out to determine the center of infestation byevaluating damage intensity through interview and field assessment by direct visual evaluation and with theaid of drone. Spotting of breeding site was done in the vicinity of plant infested area. Digging and delvingbreeding sites were done to assess the beetle and its larvae. Trapping using pheromone trap was intended toevaluate the beetle distribution. Interview was perfomed both to the coconut farmers and and the companystaff to investigate the infestation chronology and activities in the oil palm plantation. The findings indicatedthrough the research were then revealed to the both parties and also to the authority as elucidated in this paper.

1 INTRODUCTION

Coconut plantation plays the important roles for theeconomic, social and culture of most people in Indra-giri Hilir Regency. Being “the tree of life”, whereevery part of the plant possesses economic value, co-conut from this area not only fulfills the domestic de-mand but also is potential as export commodity.

There are several factors that have been reportedto act as rectricting factors of coconut production inIndragiri Hilir (Muhartoyo, 2017). One of them isthe population explosion of a pest, the Rhinocerosbeetle; Oryctes rhinoceros. The beetle is known asa global invasive pest particularly in coconut and oilpalm (CABI, 2018; Manley et al., 2018; Sherley,2000; ?). Infestation of this pest is very destructivebecause could result in the plant to die, both for theyoung plants and the old ones (CABI, 2018; Chalap-athi Rao et al., 2018). The population outbreak couldbe triggered by significant change of the environmentparticularly when ample breeding sites are available(Abidin et al., 2014; Balitka, 2010; Bedford et al.,2014; Marshall et al., 2017).

In Indragiri Hilir, massive infestation of this pesthas been reported occurred in several areas. The in-

festation is estimated up to 1975.5 ha; 1192.5 beingmoderately infested and 783 ha severely damage.

Pest outbreak in public coconut plantation in Tan-jung Simpang has provoked conflict because the farm-ers claimed that the source of the pest outbreak wasthe replanting activity conducted by the oil palm com-pany in the vicinity. Since the oil palm companydenied the claim, Indragiri Hilir Regency authorityordered scientific investigation to address the issue;which was agreed by both parties. Hence the scien-tific investigation was carried out.

2 METHODOLOGY

2.1 Time and Research Site

Study was conducted from January to May 2019.Investigation was done in Tanjung Simpang Vil-

lage, Sub-distrct Pelangiran in Indragiri Hilir; on bothpublic coconut plantation and company oil palm plan-tation.

Ulpah, S., Sutrisna, N., Fahroji, Saputra, S. and Swastika, S.The Incidence of Rhinoceros Beetle Outbreak in Public Coconut Plantation in Tanjung Simpang Village, Indragiri Hilir, Riau Province.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 151-154ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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2.2 Survey

Survey activity was conducted through interviewingcoconut farmers whose plants affected by the infes-tation of Rhinoceros beetle, regarding their sociocul-tural and understanding of the pest infestation. OilPalm plantation officials were also interviwed regard-ing their activity that might have affected the pest out-break. Related information was also obtained fromvillage officials.

2.3 Field Investigation

In public coconut plantation, field investigation wasdone by assessing the plant damage through direct vi-sual evaluation and with the aid of drone. Spottingbreeding site was also perform in the vicinity by dig-ging and delving the potential breeding site then col-lecting and counting the speciments. Systematic as-sessment was conducted in every 100m distant fromthe boundary of oil palm plantation, through visualdamage evaluation and trapping using the syntheticpheromone of the beetle at 150m interval.

In the oil palm plantation, investigation was car-ried out by spotting the possible breeding site of thebeetle. Field assessment was also perfomed to eval-uate the condition of the field and the new replantingoil palm.

2.4 Disclosure of the Reseach Findings

After twice visits and field assessment to the bothpublic coconut plantation and oil palm plantation,data gathered then studied thoroughly. Supportedwith ample scientific information to the data obtained,the findings then formulated and presented to eachparty and regency authorities.


3.1 General Information about TanjungSimpang Village

Tanjung simpang village is located in Sub-districtPelangiran with the area of 222 Km2 and inhabitateby 16 726 people. Most of the people in this area de-pend on coconut plantation. The distance of the vil-lage to the sub-district capital is 60 km, while thatof from the regency capital is 80 km, however themain transportation was through water that could bereached in about 2 hour.

The oil palm plantation company is located adja-cent to the village, covered 83 000 ha. The historyof oil palm first planting was started in 1996 on theland initially forest. Starting in 2015, the companydecided to replant the oil palm tree due to the poorcondition aggravated by the disease caused by Gano-derma funggus. The replanting plan was conducted instages as shown in Figure 1.

Figure 1: Replanting Stages Executed by Oil Palm com-pany.

3.2 Results from Field Assessment

From field observation it was found that infestationranged from 50 % to 100 %. Such massive dam-age is imminent if Oryctes population outbreaks isnot suppressed immediately (Chung, 2012; Marshallet al., 2019). The damage symptom caused by theRhinoceros beetle was very clear (Figure 2), whichwere the fan like cut on the opened coconut leaf andthe holes at the base of coconut leaf midrib (ACIAR,2017; Domberg, 2015).

The level of infestation affected by the distant ofthe coconut palm plantation to the company oil palmplantation. The severe damage was observed withinthe area adjacent to and up to 100m from the companyoil palm plantation, then gradually decreased by theincreasing distance from the company oil palm plan-tation. Photos captured with a drone also reveals thephenomenon (figure 3).

Digging and delving of the potential breeding siteof the beetle revealed the present of the beetle and itslarvae (Figure 4).

All coconut trees found up to 1100 m from thecompany oil palm plantation were attacked by thebeetle twith various intencity as shown in the Figure5.

Average number of beetles captured usingpheromone trap was also derceased by inreasing dis-tance from the company oil palm plantation whichwere 137, 88, 66 and 49 respectively for every 150


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Figure 2: Symptoms of Oryctes rhinoceros infestation.

Figure 3: The condition of coconut plantation adjacent tothe company palm plantation.

Figure 4: The beetle and its grubs located in the breedingsite spotted in adjacent area to the company palm oil plan-tation.

m interval away from the palm oil plantation. The useof pheromone-baited trap could be used as a tool to lo-cate the occurrence of the pest outbreak (Moolen andDowdy (2001, in (Ahmad and Kamarudin, 2011)),besides to control the pest population (Allou et al.,2006).

3.3 Other Findings

There are additional findings that could be taken intoaccount. Firstly, the chronology of the beetle infes-

Figure 5: Level of Rhinoceros infestation related to the dis-tance toward the palm oil plantation.

tation symptoms (started in the end of 2017 and get-ting severe by 2018) was synchron with the replant-ing activity by the company. The life cycle of in-sect such as this beetle vary greatly depending onthe food source and environmental conditions (Ka-marudin et al., 2005; Khaliq et al., 2014; Kumashiroet al., 2014). Nuriyanty et al. (2016) reported that thelife cycle of this beetle was approximately 4 monthsin Purbalingga regency. Secondly, the replanting wasconducted due to the poor condition of diseased palmoil tree caused by Ganoderma. According to Ka-marudin and Wahid (2004), poor stand of palm treesinfected by Ganoderma could be a suitable habitatfor initial build up population of the beetle. Pasaribuand de Chenon (2005) also highlighted the report byPPKS (1996) emphasizing that replanting oil palmpreviously infected by Ganoderma provided suitablemedia for population build up of the beetle. Thirdly,replanting provided abundant breeding sites for thebeetle (Abidin et al., 2014). Eventhough the companyofficials claimed that proper SOP for replanting hadbeen executed, remnant of the trunk was still foundconsisting of the beetle and its grub. Fourthly, Thefarther the location from the company palm oil plan-tation, the lesser the infestation and also the fewer thebeetle captured; indicating the center of pest outbreak.Fiftly, the legume cover crop planted which was in-tended to further conceal the buried chipping material,did not grow as expected. Vegetation such as legumecover crop is crucial to suppress oviposition by femalebeetle (Wood, 1969; Vargo, 2000), therefore couldbreak the insect cycle, (Clark, 2007). Lastly, the mostimportant step that should have been done but was ne-glegted was anticipation, socialization and extensionto the society in the area that might have been affectedby replanting activity, since replanting site has beenwidely known as breeding ground for this pest (Man-jeri et al., 2014; PEI, 2019).

The Incidence of Rhinoceros Beetle Outbreak in Public Coconut Plantation in Tanjung Simpang Village, Indragiri Hilir, Riau Province

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4 CONCLUSION

With the above data and finding, it was concludedthat the damage on the coconut plantation was re-sulted by the infestation of Rhinoceros beetle, Oryctesrhinoceros. The pest population outbreak was re-sulted from replanting activity of the company oilpalm plantation.

ACKNOWLEDGEMENTS

The authors wish to thank Indragiri Hilir Regency Au-thority for funding the study, and the Indragiri HilirPlantation Office for the accompeniment of the fieldinvestigation.

REFERENCES

Abidin, C., Ahmad, A. H., Salim, H., and Hamid, N. H.(2014). Population dynamics of oryctes rhinoceros indecomposing oil palm trunks in areas practising zeroburning and partial burning. Journal of Oil Palm Re-search, 26(2):140–145.

ACIAR (2017). Pacific pests and pathogens. fact sheets no108.

Ahmad, S. N. and Kamarudin, N. (2011). Pheromone trap-ping in controlling key insect pests: Progress andprospects. Oil Palm Bulletin, 62:12–24.

Allou, K., Morin, J.-P., Kouassi, P., N’klo, F. H., andRochat, D. (2006). Oryctes monoceros trapping withsynthetic pheromone and palm material in ivory coast.Journal of chemical ecology, 32(8):1743–1754.

Balitka (2010). Pengendalian kumbang kelapa. Balai Pen-gendalian Tanaman Palma, Menado.

Bedford, G. O. et al. (2014). Advances in the controlof rhinoceros beetle, oryctes rhinoceros in oil palm.Journal of Oil Palm Research, 26(13).

CABI (2018). Invasive species compendium, oryctesrhinoceros. cab international.

Chalapathi Rao, N., Snehalatharani, A., Nischala, A., Ra-manandam, G., and Maheswarappa, H. (2018). Man-agement of rhinoceros beetle (oryctes rhinoceros l.)by biological suppression with oryctes baculovirus inandhra pradesh.

Chung, G. F. (2012). Effect of pests and diseases on oilpalm yield. In Palm Oil, pages 163–210. Elsevier.

Domberg, M. (2015). Featured creatures:coconutrhinoceros beetle. UF/IFAS. University of Florida.Publication number:EENY-629.

Kamarudin, N. and Wahid, M. (2004). Immigration andactivity of oryctes rhinoceros within a small oil palmreplanting area. Journal of Oil Palm Research,16(2):64–77.

Kamarudin, N., Wahid, M. B., and Moslim, R. (2005). En-vironmental factors affecting the population densityof oryctes rhinoceros in a zero-burn oil palm replant.Journal of Oil Palm Research, 17(N):53.

Khaliq, A., Javed, M., Sohail, M., and Sagheer, M. (2014).Environmental effects on insects and their populationdynamics. Journal of Entomology and Zoology stud-ies, 2(2):1–7.

Kumashiro, B., Hauff, R., Hara, A., Kishimoto,C., and Ishibashi, Y. (2014). Coconutrhinoceros beetle, oryctes rhinoceros (linnaeus)(coleoptera:scarabaeidae). New Pest Advisory No.14-01. Plant Pest Control Branch, Hawaii Department ofAgriculture.

Manjeri, G., Muhamad, R., and Tan, S. G. (2014). Oryctesrhinoceros beetles, an oil palm pest in malaysia. An-nual Research & Review in Biology, 4(22):3429.

Manley, M., Melzer, M., and Spafford, H. (2018). Ovipo-sition preferences and behavior of wild-caught andlaboratory-reared coconut rhinoceros beetle, oryctesrhinoceros (coleoptera: Scarabaeidae), in relation tosubstrate particle size. Insects, 9(4):141.

Marshall, S., Moore, A., and Vaqalo, M. (2019). A newcoconut rhinoceros beetle biotype threatens coconutand oilpalm in souteast asia and the pasific.

Marshall, S. D., Moore, A., Vaqalo, M., Noble, A., andJackson, T. A. (2017). A new haplotype of the coconutrhinoceros beetle, oryctes rhinoceros, has escaped bi-ological control by oryctes rhinoceros nudivirus andis invading pacific islands. Journal of invertebratepathology, 149:127–134.

Muhartoyo (2017). The investment opportunities in coconutsector in indragiri hilir. Cocoinfo International, 24(2).

Nuriyanti, D. D., Widhiono, I., and Suyanto, A. (2017).Faktor-faktor ekologis yang berpengaruh terhadapstruktur populasi kumbang badak (oryctes rhinocerosl.). Majalah Ilmiah Biologi BIOSFERA: A ScientificJournal, 33(1):13–21.

Pasaribu, H. and de Chenon, D. (2005). Strategi pen-gendalian hama oryctes rhinocheros. Pertemuan tek-nis kelapa sawit, PT Tolan Tiga Indonesia (SIPEFGROUP), Sheraton Mustika Hotel. Yogyakarta.

PEI (2019). Masa replanting kelapa sawit rentan kumbangtanduk. berita pei.

Sherley, G. (2000). Invasive species in the pacific: a tech-nical review and draft regionalstrategy. south pacificregional environment program (sprep). 190p.

Vargo, A. (2000). Coconut rhinoceros beetle (oryctesrhinoceros). Agricultural Development in the Ameri-can Pacific (ADAP). 2000-4. ISBN 1-931436-07-3.

Wood, B. J. (1969). Studies on the effect of ground veg-etation on infestations of oryctes rhinoceros (l.)(col.,dynastidae) in young oil palm replantings in malaysia.Bulletin of Entomological Research, 59(1):85–96.


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Mobile Application of Religious Activities for the Great Mosque IslamicCenter Rokan Hulu with Push Notification

Salhazan Nasution1, Arbi Haza Nasution2, Fitra Yamita1

1Department of Informatics Engineering, Universitas Riau, Pekanbaru, Indonesia2Department of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia


Keywords: The Great Mosque Islamic Center Rokan Hulu, Android Application, Push Notification.

Abstract: The Great Mosque Islamic Center Rokan Hulu is the best national mosque in Indonesia and also as an iconof Rokan Hulu Regency which has the nickname of the Country of Thousand Suluk. This mosque is also areligious tourist place. Therefore, this mosque has many religious activity agendas that are in the spotlightof the wider community. The lack of information dissemination on religious activities is a major problemthat must be overcome. Communities often get non-updated information and outdated information. MobileApplication of Religious Activities for the Great Mosque Islamic Center Rokan Hulu with Push Notificationis the solution to these problems. This application uses the push notification method so that users easilyget information on religious activities through automatic notifications on the user’s smartphone and also asa reminder of the schedule of religious activities. Users can also set up information on religious activityinformation they want to get through the notification configuration menu. Besides, this application also has amenu about mosques that contain information on the Great Mosque Islamic Center Rokan Hulu such as prayerschedules, locations, descriptions, and galleries.

1 INTRODUCTION

A mosque is the Muslim gathering place for prayer,the building in which Muslims worship God. Thefunction of the mosque is not only a place of pros-tration but a mosque is the center of Islamic religiousactivities. During the Prophet Muhammad SAW, themosque functioned as a center for educational activ-ities, namely a place for fostering and forming thecharacter of the people (Kurniawan, 2014). Activitiessuch as celebrating Islamic holidays, discussions, reli-gious studies, lectures, recitals, and Al-Qur’an learn-ing places are held in the mosque. In addition, themosque also has a schedule of activities to be carriedout both routine activities and other religious activi-ties carried out at a certain time.

Rapid technological development is the solutionto several problems to help human work. In this eraof globalization, almost everyone has a smartphoneto support their activities. One of the operating sys-tems is Android. Android is a Linux-based mobilephone operating system. Open source, the sourcecode is provided free of charge to developers to createtheir applications to run on Android (Nugroho, 2017).Most smartphone producing companies choose the

Android operating system for their smartphone prod-ucts. Smartphones with Android-based operating sys-tems are cheaper than smartphones with paid operat-ing systems. Push notification is a service that canprovide special notifications instantly on an Androidsmartphone. The push notification service can helpusers get short notifications. This service is bene-ficial in disseminating and providing information inreal-time. So, it can overcome problems in the dis-semination of information such as information that isdifficult to obtain, information that is not up to dateand information received is outdated.

The Great Mosque Islamic Center Rokan Hulu isthe best national mosque in Indonesia and also as anicon of Rokan Hulu Regency which has the nicknameof the Country of Thousand Suluk. This mosque isalso a religious tourist place. So, this mosque hasmany religious activity agendas that are in the spot-light of the wider community. Information about re-ligious activities is needed by some tourists so theycan arrange a schedule of visits to the mosque ac-cording to these religious activities. The surround-ing community also very much wants to take part inthe religious activities carried out. Because the GreatMosque Islamic Center Rokan Hulu is a mosque that

Nasution, S., Nasution, A. and Yamita, F.Mobile Application of Religious Activities for the Great Mosque Islamic Center Rokan Hulu with Push Notification.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 155-162ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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is the center of religious activities at the district level.The lack of information in spreading religious activ-ities is a problem that must be overcome. To over-come the lack of information dissemination of reli-gious activities at the Great Mosque Islamic CenterRokan Hulu, then an application for religious activ-ity information is made using the push notificationmethod. So, users immediately get notifications au-tomatically on their smartphone when information onreligious activities entered by the admin or adminis-trator of the mosque. The Limitation of the problemsin this research is (1) This application is made forsmartphones that use the Android operating system;supports Android 4.4 (KitKat) and the latest version.(2) The push notification method in this applicationuses the Firebase Cloud Messaging (FCM) service.(3) Application management is done through the webby the admin.

2 LITERATURE REVIEW

To complete the research process, a theoretical basisis needed as the basis for research work. Fundamentaltheories are taken from books, theses, previous stud-ies, and scientific journals.

2.1 Web

The web is a collection of web pages, usually summa-rized in a domain that is located on the World WideWeb (WWW) on the internet (Jasmadi, 2004). Theweb becomes a computer network-based informationmedia that can be accessed anywhere at a relativelylow cost. The web is a form of implementation ofweb programming languages.

2.2 Android Operating System

Android is one of the mobile phone operating sys-tems. Other mobile phone operating systems such asWindows Mobile, iPhone, Symbian, and many more.This Android operating system runs by prioritizingcore applications without involving third parties eventhough the potential of third parties is greater. So thatthird-party applications have distribution limitationsin getting original data from mobile phones, commu-nicating between processes and the limitations of ap-plication distribution for their platforms (Stephanus,2011). The Android architecture consists of applica-tions and widgets, application framework, libraries,android run time, and Linux kernel.

2.3 Firebase

Firebase is Backend as a Service (BaaS) which iscurrently owned by Google. Firebase is a web ap-plication platform that helps developers build high-quality applications by storing data in the format ofJavaScript Object Notation (JSON) that does not usequeries to insert, update, delete or add data to it(Khawas and Pritam, 2018). Firebase provides a vari-ety of services, one of which is a push notification fea-ture called Firebase Cloud Messaging (FCM). FCMis a development of Google Cloud Messaging (GCM)that provides services so that developers can send no-tification messages to Android devices from servers(Nurzam et al., 2017)).

2.4 Push Notification

Push notification is a service that is widely used fornotification via short messages on smartphones (Sid-dik and Nasution, 2018). The application that will bedesigned is an application that can send push notifi-cations which will later be developed in various fieldsaccording to user needs. Lack of knowledge in thedissemination and notification of information in real-time, the information obtained is not up-to-date, sothat in various situations and conditions the informa-tion provided is outdated.

Push notification is one of the services that canovercome these problems so that no more recent in-formation is not delivered. With the use of this ser-vice, every updated information will immediately besent as a notification message, so the latest informa-tion will not be missed. Push notification service isgenerally widely applied to mobile applications suchas Android and other operating systems.

2.5 The Great Mosque Islamic CenterRokan Hulu

The Great Mosque Islamic Center Rokan Hulu is lo-cated at coordinates n 000 53 ’44.3 ”e. 1000 18 ’31.5’.The background of the establishment of this mosquewas based on the brilliant idea of the Rokan Hulu Re-gent, which was due to the absence of a representativemosque to be used as a prayer place and district-levelreligious activities. One district mosque that can beused as a center of activity as well as a symbol of Is-lam in Rokan Hulu, moreover this area is nicknamedthe Country of Thousand Suluk. Thousand Suluk isan area where many people carry out dhikr in a partic-ular place (surau) which is called by bersuluk (BadanPengelola Masjid Agung Islamic Center Rokan Hulu,2016).


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Figure 1: The great mosque islamic center rokan hulu.

The Great Mosque Islamic Center Rokan Hulu isan icon of Rokan Hulu district, dubbed the Country ofThousand Suluk. The function of the Great MosqueIslamic Center Rokan Hulu is not just a place of wor-ship but has expanded and improved its function inaccordance with the motto of the mosque as a meansof worship, achieving blessings, and increasing spirit.Equipped with various facilities, infrastructure, andwell planned religious activities programs, the GreatMosque of the Islamic Center of Rokan Hulu be-comes the center of Islamic studies and the practiceof Al-Quran values. This mosque is also a place offormation of the Islamic community in order to buildan advanced Islamic society and become a pioneer ofthe development of Islam in the international world.

2.5.1 Religious Activity Schedule of the GreatMosque Islamic Center Rokan Hulu

The schedule of religious activities at the GreatMosque Islamic Center Rokan Hulu is very crowdedevery day. The schedule of religious activities isas follows: (Badan Pengelola Masjid Agung IslamicCenter Rokan Hulu, 2016).

• Organizing Fardhu Prayer Services, which are at-tended by thousands of worshipers every day.

• Organizing Friday Prayers. The Khatib sermoncame from Pekanbaru and the leadership of thepesantren in Rokan Hulu Regency and at least hada Master degree and Lc.

• Organizing Islamic Day Activities. Celebrationof Islamic holidays with various activities suchas marches to welcome the new year of Hijriah,the splendor of Ramadhan, Tabligh Akbar, vari-ous kinds of competitions and so forth.

• Organizing Islamic Da’wah and Tabligh Akbarroutinely carried out both weekly and monthly.

• Carrying out routine recitation every once a week.

• Organizing Educational Activities. Carried outthrough da’wah, also developed in the form of

particular institutions such as Pendidikan AnakUsia Dini (PAUD), Tahfiz High School to ISQSyekh Ibrahim which blends with the mosque en-vironment.

• Empowerment of Zakat, Infaq, Shodaqoh, andEndowments.

• Carry out the Recitations and Religion Lectures atFajr and Friday Morning.

• Various Special activities during Ramadan.

3 METHODOLOGY

In this research, the first step to be carried out wasthe identification of problems which later found sev-eral issues regarding the dissemination of informa-tion on religious activities. The second stage, lookingfor suitable literature studies. The third stage, datacollection, and processing is done through observa-tion and documentation from the Mosque Manage-ment Agency. Then do the analysis and design phase.After that, the system will be created and tested. If thesystem works properly, then the next stage of imple-mentation and if the system does not run as it shouldthen return to the analysis and design phase. The laststage after implementation is the conclusion. The re-search methodology can be seen in Figure 2.

Figure 2: Research methodology diagram.

3.1 General Description of the System

The general description of the system can be seen inFigure 3, where the Mobile Application of ReligiousActivities for the Great Mosque Islamic Center RokanHulu with Push Notification will receive input fromthe admin in the form of the latest, routine, and infor-mation about the mosque. The user will set the notifi-cation according to the choice of the diverse activities

Mobile Application of Religious Activities for the Great Mosque Islamic Center Rokan Hulu with Push Notification

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topic that the information wants to get. If the user hasset a notification, then the information on religiousactivities that you want to follow will be quickly ob-tained with a notification on the user’s smartphone.

Figure 3: General description of the system.

3.2 Use Case Diagram

Use case diagrams are descriptions of a system that isused to make it easy to explain how the system and itscomponents can be related. In the Mobile Applicationof Religious Activities for the Great Mosque IslamicCenter Rokan Hulu there are 2 user sides, namely ad-min and user. The user is used as an actor in the usecase diagram. Admin has full access to manage allapplications, managing the latest religious activity in-formation, managing routine religious activity infor-mation, sending notifications and also can add anotheradmin. Before performing this task, the admin mustlog in into the system.

User can view information on the latest religiousactivities, information on routine religious activities,find the location of the nearest mosque, see infor-mation about the mosque such as prayer schedules,mosque locations, descriptions of mosques, and gal-leries. Users can also configure notifications to selectinformation on any religious activities that their no-tifications want to get. The use case diagram in thisapplication can be seen in Figure 4.

3.3 Display Design

Display design is a drawing process from the appear-ance of the system created. Display or interface isa communication mechanism between users with theapplication.

3.3.1 Designing Display of Android Applicationsfor Users

To use this mobile application, the user should installfrom the Google Play store. Users will get informa-

Figure 4: Use case diagram on application.

tion on these mobile apps and can set notifications ac-cording to the topic of information on religious activ-ities whose information they wish to obtain. Here isthe design of the android application for the user.

• Splash ScreenA splash screen is the first display when the useropens the application. The design of the splashscreen display can be seen in Figure 5.

Figure 5: Design of the splash screen application.

• Application Main DisplayThe main display design of the Mobile Applica-tion of Religious Activities for the Great MosqueIslamic Center Rokan Hulu can be seen in Figure6. In the main view of the application, the usercan immediately see the latest religious activityinformation via the home menu.

• Notification Configuration MenuThis notification configuration menu allows users


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Figure 6: Design of the main display application.

to choose what religious activity notifications theywant to get information through notifications as areminder of the activity schedule. The design ofthe notification configuration menu can be seen inFigure 7.

Figure 7: Design of the notification configuration menu.

• About Mosque MenuThe about mosque menu has four submenus,namely prayer schedule, mosque location,mosque description, and gallery. The prayerschedule submenu will display prayer timesaccording to the Great Mosque Islamic CenterRokan Hulu. The sub-menu of the mosque loca-tion will display the location of the mosque withthe Google Maps API. The submenu of mosquedescriptions is information about the mosque.The mosque gallery submenu will display photosof the mosque. The design of the menu displayabout mosques can be seen in Figure 8.

Figure 8: Design of about the mosque.

3.3.2 Designing Web Views for Admin

Admin is the manager of the entire system. Next isthe web view design for the admin as manager of thesystem.

• Admin Login DisplayThe login display is a display used by the adminto be able to enter the system and manage the sys-tem. The design of the admin login can be seen inFigure 9.

Figure 9: Design of the admin login display.

• Send Notification MenuSend Notification Menu is a menu used by the ad-min to send notifications to users on the androidapplication. The design of the send notificationmenu display can be seen in Figure 10.


Display implementation is the implementation stageand at the same time testing the system based on the


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Figure 10: Design of the send notification menu.

results of analysis and design that has been done inthe previous chapter.

4.1 Display of Android Applications forUsers

This display is a display of android applications usedfor users accessing information on diversity activitiesand information about the Great Mosque Islamic Cen-ter Rokan.

• Splash ScreenA splash screen is the first display when the useropens the application. The appearance of thesplash screen can be seen in Figure 11.

Figure 11: Display splash screen.

• Beranda MenuThe home menu is a menu that displays a list of

the latest religious activities at the Great MosqueIslamic Center Rokan Hulu. Display of the homemenu can be seen in Figure 12.

Figure 12: Display of home menu.

Detailed information on religious activities can beseen in Figure 13.

Figure 13: Detailed information on religious activities.

• Notification Configuration MenuThis notification configuration menu allows usersto select religious activity notifications that theywant to obtain information through notificationsas a reminder of the activity schedule. After theuser activates the selected notification, the userwill automatically get a notification according tothe notification that has been activated. For ex-ample, the user activates a notification for infor-


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Table 1: Likert scale for application display.

No. Category Score1. Strongly Agree (SA) 52. Agree (A) 43. Neutral (N) 34. Disagree (D) 25. Strongly Disagree (SD) 1

Table 2: Likert scale for plugin convenience.

No. Category Score1. Very Inconvenient 0%-19.99%2. Inconvenient 20%-39.99%3. Slightly Convenient 40%-59.99%4. Convenient 60%-79.99%5. Very Convenient 80%-100%

mation on Islamic Da’wah/Recitation activities asshown in Figure 14.

Figure 14: Configuration notification display.

Then, if the admin sends notifications with thecategory of Islamic Da’wah/Recitation throughthe web admin. Then the user will immedi-ately get the notification. The push notifica-tion test display for the stage of receiving Is-lamic Da’wah/Recitation notification on the An-droid application for the user can be seen in Fig-ure 15.

4.2 Application Testing Results

Application testing has been done by directly exam-ining the application and also by filling out the testingquestionnaire. The number of respondents obtainedby researchers amounted to 10 people, six peoplefrom Rokan Hulu and four people from outside Rokan

Figure 15: Display of push notification on android applica-tions.

Hulu. The questionnaire is using the 5 Likert-scalewith a final score percentage adapted from (Sagi et al.,2015) as shown in Table 1 and Table 2. This ques-tionnaire was conducted to find out how well the de-sign and usefulness of the features in the application.Some questions on this questionnaire were adaptedfrom research conducted by Yasin (Yasin et al., 2013).

4.2.1 Application Display Test Results

Application display testing has done by ten respon-dents, and these results have been collected from thequestionnaires filled by each respondent. The re-sults of the application display questionnaire and theresults of the application benefit questionnaire areshown in Table 3 and Table 4 respectively.

From the results of the application testing ques-tionnaire it can be concluded that the appearance ofthe application with an average value of 89% is veryconvenient and for the benefit of the application withan average value of 89.3% which is very convenient.

5 CONCLUSIONS

Mobile Application of Religious Activities for theGreat Mosque Islamic Center Rokan Hulu uses thepush notification method. This application is runningon the Android-based phone. Push notification givenin this apps is very useful, the user will get notifica-tions about religious activities at the Great MosqueIslamic Center Rokan Hulu; therefore no informationwill be missed out. This apps also have a schedulereminder of religious activities which can be config-ured by the user in the android application. In additionto disseminating information on religious activities,


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Table 3: Application display questionnaire results.

No Statement Total Answer Total Score %SD D N A SA1. Attractive application display. 2 5 3 41 82%2. App appearance is easy to understand or user-

friendly.4 6 46 92%

3. Easy menu navigation. 4 6 46 92%4. Color is appropriate or not excessive. 4 6 46 92%Total 179Average 44,75 89%

Table 4: Plugin convenience test result.

No Question Total Answer Total Score %VD D N A VA1. Menu features in the application are complete

and according to user needs.1 6 3 42 84%

2. The home menu feature is very informativeto add information and insights to applicationusers.

1 5 4 43 86%

3. The notification configuration menu featurehelps users receive notification of religious ac-tivity information as desired.

1 3 6 45 90%

4. Notification as a reminder of the schedule ofreligious activities.

6 4 44 88%

5. This application is very easy to use. 4 6 46 92%6. This application is very useful for users, espe-

cially the Rokan Hulu community.2 8 48 96%

Total 268Average 44,6 89,3%

users can also find out information about the GreatMosque Islamic Center Rokan Hulu. This apps hasbeen tested by ten respondents, the appearance of theapplication is rated ”very convenient” with an averagepercentage of 89%; meanwhile the benefit of the ap-plication is rated ”very convenient” with an averagepercentage of 89.3%.

REFERENCES

Badan Pengelola Masjid Agung Islamic Center Rokan Hulu(2016). Profile masjid agung islamic center rokanhulu.

Jasmadi (2004). Koleksi Templete Web dan Teknik Pembu-atannya. Yogyakarta : CV Andi Offset.

Khawas, C. and Pritam, S. (2018). Application of firebase inandroid app development-a study. International Jour-nal of Computer Applications, 179(46):49–53.

Kurniawan, S. (2014). Masjid dalam lintasan sejarah umatislam. Khatulistiwa, 4(2).

Nugroho, W. N. (2017). Aplikasi pencarian masjid ter-dekat di kota bandar lampung berbasis mobile meng-

gunakan algoritma dijkstra. Skripsi. Fakultas Matem-atika dan Ilmu Pengetahuan, Universitas Lampung.

Nurzam, F., Fajri, I. N., and Prabowo, D. (2017). Rancangbangun aplikasi media laporan aspirasi dengan fire-base cloud messaging berbasis mobile. Seminar Na-sional Teknologi Informasi dan Multimedia, STMIKAMIKOM Yogyakarta, 5(1):4–5.

Sagi, F. N., Udiana, I. M., and Ramang, R. (2015). KajianFaktor-Faktor Penyebab Ketidakefektifan Kinerja Ter-minal Bus Haumeni Kota Soe Kabupaten Timor Ten-gah Selatan. Teknik Sipil, IV(2):183–194.

Siddik, M. and Nasution, A. (2018). Perancangan aplikasipush notification berbasis android. JURTEKSI (JurnalTeknologi dan Sistem Informasi), 4(2):149–154.

Stephanus, H. (2011). Mudah Membuat Aplikasi Android.Yogyakarta: Andi Offset.

Yasin, M., Sahari, N., and Nasution, A. (2013). Online lit-eracy and mathematics assessment for deaf and hardof hearing students. CREAM. Current Research inMalaysia, 2(1):65–99.


162

An Augmented Reality Machine Translation Agent

Arbi Haza Nasution1, Yoze Rizki2, Salhazan Nasution3, Rafi Muhammad1

1Department of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Department of Informatics Engineering, Universitas Muhammadiyah Riau, Pekanbaru, Indonesia

3Department of Informatics, Universitas Riau, Pekanbaru, [email protected], [email protected], [email protected], [email protected]

Keywords: Machine Translation, Augmented Reality, Chatbot.

Abstract: English is a language used as a universal communication tool. Therefore, without English skills, a person willhave a difficulty to communicate properly and correctly in the international scope. This research developedan application of augmented reality-based translating machine that provides the education to students withdifferent media in order to increase students’ interest in learning English. This application used libraryVuforia sdk which is able to display 3-dimensional characters with markerless techniques in the form ofaugmented reality. The final result of this study was an application that can be used on smartphones withAndroid operating system. Based on the results of the application testing, it is concluded that this applicationcan display 3-dimensional characters in dim light with light intensity of 28 lux at a distance of 10cm-60cmand viewing angle of 10-90. After reviewing the application, 95% of the correspondents stated that thisapplication is good so it can help students to relearn English outside the school.

1 INTRODUCTION

According to Yamin (2017), the current developmentof information technology makes all developingcountries improve the quality of their humanresources as an effort to face global competition.English is one language that is used as a universalcommunication tool in the international scope.

Moreover, Galih et al. (2017) states thatEnglish iscurrently a foreign language introduced inelementary schools because children aged 6-12 yearshave a brilliant learning period called the golden age(Saputra and Indonesia, 2014; Pangestika et al., 2017;Mariani and Ananta, 2017).

The learning facilities at school are stillconventional in which teachers deliver the lessonsassisted by textbooks as teaching guides in frontof the class. As a result, this makes students lessinterested in the learning process.

This research generates a system in the formof an attractive English learning tool to increasechildren’s learning interest at the school age. Thissystem translates a text into sound in Indonesian toEnglish and vice versa. A smartphone is neededas a medium to run the application. Charactersin 3-dimensional form will translate questions fromusers, either words or sentences that have been

previously inputted (Dikdok, 2017; Efendi, 2014).

2 LITERATURE REVIEW

There are several prior works being discussed in thissection. The first study was an implementationof augmented reality systems conducted byYoga Aprillion Saputra, (2014), entitled ”TheImplementation of Augmented Reality (AR) inArchaeological Fossils at the Bandung GeologicalMuseum”. The second study becoming the referencefor the language translation process was conductedby Galih Vidia Pangestika, et al. (2017) entitled”An Android-Based English Language LearningApplication for Elementary School Students”. Thenext research was conducted by Mariani, et al. (2017)entitled ”The Development of SMS Response andPhone Call Applications Using Android Text ToSpeech and Proximity Sensors for Drivers” as areference for the implementation of Text To Speechmethod (Mariani and Ananta, 2017; Pangestika et al.,2017; Saputra and Indonesia, 2014).

Based on the literature reviews of the previousresearch, it can be concluded that the creation ofan augmented reality-based machine translation thatutilizes markerless techniques and Vuforia SDK as a

Nasution, A., Rizki, Y., Nasution, S. and Muhammad, R.An Augmented Reality Machine Translation Agent.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 163-168ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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supporting library has never been done.

2.1 Machine Translation

There are three different kind of machine translation.The rule-based method is a technique thatuses standard language rules in the process oftransliteration (Rahman et al., 2014; Dewantara et al.,2013). Hansel (2009) states that statistical machinetranslation utilizes a machine translation paradigmin which the translation results are generated on thebasis of statistical models using parameters obtainedfrom the analysis of the collections of paralleltwo-language texts. The neural machine translationis a new feature of google translate that works bytranslating all sentences at once, so the translationlooks more natural, accurate and not weird when it isread.

In the research of Nasution, et.al (2017), MachineTranslation (MT) is very useful in supportingmulticultural communication. Existing StatisticalMachine Translation (SMT) which requires highquality and quantity of corpora and Rule-BasedMachine Translation (RBMT) which requiresbilingual dictionaries, morphological, syntax, andsemantic analyzer are scarce for low-resourcelanguages. Due to the lack of language resources,it is difficult to create MT from high-resourcelanguages to low-resource languages like Indonesianethnic languages. Nevertheless, Indonesian ethniclanguages’ characteristics motivate us to introducea Pivot-Based Hybrid Machine Translation (PHMT)by combining SMT and RBMT with Indonesian asa pivot which we further utilize in a multilingualcommunication support system(Nasution et al., 2017;Panggabean, 2016).

2.2 Pivot-based Hybrid MachineTranslation

In the research of Nasution, et.al (2018), GoogleTranslate service and bilingual dictionary servicewere combined as a composite service in the languagegrid. There are more than a hundred high-resourcelanguages available in the Google Translate service.To this date, two Indonesian ethnic languages, i.e.,Javanese and Sundanese, are available in GoogleTranslate service alongside the official language,Indonesian (Nasution et al., 2018; Nugroho, 2005).

It is unlikely that Google Translate can providethe rest of Indonesian ethnic languages in the nearfuture, since the available corpora for Indonesianethnic languages are still scarce. In order tobridge the gap between high-resource languages and

low-resource languages, in this case between Englishand Minangkabau, a quicker approach is to createan English-Minangkabau PHMT with Indonesianas the pivot. Since Minangkabau has 61.59%lexical similarity with Indonesian based on ASJP,the morphology and syntax are similar. Therefore,Indonesian-Minangkabau word-to-word translation isexpected to be acceptable.

2.3 Language Grid

Toru Ishida (2018) mentioned that globalizationincreasingly demands multilingual communicationon the Internet, as well as in local communities.To create customized collaboration tools to supportmultilingual communities, the Language Grid wasestablished ten years ago. It has been improvingweb-based services to communities throughout theworld by providing highly adaptable infrastructureand access to a wide variety of language resourcesand services (Ishida et al., 2018; Nasution et al., 2017;Nasution, 2018).

3 RESEARCH METHOD

3.1 System Overview

Based on the results of the research analysis, itcan be concluded that the Augmented reality-basedTranslating Machine has two criteria. ThisAugmented reality-based Translating Machine caninteract with users by translating text from Indonesianinto English and vice versa, and by displayingsound as the result of translation and animated 3Dcharacters. Augmented reality-based TranslatingMachine is markerless, which means that it does notuse printed markers to display 3D animation models.

Figure 1 explains the bird view of process frominput in the form of text to output in the form ofanimation object and speech translation results.

Figure 1: Whole System Overview.


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3.2 Interactive Words

Interactive is a matter related to two-waycommunication or something that is mutuallyacting, active and interconnected and has reciprocitybetween one another (Warsita, 2008). In thissystem, the word “interactive” is classified into twocategories, namely special and general. When auser types a word in the application, the word willbe matched to the database. If it is in the database,the 3-dimensional character will say an interactiveword consisted in a special interactive word tablerandomly. Otherwise, if the word typed by the userdoes not exist in the database, the 3-dimensionalcharacter will utter an interactive word consistedin a general interactive word table randomly. Inthis system, the interactive word consists of twolanguages, Indonesian and English.

Examples of general and specific interactivewords can be seen in the following Table 1.

Table 1: Chatbot Corpus

Category Keywords #RandomStatement

Foodfried rice, meatball,fried chicken, fried

potatoes, egg

3 for eachkeyword

Color red, yellow, green,blue, white

3 for eachkeyword

Animal chicken, goat, cow,cat, dog

3 for eachkeyword

Transportation plane, car, motorcycle,bike, train

3 for eachkeyword

Fruit grape, apple, banana,mango, pineapple

3 for eachkeyword

General None 5

3.3 Flowchart

In this study, the design of the application used aflowchart in order to show the workflow done bythe system as a whole. In general, the flows of theapplication ofAugmented Reality-Based TranslatingMachine were as follows:

The flow diagram of the application of augmentedreality-based Translating Machine can be seen inFigure 2 and Figure 3.

The flows of the system of an interactive machinebased on augmented reality can be explained asfollows:

1. The user inputs the text.

2. The text is checked in the database.

Figure 2: System flowchart (Augmented reality part).

Figure 3: System flowchart (Language translation part).

3. If the text is in a special interactive database, thesystem would produce an interactive word outputin a form of a text.

4. If the text does not exist in a special interactivedatabase in the previous stage, the systemwould access the general interactive database andgenerated output from general interactive wordsin form of text randomly.

5. The output of interactive words is sent to the textto speech API to be changed into sound.

6. Character says the word or sentence to the user asoutput.

The information about the system flow for


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the interactive word of Augmented reality-basedTranslating Machine can be seen in Figure 4.

Figure 4: Interactive Word System Flowchart.

3.4 How the Application Works

This Augmented reality-based Translating Machineutilizes a markerless technique, which means thata marker used to display 3D characters has notbeen registered since the application making. Theapplication will search and mark locations in thecamera area as markers, and the location is listed asa marker to display the model of 3D characters. Anoverview of how the application works can be seen inFigure 5.


The following is the interface of the application ofaugmented reality-based machine translation.

Figure 5: Application Interface

Figure 5(a) is a picture before the user presses the

image button and Figure 5(b) is a picture after the userpresses the image button.

In this subchapter, we discuss the results of theapplication testing that has been made. Some of thetests that have been carried out include light intensitytesting, viewing angle testing, distance testing,markerless detection location testing, translationtesting, and interactive word testing.

4.1 Black Box Testing Scenarios

Black box testing on the application of augmentedreality translating machine was conducted to test eachfunction of the interface input in the application,in order to know whether the interface input wasin accordance with the expected output. A blackbox testing result shows that all the system designedmatch to table 3.1 functionally work as expected.

4.2 Light Intensity Testing

Light intensity testing was conducted inside andoutside the room with different light intensities. Thistest was conducted to find out whether the applicationof augmented reality translating machine translatorcould track and display animated models at differentlight sources.

The conclusion of the test on light intensity can beseen in Table 2.

Table 2: Application test results against light intensity

TestCase

LightIntensity

WaitTime Result

TestResults

DaytimeOutdoor

230 lux 1 Second3D

Charactershowed

Success

OutdoorNightDay

28 lux 1 Second3D

Charactershowed

Success

Indoor 1130 lux 1 Second3D

Charactershowed

Success


Charactershowed

Success


Characternot showed

Notsuccessful

Based on the results of the light intensity testingin Table 2, it can be concluded that the applicationof machine translators cannot mark the location ortracking markerless if the light intensity is 0 lux. Inother words, the markerless method in Vuforia did notrequire light even if there was little tracking on thetarget.


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4.3 Distance and Angle Testing

The distance and angle testing was done to find outhow far and at what angle the markerless method onVuforia sdk displayed the 3D characters. This test wascarried out with bright light. The test was repeated ata minimum distance of 10cm with an angle of 10tothe farthest distance of 60cm at an angle of 90.

The results of testing distance and angle of thelocation can be seen in Table 3.

Table 3: Distance and Angle Testing

Action Testing Result TestResultsDistance Angle

10 cm 10 Character3D showed Success

60 Character3D showed Success

















Based on the data of the test results in Table3, it can be concluded that with a distanceof at least 10cm and an angle of 10, the

application of the translating machine is still abletodisplay 3-dimensional characters well, and thetranslating machine application is still able to display3-dimensional characters properly with the furthestdistance testing of 60 cm with a taking angle of60and 90.

4.4 Types of Tracking Object Testing

Testing the types of tracking object with themarkerless method was carried out to find out the bestobject or place in marking the location by Vuforia sdkusing the markerless technique. This test was carriedout with 3 types of objects.

The conclusion of the overall results of testing thetypes of tracking object can be seen in Table 3. Basedon the testing conducted on the tracking object, it canbe concluded that Vuforia sdk using the markerlessmethod cannot be used on all tracking object fieldsas listed in Table 3. It is because if the object lacks ofimage features, the 3D characters will not appear eventhough the light and color on the object are sufficient.

4.5 Evaluation

The evaluation was performed by givingquestionnaires to 20 people, in order to find outthe responses from users about the application ofaugmented reality-based translating machine. Theresults of the evaluation after giving questionnairesto 20 respondents can be seen in Table 4.

Table 4: Correspondent Percentage

Correspondent PercentageExcellent Very Good Good Not Good

4 15 1 0

Overall, the results of the questionnaire werecalculated by using the tabulation formula to getthe results of the percentage of each answer tothe questionnaire. Each of these percentages is asfollows:

1. Excellent : 4/20*100% = 20%

2. Very Good : 15/20*100% = 75%

3. Good : 1/20*100% = 5%

4. Not good : 0/20*100% = 0%

5 CONCLUSIONS

The research and the design of the application ofaugmented reality-based translating machine have


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been successfully implemented and a series of testshave been conducted to test the capabilities of theapplication and the following results are obtained.The application can be used as a reference in learningword pronunciation and translation from English intoIndonesian and Indonesian into English. However,it cannot track well if there is no light. It alsocannot display the 3-dimensional characters if thereare few details on the marker. The minimum distanceto obtain good results in displaying 3-dimensionalcharacters is 10cm from the marked location point.At a distance of 60cm with taking angles above 10to90, the application still can display 3-dimensionalcharacters properly. The application can be used bothoutdoors and indoors.

REFERENCES

Dewantara, I. M. A. Y., Crisnapati, P. N., Kesiman,M. W. A., and Darmawiguna, I. G. M. (2013).Augmented reality book pengenalan gerak dasar taribali. Kumpulan Artikel Mahasiswa Pendidikan TeknikInformatika (KARMAPATI), 2(8):1022–1028.

Dikdok (2017). Naikan kemampuan google translatehadirkan neural machine translation untuk banyakbahasa, jurnal apps.

Efendi, I. (2014). Pengertian augmented reality. Diambilkembali dari it-jurnal: http://www. it-jurnal.com/2014/05/Pengertian-Augmented-Reality-AR.html.

Ishida, T., Murakami, Y., Lin, D., Nakaguchi, T., and Otani,M. (2018). Language service infrastructure on theweb: the language grid. Computer, 51(6):72–81.

Mariani, H. T. and Ananta, M. T. (2017). Pengembanganaplikasi respons sms dan panggilan teleponmenggunakan android text to speech dan proximitysensor bagi pengemudi mobil. Jurnal PengembanganTeknologi Informasi dan Ilmu Komputer e-ISSN,2548:964X.

Nasution, A. H. (2018). Pivot-based hybrid machinetranslation to support multilingual communication forclosely related languages. World Transactions onEngineering and Technology Education, 16(2):12–17.

Nasution, A. H., Murakami, Y., and Ishida, T. (2018).A generalized constraint approach to bilingualdictionary induction for low-resource languagefamilies. ACM Transactions on Asian andLow-Resource Language Information Processing(TALLIP), 17(2):9.

Nasution, A. H., Syafitri, N., Setiawan, P. R., and Suryani,D. (2017). Pivot-based hybrid machine translationto support multilingual communication. In 2017International Conference on Culture and Computing(Culture and Computing), pages 147–148. IEEE.

Nugroho, A. (2005). Analisis dan perancangan sisteminformasi dengan metodologi berorientasi objek.Bandung: Informatika.

Pangestika, G. V., Wikusna, W., and Suryadi, A. H. (2017).Aplikasi pembelajaran bahasa inggris untuk muridsekolah dasar berbasis android. eProceedings ofApplied Science, 3(3).

Panggabean, H. (2016). Urgensi dan posisi bahasainggris di indonesia. Universitas Methodist Indonesia,Medan.

Rahman, A., Ernawati, and Funny Farady, C. (2014).Rancang bangun aplikasi informasi universitasbengkulu sebagai panduan pengenalan kampusmenggunakan metode markerless augmented realityberbasis android. Jurnal Teknik Informatika, 7(2).

Saputra, Y. A. and Indonesia, T. (2014). Implementasiaugmented reality (ar) pada fosil purbakala dimuseum geologi bandung. Jurnal Ilmiah Komputerdan Informatika (KOMPUTA), 1:1–8.


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The Community Perception of Traditional Market Services in PekanbaruCity, Riau Province

Puji Astuti, Febby Asteriani, Eka Surya Pratiwi and Thalia Amanda PutriDepartment of Urban and Regional Planning, Universitas Islam Riau, Pekanbaru, Indonesia

pujiastutiafrinal,[email protected], [email protected], [email protected]

Keywords: Community Perseption, Level of Satisfaction, Modern Market, Traditional Market.

Abstract: The market existence is one of the most apparent indicators of economic activities.The increasing of modernmarket development in Pekanbaru cause changing public perception in shopping activity on the use of tradi-tional market facilities. The study purpose is identify community perception of trading facilities on tradisionalmarket to formulate policies relating to improving market services to the community. The analysis techniqueused quantitative descriptive analysis. Its analyzing the level of customer satisfaction and assessment of servicecondition; complete and price certainty of goods, market comfort, market cleanliness, availability of facilities,and market security. For traditional market services measured from sellers politeness, sellers readiness andsellers friendliness. Based on research concluded the level of customer satisfaction in the traditional marketsis not satisfactory and assessment of service conditions is satisfactory.

1 INTRODUCTION

The traditional market is a traditional selling place(hereditary), where the sellers and buyers meet, thegoods traded are dependent on the request of thebuyer (consumer), the price set is the agreed pricethrough a bargaining process, the trader as a produceroffers little above the standard price. In general, tra-ditional markets are places for selling basic needs.Usually traditional markets are active within certaintime limits, such as morning markets, afternoon mar-kets, weekend markets and so on. Traditional marketscan be managed by the government or the private sec-tor, the available facilities consist of wards, booths,warehouses, shops, booths / kiosks, public toilets andothers around traditional markets. In the traditionalmarket, the buying and selling process takes place hu-manely and communicates with high family values.

Traditional market as a city infrastructure thatmust be managed regularly and continuously, its con-dition is highly marginalized by the existence of amodern market with its complete facilities and ser-vices. Traditional markets, most of which are admin-istered by the government, serve the segmentation ofmiddle-lows with inappropriate physical conditionssuch as slum, muddy, crowded, etc (Linda, 2008;Witell et al., 2011). Traditional markets are one ofthe important sectors that support the people’s econ-omy, the interests of small people to the upper mid-

dle class are accommodated (Wardoyo, 2009). Tra-ditional markets are places where sellers and buyersmeet and are marked by transactions of sellers andbuyers directly.

Based on data released by the Association of In-donesian Market Traders (APPSI) in 2005, the growthof traditional markets was 8.01%, while the growth ofthe modern market was 31.4% per year. The condi-tion of traditional markets is increasingly marginal-ized with the existence of a modern market with com-plete facilities and services. Presidential Regulationof the Republic of Indonesia No. 112 of 2007 con-cerning the Arrangement and Development of Tradi-tional Markets, Shopping Centers and Modern Storeswhich were followed up by the Minister of Trade Reg-ulation of the Republic of Indonesia No.53 / M-DAG/ PER / 12/2008 concerning the Guidelines for the Ar-rangement and Development of Traditional Markets,Shopping Centers and Modern Stores is a manifesta-tion of the government’s response to the conditionsof competition that occur between traditional mar-kets and modern markets. These regulations regulatea number of important matters, including the rulesfor the provision of compulsory facilities for tradi-tional and modern shop markets, location and licens-ing rules, sales system rules and working hours, tothe rules of partnership with suppliers. Rules regard-ing gradual administrative sanctions also apply to vi-olations, ranging from written warnings, freezing to

Astuti, P., Rosadi, S., Asteriani, F., Pratiwi, E. and Putri, T.The Community Perception of Traditional Market Services in Pekanbaru City, Riau Province.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 169-174ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

169

revocation of business licenses(Dasgupta et al., 1994;Bangia et al., 2008).

The recent development of Modern Markets andModern Stores in Pekanbaru City has increasedrapidly, resulting in the emergence of various publicperceptions in conducting shopping activities. Thelimitation of traditional markets in facilitating thecompleteness of facilities and infrastructure is an im-portant issue in shifting community behavior in shop-ping activities. This behavior is in the form of con-sumer perceptions in terms of shopping satisfactionand an assessment of traditional market service con-ditions.

The customer’s perception of the quality of a ser-vice and overall satisfaction has several indicators /instructions that must be provided. Traders may smilewhen they talk about goods or services, they mightsay good things about goods or services. A smile isproof that someone is satisfied, frowning instead re-flects disappointment. Both of the above smile andsay good things are manifestations or indicators of aconstruct called customer satisfaction. Satisfaction isthe level of one’s feelings after comparing the per-formance / results they feel with their expectations.While according to (Kotler, 2002) satisfaction is afeeling of pleasure or disappointment someone whoappears after comparing between perceptions / im-pressions of the performance (or results) of a prod-uct and its expectations. The level of satisfaction is afunction of the difference between perceived perfor-mance and expectations. If the performance is belowexpectations, the customer will be disappointed. Ifperformance is in line with expectations, customerswill be satisfied. Whereas if the performance exceedsexpectations, customers will be very satisfied. Cus-tomer expectations can be shaped by past experiences,comments from relatives and promises and market-ing information and things. Satisfied customers willbe longer, less price sensitive and have good com-ments. To create customer satisfaction, it must createand manage a system to obtain more customers andthe ability to retain customers (Hill, 1966; Price et al.,2015).

According to Sari (2011) to assess the level ofcustomer satisfaction and assessment of market ser-vice conditions can be seen from the completenessof goods, certainty of the price of goods, quality ofgoods, market convenience, market cleanliness, fa-cilities and market security. As for the assessmentof market service conditions, it can be seen from thecourtesy of traders, merchant alertness and merchanthospitality. To realize a clean, safe and comfortabletraditional market. Need to be supported by the avail-ability of good facilities and infrastructure. Facilities

are supporting facilities that function for the imple-mentation and development of economic, social andcultural life, such as parking facilities, health facili-ties, facilities of worship. Infrastructure is a completephysical environment that allows the market environ-ment to function properly, such as landfills, drainagenetworks, sewerage drains, signs.

2 RESEARCH METHODS

Perception is the presumption of something or a cer-tain social condition based on the social constructioncreated in the community. Perception is an experi-ence or assessment of objects, events, or relationshipsthat are obtained by deducing information or convey-ing messages (Hariyono, 2007). The market which isthe center of the crowd is perceived by everyone dif-ferently. As a means of shopping for the community,the market is able to create perceptions of each visitorabout their own functions and benefits. The results ofthis study will explore the perception of communityshopping in the use of trade facilities in PekanbaruCity.

The purpose of this study is to determine the pub-lic perception of traditional market services in Pekan-baru City. The scope of the area in this study is the ad-ministrative area of Pekanbaru City consisting of tentraditional markets managed by the Pekanbaru CityMarket Service (Pekanbaru, 2013b), namely:

• Sukaramai Market in Jendral Sudirman Street,Pekanbaru Kota District

• Inpres H. Agussalim Market in H. AgussalimStreet, Pekanbaru Kota District

• Senapelan Market in Jendral Ahmad Yani Street,Sukajadi District

• Limapuluh Market in Sultan Syarief Kasim Street,Limapuluh District

• Bawah Market in Saleh Abbas Street, SenapelanDistrict

• Sail Market in Hangtuah Street, Sail District

• Rumbai Market in Kayangan Street, Rumbai Pe-sisir District

• Labuh Baru Market in Durian Street, Labuh BaruDistrict

• Simpang Baru Market in Soebrantas Street, Tam-pan District

• Cik Puan Market in Tuanku Tambusai Street,Sukajadi District


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The approach used in this study uses descriptiveresearch methods by identifying object of researchthrough a description, understanding or explanationof the analysis that is measurable or not measurable.The field survey was carried out by distributing ques-tionnaires to the public/buyers on traditional marketsthat were carried out in the morning at 06.00 am until12:30 am on April 8-23, 2015. The hours were chosenbecause the majority of traders sell and make buyingand selling transactions to buyer at this time.

The sampling technique used is accidental sam-pling. According to Sugiyono (2010) accidental sam-pling is a technique of determining samples based onchance, that is, anyone who accidentally meets witha researcher can be used as a sample, if the personwho happened to be found is suitable as a data source.According to (Arikunto, 2002) the determination ofsampling is if less than 100 is better taken all untilthe research is population research. If the number oflarge subjects can be taken between 10-15% or 20-55% or more depending on the ability of researchersrelated to time, energy and funds, the area of observa-tion of each subject because it involves a lot of funds,and the size of the risk by researchers. The number ofsamples to be studied is calculated using the Slovinformula (Sangaji, 2010):

n =N

1+Ne2 (1)

n = sample sizeN = population sizee = critical value (accuracy limit) desired (0-10%)

According to data obtained from PekanbaruCentral Statistics Agency (BPS) (Pekanbaru, 2013a),the population of Pekanbaru in 2013 was 999,031people. Then the amount is calculated into the Slovinformula with an estimated error of 6% so that it canbe known as follows:

n = 999.0311+999.031(6%)2

n = 999.0311+9943(0.06)2

n = 999.0313597.5

n = 277,7400 = 278 people

Based on these calculations the total number ofsamples to be taken is 278 respondents, then for 8traditional markets consists of 28 respondents and 2markets with 27 respondents. Distribution of ques-tionnaires was conducted in ten traditional markets inPekanbaru City. In carrying out this research, data

collection techniques carried out were the distributionof questionnaires or interviews directly with respon-dents, observations or direct observations in the fieldto find out market conditions to traders, and documen-tation. To collect data in this study follows variablesand indicators that have been extracted from theoriesabout traditional market services as presented in Table1.

Table 1: Research Variables

Research Ob-jectives

Variables Indicators

Identify thelevelof customersatisfaction intraditionalmarkets

Identificationof availabil-ityand condi-tionof facilitiesandinfrastructure

1. Completenessof goods2. Price Certainity3. Quality ofGoods4. Market Conve-nience5. Market Cleanli-ness6. Complete Facil-ities7. Security

Identify as-sessments oftraditionalmarket serviceconditions.

Identificationof the roleof mar-ket traderstowardsconsumers

1. Courtesy ofmerchants2. Efficacy oftraders3. Hospitality oftraders

Field surveys are carried out by distributing ques-tionnaires to the public / buyers. In traditional mar-kets, this research was conducted in the morning at06.00 WIB until 12.30 WIB on April 8-23, 2015. Thehour was chosen because the majority of traders selland buy and sell transactions to buyers at that hour.


3.1 Distribution of Traditional Marketsin Pekanbaru City

Placement of market location will affect the rangeof market services for users. Market placement willalso affect the perceptions of community shopping.Pekanbaru City is a city with a population of 999,031people. To fulfill their daily needs, the communityconducts buying and selling activities in traditionalmarkets. Pekanbaru City has ten traditional marketsunder the management of the Pekanbaru City Govern-ment, especially the Pekanbaru City Market Service.

The Community Perception of Traditional Market Services in Pekanbaru City, Riau Province

171

Figure 1 is the distribution of traditional markets inPekanbaru City.

Figure 1: Distribution of Traditional Markets Location inPekanbaru City

3.2 Characteristics of Respondents

The majority of consumers or respondents are female(84.98%) are on average over 30 years old (75.54%).The biggest traditional market user is housewife of60.43%. The population of Pekanbaru City consistsof Malays, Minang, Javanese, Batak Tribe, the re-maining various other tribes. Traditional market con-sumers are dominated by Malays (48.92%) and Mi-nang (32.37%) with the largest number of familymembers owned by consumers (1-5.75%). The in-come of visitors/buyers in traditional markets is be-tween Rp. 1,000,000 - 2,900,000 (92.81%) and grad-uated from senior high school (57.19%).

3.3 Identification of ConsumerSatisfaction Levels in TraditionalMarkets

Based on the answers of 278 respondents in all tra-ditional markets in Pekanbaru City, for completenessof the items respondents chose 75.54% at the satis-fying level. This is because the fulfillment of all theneeds of consumers in buying all their needs. For cer-tainty of the price of goods, highest percentage is at57.55% where respondents choose unsatisfactory, thisis contrary to the characteristics of traditional mar-kets, where in the process of bargaining is createdwhich has no fixed price but consumers here pro-vide sufficient ratings high for certainty of the priceof goods. This is because the average price agreedupon by the respondents with all the traders on themarket is almost the same, so the respondents choseuncertain price.

The level of consumer satisfaction on the qualityof goods can be seen with the highest percentage of

respondents satisfying with a value of 76.98%, wherethe respondents rated the basic needs here as havinggood quality because basic goods always change withnew and fresh goods fresh supplied from West Suma-tra Province and North Sumatra Province. For marketconvenience the highest percentage of 70.86% of re-spondents voted unsatisfactory because respondentsrated traditional markets on busy days visitors feltvery hot and jostling which resulted in inconvenience.

The level of customer satisfaction on marketcleanliness, the respondents chose 57.55% to be un-satisfactory. This happened because respondents con-sidered the cleanliness of the traditional market wasfar from being adequate or satisfying, it was muddyand smelly. However, in some traditional markets,cleanliness has been regularly managed, although itstill needs to be improved. For complete facilities thehighest percentage is unsatisfactory with a value of50.00%. This reflects the still many unsatisfactorymarket facilities that can even be said to be inade-quate. This is one of the weaknesses of the traditionalmarket. The level of consumer satisfaction with mar-ket security, respondents chose 51.08% to be unsatis-factory. This proves that there is still a lack of marketsecurity felt by the respondents, especially the veryvulnerable cases of pickpocketing.

Figure 2: Graph of the Level Satisfaction of Consumer inTraditional Market, Pekanbaru City

3.4 Assessment of the Conditions ofService of Traditional Markets

The service quality of market facilities will providecomfort to consumers who will come to shop. Factorsthat become elements of service include courtesy ofmerchants, merchant alertness and merchant friendli-ness. Table 3 shows the community’s assessment oftraditional market services in Pekanbaru City.

Based on the answers of 278 respondents whowere in all traditional markets in Pekanbaru, the as-sessment of the courtesy of traders in doing service,the highest percentage was in the satisfactory choice


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Table 2: Level of Satisfaction of Traditional Market Consumers in Pekanbaru City

SL

Answer

VNS NS S VS

A % A % A % A %

CG 4 1.44 22 7.91 210 75.54 42 15.11

PC 22 7.91 160 57.55 91 32.73 5 1.8

QG 1 0.36 41 14.75 214 76.98 22 7.91

MC 17 6.12 197 70.86 61 21.94 3 1.08

C 28 10.07 160 57.55 87 31.29 3 1.08

CF 12 4.32 139 50 119 42.81 8 2.88

MS 11 3.96 142 51.08 123 44.24 2 0.72Note:

A: Amount; SL: Satisfaction Level; CG: Completeness of Goods; PC: Price Certainty; QG: Quality of Goods; MC: MarketConvenience; C: Cleanliness; CF: Complete Facilities; MS: Market Security; VNS: Very Not Satisfying; NS: Not Satisfying;

S: Satisfying; VS: Very Satisfying

Table 3: Assessment of Traditional Market Services in Pekanbaru City

ASC

Answer

VNS NS S VS

A % A % A % A %

CM 4 1.44 21 7.55 174 62.59 79 28.42

ET 5 1.8 18 6.47 185 66.55 70 25.18

HM 3 1.08 12 4.32 181 65.11 82 29.5Note:

A: Amount; ASC: Assessment of Service Conditions; CM: Courtesy of Merchants; ET: Efficacy of Traders; HM: Hospitalityof Merchants; VNS: Very Not Satisfying; NS: Not Satisfying; S: Satisfying; VS: Very Satisfying

Figure 3: Traditional Market Services Assessment Graph inPekanbaru City

of 62.82%. This is because the traders are quite politein serving the respondents and there is an interactionthat creates intimacy between the traders and buyersand the traders use neat clothes, good words and al-ways give a smile to the buyers. the results of the per-centage to satisfy are quite high at 66.43%. Respon-dents considered that when the respondents came tothe outlets or kiosks of the merchants, they were swift

and deft in welcoming and explaining the items avail-able and had a quick response in serving the buyers.

Friendly is one way to attract customers or buy-ers. This is what traders on the market do. So thatprospective buyers want to buy where they sell. Theassessment of merchant friendliness in service to con-sumers is at a satisfactory level of 64.98%, wherethe respondents are satisfied with the hospitality thatoccurs due to direct interaction between sellers andbuyers. The hospitality of the merchants was feltby consumers when the respondents passed the shopsor shops of the merchants, where they immediatelygreeted the respondents to be able to stop by wherethey were selling. The hospitality of traders is able toprovide a sense of family and comfort to the respon-dents or buyers.

4 CONCLUSIONS

Based on the research, the conclusions are as follows:

• The distribution of traditional markets in Pekan-baru City is in close proximity to the city center.

The Community Perception of Traditional Market Services in Pekanbaru City, Riau Province

173

• The level of community satisfaction with com-pleteness, quality, safety, cleanliness and comfortrelated to the condition of traditional markets inPekanbaru City is in a condition that is not satis-factory and has not met expectations of the com-munity.

• Community assessment of the merchant condi-tions services has met criteria expected by thecommunity.

ACKNOWLEDGEMENTS

This research was supported by Departement of Ur-ban and Regional Planning, Faculty of Engineering,Universitas Islam Riau. We thank our colleagues fromPekanbaru City Governement who provided insightand expertise that greatly assisted the research, al-though they may not agree with all of the interpre-tations/conclusions of this paper.

REFERENCES

Arikunto, S. (2002). Prosedur Penelitian Suatu PendekatanPraktek.

Bangia, A., Diebold, F. X., Schuermann, T., and Stroughair,J. (2008). Modeling liquidity risk with implicationsfor traditional market risk measurement and manage-ment.

Dasgupta, C. G., Dispensa, G. S., and Ghose, S. (1994).Comparing the predictive performance of a neu-ral network model with some traditional market re-sponse models. International Journal of Forecasting,10(2):235–244.

Hariyono, P. (2007). Sosiologi Kota untuk Arsitek.Hill, P. (1966). Notes on traditional market authority and

market periodicity in west africa. The Journal ofAfrican History, 7(2):295–311.

Kotler, P. (2002). Manajemen Pemasaran, Edisi Millenium,Jilid 2.

Linda, E. Y. (2008). Persepsi Masyarakat TerhadapPelayanan Fasilitas Pasar Kota Batu.

Pekanbaru, B. P. S. P. K. (2013a). Kota Pekanbaru dalamAngka Tahun 2013. Pekanbaru, BPS Kota Pekanbaru.

Pekanbaru, D. P. K. (2013b). Ekspose Profil Dinas Pasar.Price, R. A., Wrigley, C., and Straker, K. (2015). Not just

what they want, but why they want it: Traditionalmarket research to deep customer insights. Qual-itative Market Research: An International Journal,18(2):230–248.

Witell, L., Kristensson, P., Gustafsson, A., and Lofgren, M.(2011). Idea generation: customer co-creation versustraditional market research techniques. Journal of Ser-vice Management, 22(2):140–159.


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Separation of Crude Oil and Its Derivatives Spilled in Seawater by usingCobalt Ferrite Oxide

Mohammed A. Samba1, Ibrahim Ali Amar2, Musa Abuadabba1, Mohammed A. ALfroji1, Zainab M.Salih1 and Tomi Erfando3

1Department of Oil and Gas , Faculty of Energy and Mining Engineering, Sebha University, Sebha, Libya2Department of Chemistry, Faculty of Science, Sebha University, Sebha, Libya

3Department of Petroleum, Universitas Islam Riau, Pekanbaru, Indonesiamoh.samba, [email protected], [email protected], [email protected],


Keywords: Magnetic Cobalt Ferrite Oxide Nanoparticles, Oil Spills, Sea Water.

Abstract: Oil spills can cause a wide range of impacts in the marine environment and are often portrayed by the mediaas ’environmental disasters’ with dire consequences predicted for the survival of marine flora and fauna. Thepurpose of this paper is to study the possibility of using spinel oxide (CFO) as an oil absorbent materialwith the aim of removing crude oil and its derivatives from aqueous solutions. Spinel oxide from cobaltferrite nanoparticles with formula CoFe2O4 (CFO) was prepared by sol-gel method. Functional groups werealso identified on the surface of the oxide using the infrared spectrum (FTIR). In addition, crude oil and itsderivatives were diagnosed using FTIR, and the density and viscosity of crude oil and its derivatives at 15

C temperature. In this study, three samples of seawater were used from different Libyan regions (GemensSeawater, Abo Sitta Port, Elbrega Anchorage), and Two samples of crude oil were used from different Libyanfields (Light, Medium). The samples of crude oil used at three different concentrations (0.01g, 0.03g, 0.05g).However, the oil removal was calculated for different scenarios as gm / gm and as percentage. The oil removalcapabilities of the prepared absorbent were found to be 10.966 2.3651 g/g to 4.5426 ± 0.113 g/g, 31.8333 ±5.324 g/g to 7.02053 ± 1.1271, 14.7333 ± 3.1988 g/g to 6.01 ± 0.1287 g/g, 47.1033 ± 6.0222 g/g to 9.2122± 2.8177, 10.8833 ± 2.1840 g/g to 4.5786 ± 0.1921 g/g, 42.96 ± 1.4046 g/g to 10.5020 ± 1.3172 g/g forGemmens Seawater (light oil), Gemmens Seawater (medium oil), Port Abu Sitta (light oil), Port Abu Sitta(meduim oil), Elbrega Anchorage (light oil) and Elbrega Anchorage (medium oil), respectively. The resultssuggest that the prepared magnetic nanoparticles can be used as absorbent materials for removing oil spillsfrom sea water especially at medium oil.

1 INTRODUCTION

Environmental pollution is the pollution of air, landand water in many ways. There are several reasonsfor environmental pollution, such as from agricul-ture and industry. Environmental pollution has dras-tically changed the air, water and terrestrial ecosys-tems as a result of the industrial revolution in Europe,North America and China in the 19th century. More-over, different types of toxic gases and different formsof carbon components were produced from factories,transport, and energy sectors has resulted in differentchanges in the global climate and weather patterns,and become a source of contamination of land, as wellas the ocean environment where the average temper-ature and acidity are increasing. In addition, many

other chemicals like fertilizers used in the agriculturalindustry also contribute to the pollution of the seasover vast areas (Fartoosi and M., 2013).

Oil spills can have devastating effects on water-ways and oceans. In the oil it is the polycyclic aro-matic hydrocarbons (PAHs) that cause most of thetoxicity for human life, but the physical nature of oil,i.e. the stickiness is a major problem for a number oforganisms such as birds. Spills of oil has a numerousnegative impacts both short and long term, resultingin economic and financial losses. Also, the recover-ing and clean-up processes are very costly; see forexample cases such as the clean-up from the ExxonValdes or the Deep Water Horizon (Fartoosi and M.,2013). Oil spills could be removed through manymethods such as mechanical, chemical and treatment

Samba, M., Amar, I., Abuadabba, M., Alfroji, M., Salih, Z. and Erfando, T.Separation of Crude Oil and Its Derivatives Spilled in Seawater by using Cobalt Ferrite Oxide.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 175-181ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

175

by burning in situ, this study will include a part of thechemical methods spinel oxide nanoparticles (mag-netic spinal compounds).

1.1 Magnetic Spinel Compounds

The mixed transition elements of the general formulaAB2O4 are called spinel’s. These oxides take theirname from spinel metal (MgAl2O4). A is a binaryion (Fe2 +, Co2 +, Ni2 +, Zn2 +, Mg2 +, etc.), while Bis a trivalent ion (Fe3 +, Co3 +, Cr3 +, Al3 +, Mn3

+, etc. ) (Smart, ). Spinel oxides are among themost important magnetic nanomaterial’s. Spinel fer-rite, SF Magnetic nanoparticles are spinel oxides con-taining tri-iron ions. These oxides have the generalformula M2+ Fe3 + O4 (Where M2 + represents Mn2

+, Fe2 +, Co2 +, Ni2 +, Zn2 +, Mg2 + etc.). Theseoxides have distinct chemical and physical properties(Reddy, 2016). Excellent magnetic properties, Largesurface area, its surface has a large number of effec-tive sites, high chemical stability, easy to prepare andconvert to the desired shape (Smart, ; Gomez-Pastoraet al., ).

Spinel oxides has wide applications in severalfields including: gas sensors, magnetic devices, wa-ter purification, medicine, catalysts, recharging bat-teries and ammonia production by electric stimulation(Amar, 2014), as shown in figure 1.

In the field of water treatment, spinel nano-magnetic nanoparticles on the list of materials canbe used as absorbent materials, because it can be re-moved quickly and easily from the solution after ab-sorption using an external magnetic field, after sepa-rating the pollutants can be removed and reused sev-eral times, Water Purification.

2 MATERIALS AND CHEMICALS

CoFe2O4 were used in this study. Seawater three sam-ples were used after routine testing and distilled water.Light and Medium crude oil were also used with (den-sity: 0.8245, API: 40, viscosity: 5.6136 and Boris3.5915 @ 25 C and @ 37.5 C, Sp.Gr @ 60/60Fo:0.8249) for light. While the (density: 0.8368, API:37.5, viscosity: 19.5970 and Boris 9.7102 @ 25

C and @ 37.5 C, Sp.Gr @ 60/60 Fo:0.8372) formedium.

2.1 Cobalt Ferrite Oxide NanoparticleParticles (CoFe2O4)

The magnetic spinal Cobalt ferrite oxide powder wasprepared 10 gm from magnetic spinal Nanoparticle

Figure 1: Some applications of spinel ferrite oxides (Amar,2014)

formula CFO )COFe2O4 (by Sol-gel method (Amaret al., 2018), and The required quantities of cobaltnitrate (12.4041g) and iron nitrate (34.4369g) wereweighed, Then add it in a small amount of distilledwater. Then add citric acid in amount of (36.8486g)and EDTA in amount of (37.34g) as complication fac-tors, the ammonia solution (NH3.H2O) was added topH control to 6, The solution was then evaporated us-ing an electric heater with the solution moving contin-uously by a magnetic mold to distribute heat. And bycontinuously heating and stirring solution (mixture)to thick black gel, the magnetic stirrer was then re-moved and the gel left on the electric burner com-pletely burned and turned into a solid component(ash), The component was milled solid obtained andplaced in ceramic seals and burned in the air in thefurnace at 600 C for 2 hours to remove the remainingorganic compounds and obtain a pure phase of pow-der (Cobalt ferrite oxide), which will later be used as amaze material to remove the blue methylene dye fromits solutions water. Figure 2 Shows the procures toprepare the spinal oxide (Scheffe et al., 2011; Scheffeet al., 2013).

2.2 Sea Water and Crude Oil

Three samples of seawater were obtained from dif-ferent parts of Libya, Tripoli, Benghazi and Al Bregaas shown in the figure 3. The parameters of seawa-ter were calculated at the Faculty of Science Univer-sity of Sebha, as shown in Table 1. Two samples ofcrude oil were collected from different fields of Libya(Light, Medium) As shown in the figure 4, Crude oilproperties were calculated at the Tripoli PetroleumResearch Center as shown in table 2.


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Figure 2: Steps of Preparation Spinal oxide

Figure 3: Shows seawater samples that used in this study

Figure 4: Shows oil samples that used in this study


3.1 FTIR Result

Functional groups on the surface of the spinel oxideprepared by the sol-gel method and then identified us-ing the infrared absorption spectrum (FTIR). The car-

Table 1: The Properties of seawater for three samples

TypeMarsa Sea

GminesMinaAbo-seta

al-Briga /Benghazi /TripoliConductivity (mc/cm) 183.9 186.7 180.7

pH 7.34 7.9 7.52

Salinity1222810 1314210 1132110(ppm)

Where:MC/CM = Milli Cemence/CentimeterPpm = Pond per Million

Table 2: The Properties of Crude Oil.

Test Method TestDescription UnitResult

X- field X-field

ASTM D 5002 Density @ 15CSp.Gr 60/60FAPI g/cc////

0.8368 0.8245

0.8372 0.8249

37.5 40

ASTM D 445

K.Viscosity@25C m 19.597 5.6136

[email protected]

m2/s 9.7102 3.5915

Where:ASTM = American Society for Testing And Material.K.Viscocity = Kinematic Viscocity Sp.Gr = SpecificGravity

bon nanotube (CFO) oxide after burning the ash com-pounds in preparation in air at 600C for two hours.Figure 5 shows the FTTR results for Nanoparticles,it is clearly seen that there are bundles of the termi-nals at 3968 cm-1 and 2928 cm-1; these packets canbe attributed to the Co-O and Fe-O bonds, respec-tively. These specialty packs are characteristic of allspinel oxides. Figure 6 and figure 7 have shown theFTTR results for different oil type, where the range ofwavenumber from 600 to 4000 cm-1.

Figure 5: FTIR results for nanoparticles

Separation of Crude Oil and Its Derivatives Spilled in Seawater by using Cobalt Ferrite Oxide

177

Figure 6: FTIR Results for light oil.

Figure 7: FTIR Results for medium oil.

3.2 Results of Oil Removal asgram/gram g/g

The technique of remove the oil from the sea water aby using magnetic rod has shown in the figure 8.

Figure 8: Shows the step of removal oil spot from watersurface (Amar et al., 2019)

The following equation for calculating the oil re-moved:

OR = (m2−m1)/m1 (1)

Where:OR=Oil Removal (gm/gm).m1= Concentration of the spinal (gm).m2= The weight of the spinal and oil (gm).

3.2.1 Gemmens Seawater

Figure 9,10 and table 3 display the gravimetric oil re-moval (OR, g/g) or the oil absorption capacity of thetested oily samples (light and medium) of GemmensSeawater as a function of absorbent amount. As canbe seen, in all cases the gravimetric oil removal ofGemmens Seawater decrease with the increase in theamount of the adsorbent from 0.01 to 0.05 g. In thecase of light oil (Figure 9), the OR decreased from10.966 ± 2.3651 g/g to 4.5426 ± 0.113 g/g as theamount of absorbent material. For the medium oil, theOR was about 31.8333 ± 5.324 g/g at the absorbentamount of 0.01 g and reached a value of 7.02053 ±1.1271 g/g when the absorbent amount increased to0.05 g (Figure 10).


Gemmens

Meduim Light

O.R

Concentrate

Sd O.R

Concentrate

Sd

31.8333 0.01 2.36 10.966 0.015.324

1.5565 13.8388 0.03 0.3967 5.6955 0.03

1.1271 7.2053 0.05 0.113 4.5426 0.05

Where:OR=Oil Removal.Sd=Standard Devition.

3.2.2 Port Abu Sitta

Figure 11,12 and table 4 display the gravimetric oilremoval (OR, g/g) or the oil absorption capacity ofthe tested oily samples (light and medium) of PortAbu Sitta Seawater as a function of absorbent amount.As can be seen, not all cases the gravimetric oil re-moval of Abu Sitta Seawater decrease with the in-crease in the amount of the adsorbent from 0.01 to0.05 g. In the case of light oil (Figure 11), the OR de-creased from 14.7333 ± 3.1988 g/g to 6.01 ± 0.1287g/g as the amount of absorbent material. For themedium oil, the OR was about 47.1033 ± 6.0222 g/gat the absorbent amount of 0.01 g and reached a valueof 9.2122 ± 2.8177 when the absorbent amount in-creased to 0.03 g, while 10.0593 ± 0.8987 g/g whenthe absorbent amount increased to 0.05 g (Figure 12).


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Figure 9: Shows The Crude Oil (Light) Concentration, OilRemoval Gemmens

Figure 10: Shows the Crude Oil (Medium) Concentration,Oil Removal Gemmens

3.2.3 Elbrega Anchorage

Figure 13,14 and table 4 display the gravimetric oil re-moval (OR, g/g) or the oil absorption capacity of thetested oily samples (light and medium) of Elbrega An-chorage Seawater as a function of absorbent amount.As can be seen, in all cases the gravimetric oil re-moval of Elbrega Anchorage Seawater decrease withthe increase in the amount of the adsorbent from 0.01to 0.05 g. In the case of light oil (Figure 13), the ORdecreased from 10.8833 ± 2.1840 g/g to 4.5786 ±0.1921 g/g as the amount of absorbent material. Forthe medium oil, the OR was about 42.96± 1.4046 g/gat the absorbent amount of 0.01 g and reached a valueof 10.5020 ± 1.3172 g/g when the absorbent amountincreased to 0.05 g (Figure 14).


PORT ABU SITTA

Medium Light

Sd O.R Concentrate Sd O.R Concentrate

6.0222 47.1033 0.01 3.1988 14.7333 0.01

2.8177 9.2122 0.03 1.598 6.8199 0.03

0.8987 10.0593 0.05 0.1287 6.01 0.05

Figure 11: Shows the Crude Oil (Light) Concentration, OilRemoval Port Abu sitta

Figure 12: Shows the crude oil (medium) concentration, oilremoval port Abu sitta

Figure 13: Shows the crude oil (light) concentration, oilremoval Elbrega Anchorage

Figure 14: Shows the crude oil (medium) concentration, oilremoval Elbrega Anchorage


179


Elbrega Anchorage

Medium Light

Sd O.R Concentrate Sd O.R Concentrate

1.4046 42.69 0.01 2.184 10.8833 0.01

2.5788 14.2086 0.03 0.6217 5.3132 0.03

1.3172 10.502 0.05 0.1921 4.5786 0.05

3.3 Results of Oil Removal asPercentage

The following equation for calculating the percent-age:

Remaining=((Woil+Powder)−Wremoval)/(Woil+Powder)(2)

OilRemovalPercentage = (1−Remaining)∗100 (3)

3.3.1 Gemmens Seawater

The highest percentage of oil removal was (52.73%)at the powder concentration (0.05gm) during the lightoil, when using the medium oil, the highest oil re-moval percentage was (79.43%) at the powder con-centration(0.03gm) as shown in the table 6.

Table 6: Shows the Oil Removal Percentage of GemmensSeawater

Gemmens

Light Medium

Concentration Percentage % Concentration Percentage %

0.01 24.65 0.01 60.92

0.03 33.74 0.03 79.43

0.05 52.73 0.05 65.09

3.3.2 Port Abu Sitta

When we use the light oil was the highest removed(66.69%), It was when the powder concentration(0.05gm), When using the medium oil was the highestremoval rate (91.1%), It was when the powder con-centration (0.05gm) as shown in the table 7.

Table 7: Shows the oil removal percentage of Abu Sitta port

Port Abu Sitta

Light Medium


0.01 32.41 0.01 89.25

0.03 46.41 0.03 54.81

0.05 66.69 0.05 91.1

3.3.3 Elbrega Anchorage

The light oil was the highest removed about (53.08%),It was when the powder concentration (0.05gm),When using the medium oil was the highest removalrate (93.1%), It was when the powder concentration(0.05 gm) as shown in the table 8.

Table 8: Shows the oil removal percentage of Abu Sitta port

Port Abu Sitta

Light Medium


0.01 25.17 0.01 82.79

0.03 37.47 0.03 80.92

0.05 53.08 0.05 93.1

4 CONCLUSION

The properties of iron oxide were studied and func-tional groups were identified using the infrared spec-trum. Two types of oil samples (Light and Medium)were used as water pollutants model. Within the ab-sorbent amount of 0.01 to 0.05 g, the gravimetricoil removal capabilities were between the 24.5% to93.1%. The obtained results suggest that Cobalt Fer-rite Oxide Nanoparticle might be promising absorbentmaterials and can be used for oil-spill cleanup fromSea water specially for medium oil.• The material must be milled enough to avoid

falling into the bottom of the test.• High-density raw materials must be heated when

aggregated in cold temperatures.• Apply experiments in large vessels for easy han-

dling with magnets and to contribute to the suc-cess of the experiment.

• A medium-sized absorbent should be used foreasy handling with the addition of oil.


180

REFERENCES

Amar, I. A. (2014). et al (2014). Electrochemical synthesisof ammonia from N 2 and H 2 O based on (Li, Na, K)2 CO 3Ce 0. 8 Gd 0. 18 Ca 0, 8(18).

Amar, I. A. et al. (2018). Synthesis and Characterization ofMagnetic CoFe1. 9Cr0.

Amar, I. A. et al. (2019). Oil spill removal from wa-ter by absorption on zinc-doped cobalt ferrite mag-netic nanoparticles. Advanced Journal of Chemistry-Section A (Theoretical, Engineering and AppliedChemistry), pages 266–385):.

Fartoosi, A. and M., F. (2013). The impact of maritimeoil pollution in the marine environment: case studyof maritime oil pollution in the navigational channelof Shatt Al-Arab.

Gomez-Pastora, J. et al. (2014).Reddy, D. H. K. (2016). Spinel ferrite magnetic adsor-

bents: alternative future materials for water purifica-tion? Coordination Chemistry Reviews.

Scheffe, J. R., Allendorf, M. D., Coker, E. N., Jacobs,B. W., McDaniel, A. H., and Weimer, A. W. (2011).Hydrogen production via chemical looping redox cy-cles using atomic layer deposition-synthesized ironoxide and cobalt ferrites. Chemistry of Materials,23(8):2030–2038.

Scheffe, J. R., McDaniel, A. H., Allendorf, M. D., andWeimer, A. W. (2013). Kinetics and mechanism ofsolar-thermochemical h 2 production by oxidation ofa cobalt ferrite–zirconia composite. Energy & Envi-ronmental Science, 6(3):963–973.

Smart, L. E. Solid state chemistry: an introduction. ThirdEdition.


181

Study of Open Space Utilization in Pekanbaru City, Riau Province

Mira Hafizhah T., Febby Asteriani, Danel Teguh P., Mardianto, Angelina Rulan S.Departement of Urban and regional Planning, Universitas Islam Riau, Pekanbaru, Indonesia

mirahafizhah, [email protected], [email protected], [email protected]

Keywords: City, Open Space, Public Area, Utilization.

Abstract: Public open space is a necessity for residents of Pekanbaru City and other big cities, with a variety ofcommunities and residents of Pekanbaru City certainly need public open space that is suitable for theircommunity needs, such as gathering, sports, recreation and so on. In addition to making the city neat, beautiful,beautiful, this also serves as a support for the city community to feel comfortable in their city, creating a happy,healthy, intelligent and active society. The purpose of study to know utilization of open space in pekanbarucity ecspesialy in MTQ area,Pekanbaru city park, urban forest andPlaza in the Great Mosque of An-Nur, Theanalysis technique used qualitative descriptive analysis.The result of questionnaire and interviewisOpen spacesin the city of Pekanbaru are used by visitors as a place to exercise, playground, recreation in distributing talentsor hobbies, trading and there are also those who use it as a culinary or snacking place that traders providearound the location of public open spaces. Most of the public or visitors to public open space use publicopen space as a place to exercise. The condition of public open space is generally good, comfortable, andmanagement is quite good. However, public open space facilities that still do not meet the needs of visitors,the condition of the facility also needs to be paid more attention, visitors prefer the location of public openspaces that are not far from where they live.

1 INTRODUCTION

Public open space is a necessity for residents ofPekanbaru City and other big cities, with a varietyof communities and residents of Pekanbaru Citycertainly need public open space that is suitable fortheir community needs, such as gathering, sports,recreation and so on. In addition to making the cityneat, beautiful, beautiful, this also serves as a supportfor the city community to feel comfortable in theircity, creating a happy, healthy, intelligent and activesociety(Pekanbaru, ; Budihardjo and Sujarto, 1999;Budihardjo, 2011).

The public open space needed by the peopleof Pekanbaru City is certainly a public open spaceequipped with supporting facilities or infrastructurein accordance with the function of the public openspace.Public open spaces in Pekanbaru City arespread in several Subdistricts in Pekanbaru City,while public open spaces in the urban scale inPekanbaru City are full MTQ areas in Bukit RayaDistrict, MTQ Park at Arifin Ahmad Road Crossingin Marpoyan Damai District, Polytechnic PlaygroundCaltex Riau in Rumbai District, Bandar LakeKayangan Lembah Sari in Rumbai Pesisir District,

Main Riau Stadium Area in Tampan Subdistrict,Urban Forest in Sail District, City Park, Plaza in theGreat Mosque of An-Nur, CFD on Diponogoro streetin Pekanbaru (Kuntjojo, 2009; Mulyandari, ; Woolley,2003).

2 LITERATURE REVIEW

Open space can be interpreted as undeveloped landor an environmental area designated as parks, roads,and natural destinations such as agricultural areas.(Mulyandari, ; Schmitt, 2004; Agboola et al.,2017).Public open space in Permendagri Number 1of 2007 concerning structuring green open spaces inurban areas, is spaces in a city or wider area, both inthe form of area / area and in the form of elongatedareas / lanes where the use is more open which isbasically without buildings.

3 RESEARCH METHODS

The research approach used in this study isthe inductive approach, starting from the desire of

182Hafizhah T., M., Asteriani, F., Mardianto and Rulan S., A.Study of Open Space Utilization in Pekanbaru City, Riau Province.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 182-187ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

researchers to give meaning to observational data inthe form of empirical generation (initial categories,assumptions, then become a theory)(Kuntjojo, 2009;MacDonald et al., 2009; Ishii et al., 2010).

The purpose of this study utilization open space inPekanbaru City. The scope of the area in this study isthe administrative area of Pekanbaru City consistingof several open space in Pekanbaru, this are has beenchosen based on most activity community.

• MTQ areas in Bukit Raya District,

• Pekanbaru City Park,

• Urban Forest,

• Plaza in the Great Mosque of An-Nur,

To find out the utilization of public openspace in the city of Pekanbaru can be usedqualitative descriptive analysis, in which thisqualitative descriptive analysis will explain the theorydescriptively about the utilization or function ofpublic open space, this analysis is used to be able tosee the direction of regional public open space, theactivity tendency will be carried out to analyze the useof land around the public open space. It is also doneby distributing questionnaires in public open spacesthat are semi-open

The sampling technique in this study uses aselected sample (Non Probality sample), becausethe population studied is infinite (Population whosenumber and identity of members is unknown).The method of sampling is done using accidentalsampling. The method of taking accidental samplingis taken on the basis of if only, without being plannedin advance, also the desired number of samples is notbased on considerations that can be justified, providedthey meet the needs. The conclusions obtained areonly crude and temporary. In research it can happento obtain samples that are not planned in advance, butby chance, that is the unit or subject is available toresearchers when data collection is done. The processof obtaining this kind of sample is called accidentalsampling (Kuntjojo, 2009).

From the sampling technique researchersconducted questionnaires on weekdays and onholidays. On weekdays the time chosen is 2 daysbetween Monday and Friday, and on holidays onSaturdays and Sundays. Special Car free Day is onlydone one day, namely on Sunday because this activityis only done once a week. So the number of samplesobtained in each public open space can be seen in thefollowing table:

Table 1: Respondent Public Open Space in Pekanbaru

No Public Open SpaceKuesioner

interviewWork day Holiday Result1 MTQ 10 20 30 122 Pekanbaru

City Park7 16 23 16

3 Urban Forest 8 10 18 94 Plaza in the

Great Mosqueof An-Nur,

9 16 25 17

Result 34 62 96 54


4.1 Utilization Open Space inPekanbaru

4.1.1 MTQ Area

Pekanbaru’s MTQ full area is one of the public openspaces in Pekanbaru City, this area is located onSudirman street, the Full Zone of MTQ is locatedon Jendral Sudirman street which is the road ofPekanbaru City Protocol. To reach this locationvery easily, visitors can use private vehicles such asbicycles, motorbikes or cars. In addition, visitorscan also use city transportation, the MTQ full area ispassed by several city transportation such as Angkot,City Bus, and TransmetroPekanbaru.this area hasquite extensive land, the total area of this area isaround 15 hectares. The facilities are quite complete,such as seating, lighting, garden houses, trash binsand other supporting facilities. The Full Zone ofMTQ has land as a place for citizens to exercise,create play, gather and so on. However, activitiesin the currently reduced MTQ area can be seen atthis time visitors of this region are decreasing. Theexistence of land conversion in some areas, thisarea has quite extensive land, the total area of thisarea is around 15 hectares. The facilities are quitecomplete, such as seating, lighting, garden houses,trash bins and other supporting facilities. The FullZone of MTQ has land as a place for citizens toexercise, create play, gather and so on. However,activities in the currently reduced MTQ area can beseen at this time visitors of this region are decreasing.The existence of land conversion in some areas.The MTQ area is one of the public open spacesin the city of Pekanbaru, with its strategic location,the area is crowded with residents of PekanbaruCity in the evening and at night, as seen from theanswers of 30 public visitors to the open spacequestionnaire (60%) when visiting more often donein the afternoon and (40%) make visits at night. witha wide area, this MTQ area is often held art events,expo music concerts and other events, in the MTQ


183

Figure 1: MTQ Area

area there are various kinds of traditional houses invarious regencies in Riau Province. In addition toart performances, Pekanbaru residents often use theMTQ area as a place of recreation (33%), socialize(23%) and do sports activities (27%) in this place suchas playing football, and so on. At night the MTQarea was made into the city of Pekanbaru as a culinarytourist spot (17%), such as grilling corn, bananas andvarious kinds of food sold by traders in the MTQ area.

4.1.2 Pekanbaru City Park

Pekanbaru City Park is located in a very strategicarea that is in the city of Pekanbaru preciselyon Diponogoro street in Pekanbaru Subdistrict,transportation modes that can be used towards thisarea visitors can use Transmetro Pekanbaru orpersonal vehicles. Pekanbaru city park has an areaof 2.3 hectares. This city park is equipped with quitegood facilities such as lounge benches, swimmingpools, various children’s games and several types ofplants and flowers that make this garden beautiful,besides these facilities in the city park also providesbicycle rental and selling various kinds of food anddrinks.

Figure 2: Pekanbaru City Park

Pekanbaru City Park, located on Diponogorostreet, is one of the public parks that can be utilizedby Pekanbaru City residents, the city park serves

as a provider of oxygen or an area that provideshealthy air amidst pollution in Pekanbaru City. Ofthe 23 questionnaires distributed in the City Park,visitors said visitors used the City Park as a placeof recreation (43%), sports (13%), socializing, andgathering places for Pekanbaru City residents (26%).Visitors who often come to city parks (26%), rarely(52%), are very rare (22%). Visit times are oftencarried out in the morning (4%), during the day(26%), in the afternoon (70%).

4.1.3 Urban Forest

Pekanbaru City Forest is located in Sail District,Sukamaju Village, Pekanbaru, precisely onDiponegoro street.Access to the city forest visitorscan use private vehicles such as motorbikes or cars.Visitors can also use the Transmetro Pekanbarupublic vehicle that passes Diponogoro street, afterwhich visitors walk a little to the urban forestarea.Urban forest is one of the lungs of the city ofPekanbaru, the city forest in the Sail District hasa variety of plants, and has facilities that are quitegood, but still not maintained in the assessment of theoverall forest of Pekanbaru City can be categorizedquite well.

Figure 3: Urban Forest

Urban forest is a land in the middle of thecity which is left to be planted perennials or treesthat grow in the middle of the city or on theoutskirts of urban settlements. Urban forest locatedin Sail Subdistrict is very large or very importantrole for Pekanbaru City, this urban forest servesas a counterweight to human ecology in variousways such as air cleanliness, availability of groundwater, sun protection, animal life in the city, andalso as recreation place for the people of PekanbaruCity. In addition to these main functions, therewere 18 respondents from the City Forest Zonesaid that visitors used urban forest as a place ofrecreation (28%), and often used as a photographerand model talent channel for photography activities(44%), sports (11% ), socializing (17%). The time


184

Figure 4: Plaza in the Great Mosque of An-Nur

of visit is often done in the morning (6%), during theday (6%) in the afternoon (88%). The following is anillustration of the use of urban forests by the peopleof Pekanbaru City.

4.1.4 Plaza in the Great Mosque of An-Nur

Pekanbaru Great An-nur Mosque is the largest placeof worship in Pekanbaru City, the mosque was builtin 1963 and completed in 1968 and carried out a totalrenovation in 2000, the Great Annur mosque has aplaza that is wide enough to be used as an open spacepublic by the people of Pekanbaru City.In addition toprivate vehicles, transportation that can be used byvisitors to go to the Great Mosque of Annur is Citytransportation or Transmetro Pekanbaru which passesthrough the great annur mosque.

The Great Mosque of Annur has an area of about12.6 hectares, with the land area providing flexibilityfor the provision of open land for the public ofPekanbaru including the green park area and largeparking area.The existing conditions of the Plazalocated in the Great Mosque area of Annur is quitegood, this area has a field to play, creativity, track torun, large parking, RTH is quite good. In addition,the Great Mosque of Annur is equipped with variouseducational facilities ranging from the Playgroup toHigh School and also has a library and meeting hall.

The Great Mosque of Annur Pekanbaru is thegrandest Muslim house of worship in the city ofPekanbaru, with an area of about 12.6 hectaresof this mosque area having educational facilities,ranging from preschool, kindergarten, elementaryschool, junior high school to high school level. placeof worship. The Great Mosque of Annur has avery large plaza, from the respondents who got 25people in the Mesjid Agung plaza, in the plaza thismosque residents of Pekanbaru use as a place to play,recreation (12%), exercise (76%), socialize (12% )and others. Visitors who often come to this place(40%) are rare (32%), and very rare (28%). The timeof visit is often done in the morning (4%), during theday (4%), in the afternoon (88%).

To further find out the use of public open space inthe city of Pekanbaru can be seen from the results ofinterviews with visitors to public open spaces. Basedon the results of interviews, visitors can be seen in thefollowing table 2.

5 CONCLUSION

MTQ full visitors rarely go to this location, the time ofvisit is more often done in the afternoon and evening,but more visitors visit in the afternoon. The fullcondition of MTQ is good, visitors are comfortable inthis location, management of MTQ area is quite good,except that facilities in the MTQ area do not meet theneeds of users of public open space, the cleanliness ofthis park is still lacking, MTQ is very strategic, accessto easy locations reachable. Visitor advice on theGovernment so that facilities at the location of publicopen spaces are equipped according to the needs ofvisitors.

City Parks are often visited in the afternoonwith the aim of exercising, gathering and recreation,visitors who come to this place live not far from thelocation of city parks, facilities in the city park arestill incomplete and in poor condition, the cleanlinessof city parks is not maintained Access to the city parkis easy, the city park is located in a very strategiclocation in the city center. Suggestions for visitorsto the government and managers to complete andimprove urban park facilities to be better and morecomfortable to visit.

Respondents obtained said that they rarely cameto the location of the urban forest, and visitors camein the afternoon with the aim of sports, recreation oftalent / hobby distribution, visitors felt comfortablebeing in the location of urban forests, managementof urban forests was quite good, but facilities atthis location were still lacking complete, city forestcleanliness is not well maintained, access to cityforests is easy. Most of the visitors come to usepersonal vehicles at a distance from the house not sofar to the city forest. Suggestions for the Governmentto improve and equip facilities at the location of urbanforests and maintain cleanliness in the location of cityparks.

The Great Mosque of Annur Plaza is visited in theafternoon with the aim of sports, recreation, gatheringand socializing, the condition of the Great Mosque ofAnnur plaza is good, and cleanliness in the plaza areais very well maintained. Access to easy locations,most visitors come to the location using personalvehicles. advice the end to the management and thegovernment so that the facilities in the plaza of the


185

Table 2: Interview Visitors to Open Public Spaces in Pekanbaru City

No Open Spaces Result1 MTQ Area 1. Visitors are more likely to go to the location in the afternoon and evening.

2. The purpose of visitors in the afternoon is to exercise around public openspaces, play, recreation, gather with communities such as photography lovers,skateboarding and those who intentionally come only to enjoy snacks sold bytraders in the MTQ area.3. The purpose of visitors at night in general is to enjoy culinary sales by tradersin MTQ areas such as roasted corn, roasted bananas, satay and etc. And oncertain nights the MTQ area is a place for performing arts such as music concerts,expo events and other events.4. Riau Town Square Development Activities that are not clear about thedevelopment disturbs visitors’ comfort.5. Public open space facilities are still lacking, such as seating, garden housesand other supporting facilities.6. MTQ Area Cleanliness needs to be improved.7. Strategic MTQ area in the city center and access to the area is quite easy,traversed by citytransportation and trans metro pekanbaru.8. Many visitors come to use personal vehicles such as motorbikes and cars.9. The reason visitors choose this MTQ area is because it is close to where theylive.10. Visitor suggestions to the government to complete and improve public openspace facilities in the MTQ area, so that the MTQ area can be utilized optimally

2 Pekanbaru City Park 1. City parks are often visited in the afternoon and evening.2. The purpose of visitors to this place is to play, recreation, relax and gather.3. Visitors feel comfortable in the city park.4. City park facilities are still incomplete and in poor condition.5. Cleanliness in city parks is still lacking6. Access to the location is very easy and the location is very strategically locatedin the city center.7. Visitors who come to the location use personal vehicles8. Many visitors who come to this location because the city park is a comfortableplace for recreation and close to where to live.9. Hope for the government to complete facilities and further improve thecondition of the facilities and cleanliness of city park

3 Urban forest 1. Visitors visit the urban forest more often during the day and evening.2. The visitor’s destination comes to the forest city for recreation, enjoying thefresh air of the city forest, gathering with friends and those who come to takepictures.3. The city forest is very comfortable with fresh air, but the cleanliness in thecity forest is still lacking so that it disturbs the comfort of visitors.4. Facilities are still lacking with unfavorable conditions.5. Visitors come using motorbikes and cars.6. Many visitors come to the city forest because it is not far from where theylive.7. Hope for the government to be installed or repaired by existing facilities suchas seats, trash bins and roads in the urban forest to make it more comfortable.

4 Plaza in the Great Mosqueof Annur

1. When visitors come to the plaza of the Great Mosque of Annur in theafternoon.2. The purpose of visitors in general is to exercise and play.3. The Great Mosque of Annur Mosque is very comfortable4. Cleanliness is very awake.5. Facilities at this plaza are still not as comfortable as seating.6. Access to the Great Mosque of Annur Plaza is very easy.7. Visitors come to the location using personal vehicles.8. Visitors come to the location because this location is not far from wherevisitors live.9. Suggestions to the government are to complete the facilities and add greeneryto the location of the park to make it more comfortable.


186

Great Mosque of Annur are complete.Overall, the condition of public open space

in Pekanbaru City is good but that needs to beconsidered again, namely the completeness andmaintenance of facilities in public open spaces. Inspatial planning, open space in the city of Pekanbaruis still very lacking to meet the needs of the city ofPekanbaru.

REFERENCES

Agboola, O. P., Rasidi, M. H., and Said, I. (2017).The influence of open space utilization onresidents’attachment with community: A casestudy of rural market square in southwest nigeria.ArchNet-IJAR, 11(1).

Budihardjo, E. (2011). Penataan Ruang PembangunanPerkotaan. PT ALUMNI, Bandung.

Budihardjo, E. and Sujarto, D. (1999). Kota Berkelanjutan.Alumni, Bandung.

Ishii, H. T., Manabe, T., Ito, K., Fujita, N., Imanishi, A.,Hashimoto, D., and Iwasaki, A. (2010). Integratingecological and cultural values toward conservationand utilization of shrine/temple forests as urban greenspace in japanese cities. Landscape and EcologicalEngineering, 6(2):307–315.

Kuntjojo (2009). Metode Penelitian. Universitas NusantaraPGRI, Kediri.

MacDonald, J., Shahrestani, S., and Weis, J. (2009).Behavior and space utilization of two common fisheswithin caribbean mangroves: implications for theprotective function of mangrove habitats. Estuarine,Coastal and Shelf Science, 84(2):195–201.

Mulyandari, H. 2010. Pengantar Arsitektur Kota,Yogyakarta.

Pekanbaru, B. P. S. P. K. Kota Pekanbaru dalam AngkaTahun 2013. BPS Kota Pekanbaru, Pekanbaru.

Schmitt, K. (2004). Method and system for utilizationassessment development and management of openspace land areas. US Patent App. 10/849,907.

Woolley, H. (2003). Urban Open Spaces. ,Spon Press, NewYork.


187

Application of Augmented Reality as a Multimedia Learning Media:Case Study of Videography

Ahmad Zamsuri, Fadli Suandi and Rizki NovendraFaculty of Computer Science, Universitas Lancang Kuning, Jl. Yos Sudarso KM. 8 Rumbai, Pekanbaru, Indonesia


Keywords: Augmented Reality, Marker, Teaching Module, Tracking

Abstract: The application of AR (augmented reality) is currently growing and adopted by various fields, including in thefield of education. AR can be combined with conventional teaching materials such as books to provide morein-depth experience and understanding of the material to be conveyed. This research utilizes AR technologywhich is used in multimedia lecture teaching modules that discuss videography material. Testing by comparingthe minimum distance and maximum distance on the marker printed on white paper and opaque paper. Theresults of the study found that teaching modules printed on white paper were better in AR tracking at a certaindistance compared to modules printed on opaque paper. The similarity between markers with each other alsomakes the application display object incompatibility with the marker.

1 INTRODUCTION

Learning media is one of the factors that can improvethe quality of education. The use of learning mediacan increase motivation and interest for students in theteaching and learning process. Integration betweenlearning media and technology is busy nowadays.This is done with the aim of producing learning mediathat are more effective and efficient (Afdal et al.,2018; Amir, 2017).

Multimedia-based computer technology was lateradopted to support interactive learning media. Thetechnology is very effective for students to understandthe material taught compared to conventional learningmethods. This is in line with the standardlearning process contained in the GovernmentRegulation of the Republic of Indonesia number19 in article 19 which reads: ”The learningprocess in educational units is held interactively,inspiring, fun, challenging, motivating students toactively participate, and providing sufficient spacefor initiatives, creativity, and independence inaccordance with the talents, interests, and physicaland psychological development of students ”(Hananet al., 2018; Republik Indonesia, 2005).

One of the technological advancements thatare widely adopted in today’s learning media isAugmented Reality (AR). AR is a technology thatallows virtual information generated by computers tobe combined into a real environment. The presence of

AR can bridge between real and virtual in real-time.The application of AR is currently growing andadopted by various fields, including in the field ofeducation. AR can be combined with conventionalteaching materials such as books to provide morein-depth experience and understanding of the materialto be conveyed(Jung and Dieck, 2018; Riyanto,2015).

In this study, the author will use AR technologywhich is used in multimedia lecture teaching modulesthat discuss videography material. Videographymaterial that is full of practices is not optimal ifit only uses teaching materials in the form of text,so it is considered necessary to use AR as a mediathat can display material information in the form ofvideos. This is expected to help students to moreeasily digest lecture material using AR-based learningmedia (Wulansari et al., 2013).

2 RESEARCH METHODS

The method used in this study is the MultimediaDevelopment Life Cycle (MDLC) method. TheMDLC method is used to create AR-based learningmaterial that uses multimedia content in the formof videos. This method consists of several phases,namely: Concept, Design, Material Collecting,Assembly, Testing, and Distribution. The followingis a general description of MDLC in Figure 1.

188Zamsuri, A., Suandi, F. and Novendra, R.Application of Augmented Reality as a Multimedia Learning Media: Case Study of Videography.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 188-193ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

Figure 1: MDLC development model

The initial concept in this study was to developa video-based augmented reality application as asupporter of learning about videography. At thedesign phase, a text-based teaching module will bedesigned that contains some teaching material onvideography. After that, a marker is designed to referto certain material. Each material each has 1 markerthat will help the reader to use AR technology whenscanning the marker that has been made (Azuma,1997; Azuma et al., 2001).

At the material collection phase, a numberof resources will be collected in designingteaching materials and making applications suchas markers and videos supporting teaching materials.Furthermore, in this step, the application supportingmaterials will be processed. AR applicationdevelopment uses Unity and vuforia. The ARapplication will be used on mobile devices based onthe Android operating system (Milgram et al., 1995).

Next is the testing phase using the camera of amobile device with the Android operating system.The test is done by trying to scan the markers thathave been made using white paper and opaque paperwith various lighting conditions, and the distancewhether the marker can display the video so thatthe use of AR can be well adopted in the teachingmaterial. In the last phase, the distribution will bemade instructions on the use of teaching materialsalong with the AR applications that have been made.Thus the teaching material can be used and utilizedby those who want to use it.


3.1 Concept

The concept in this study is to create an augmentedreality application that is used in a text-basedmultimedia teaching material. The learning materialchosen is about videography. The material used inthis study is about the 8 basic movements of thecamera in videography.

The concept of the 8 basic movements is explainedthrough text in teaching materials, then the functionof the augmented reality application designed is asan additional medium that will display video-basedtutorials on the 8 basic movements of the camera. Thefollowing research concepts can be seen in Figure 2.

Figure 2: The concept of Augmented Reality developed

3.2 Design

Augmented reality application developed using Unityversion 2018.2.11 which is integrated with Vuforiaas a marker storage database. The application isdesigned later through a compiler (output) processwith the output in the form of an .apk extensionso that the application can be run on an Androiddevice. Android devices that can run this augmentedreality application with minimum specificationsusing Android 4.1 JellyBean and the maximumspecifications of Android 8.0 Oreo.

For making augmented reality markers usingthe Adobe Photoshop CS 6 application. Markersare made using certain black and white lettercombinations that aim to obtain a high contrastlevel with the aim of the marker being more easilyrecognized during application testing.

Next is making a simple teaching module aboutthe basic techniques of videography. This teachingmodule is designed using the Microsoft wordapplication. In this module a brief explanationof 8 types of basic camera movements for videocapture is accompanied by examples of how to takethrough tutorial videos that will appear when scannedaugmented reality markers use an Android device.

Application of Augmented Reality as a Multimedia Learning Media: Case Study of Videography

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3.3 Material Collecting

The resources collected in this step are teachingmodules along with video tutorials supportinglearning materials basic techniques of cameramovement on videography. The teaching moduleadopted in this research is based on journalsand several websites that discuss basic shootingtechniques in the science of videography.

After the teaching module is finished, the nextstep is to make a video tutorial related to the basictechniques of shooting on videography. Each of thetechniques described will contain 1 tutorial videoand 1 marker. The following examples of teachingmaterials and markers can be seen in Figure 3.

Figure 3: Teaching materials along with markers that willdisplay the learning video tutorial when scanned

3.4 Assembly

This research began by making teaching materialabout the basic techniques of camera movement invideography. Next, 8 simple modules are producedas teaching material. Then followed by making 8markers. Last is to create an augmented realityapplication that is integrated with the teachingmodules that have been created.

3.4.1 Production of Teaching Modules

The material presented in this teaching module onlydiscusses the basic techniques of camera movementin discussions about videography. By collectinglearning material from journals and websites, 8teaching modules are produced representing eightcamera movement techniques discussed in thismodule which include a discussion of techniques:zoom, tilt, dolly, dolly zoom, arc, follow, trackingand pan . The resulting document is created usingthe Microsoft Word application.

3.4.2 Markers Production

At this phase the author makes 8 markers usingthe Adobe Photoshop CS 6 application. The

marker making technique is adopted at this phaseby making markers based on the names of eachcamera movement technique. An example is in thediscussion of zoom techniques, the word ’zoom’ isused for making markers. When discussing the dollytechnique, the word ’dolly’ is used as a marker onthe marker. In order for the marker to be easilyrecognized during the application experiment, thecolor combination used must produce a high degreeof contrast. Simple colors that have high contrast areblack and white. So that the color is chosen as themain color on the marker that will be made. Blackwill be the edge surrounding the marker, and willbecome the color of the word made. White is usedas the background for the marker. Markers used inthis study can be seen in figure 4.

Figure 4: The marker that will be tested

3.4.3 Production of Augmented RealityApplication

The phases of making augmented reality applicationsuse 2 main tools, Vuforia engine and Unity. Vuforiaengine functions as a database of marker storagethat has been created. Unity functions as processingsoftware that can process graphics, images, sounds,animations and so on. Unity is a cross platformsoftware that can produce application output invarious formats such as .exe, .apk, and so on.

In the first phase is registering 8 markers that havebeen made at Vuforia. After all the markers havebeen uploaded, a rating statement for each markerwill appear. The rating is rated with a star with amaximum value of 5 stars and a minimum of 0 stars.If the marker gets a 5 star rating, it indicates that themarker is more easily detected. Conversely, if therating is closer to 0, the more the marker will be moredifficult to detect.

Of the 8 markers that have been uploaded toVuforia, we got 7 markers with a rating of 4 stars and1 marker that has a rating of 3 stars. The followingis the appearance after the entire marker has beenuploaded to Vuforia as can be seen in Figure 5.


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Figure 5: Display of the marker uploaded to Vuforia

The second phase is to make an augmented realityproject using Unity. The project in this study aswell as the name of the application produced isVideografiAR. The following picture of the projectthat has been made using Unity can be seen in Figure6.

The project consists of 1 main scene calledvideografiar which contains 8 marker objects. InFigure 5.12 you can see the naming of objects basedon the name of the marker preceded by the word’ImageTarget’ in front of it. Each object contains eachmarker along with the tutorial video which will thenbe displayed when the camera on the android devicedetects the marker.

Figure 6: Display of the marker uploaded to Vuforia

After completing all objects in the main scene, thenext is to do the build process. The build process is aprocess that will make a scene that has been made intoan output in the form of an application with a certainformat. In this project the selected build process is theAndroid platform. The following look of the build canbe seen in Figure 7.

Figure 7: Build process in Unity

3.5 Testing

After the application creation process is complete,then the application is installed on an Android deviceto be tested. Android devices used in this trial areSamsung S7 Edge with the following specifications:

• Operating System: Android 8.0.0 Oreo

• Memory: 4GB RAM, Internal: 32GB

• Rear Camera: 12 MP

The test in this study uses 2 types of paper withdifferent colors. The first paper is white HVS paperand the second paper is opaque paper with a darkercolor. All markers were printed on both types ofpaper, then tested how the minimum and maximumdistance of the marker was successfully tracked usingthe augmented reality application. The following testdocumentation can be seen in Figure 8 and Figure 9.

Figure 8: Markers printed on white paper and opaque paper


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Figure 9: Markers detected using an android device anddisplaying a tutorial video

After testing, the following results from the test canbe seen in table 1. From the test, it can be concludedthat there is a difference in the farthest distance of themarker printed on white paper and opaque paper. Ofthe 8 markers tested, markers printed on white papercan be detected at distances greater than 5 to 10 cmcompared to markers printed on opaque paper. For thedetection of markers at the shortest distance on whitepaper and opaque paper each is at the same distanceof 5cm.

Table 1: The marker detection test results using an Androiddevice

NoMarker Marker White Paper Opaque PaperName Rating Shortest

DistanceFarthestDistance

ShortestDistance

FarthestDistance

1 Pan 4 5 cm 70 cm 5 cm 65 cm2 Zoom 4 5 cm 90 cm 5 cm 85 cm3 Tracking 4 5 cm 65 cm 5 cm 55 cm4 Follow 4 5 cm 75 cm 5 cm 60 cm5 Dolly 4 5 cm 85 cm 5 cm 80 cm6 Tilt 3 5 cm 30 cm 5 cm 25 cm7 Dolly

Zoom4 5 cm 90 cm 5 cm 85 cm

8 Arc 4 5 cm 85 cm 5 cm 70 cm

All markers tested successfully displayedvideography learning tutorial videos using theaugmented reality VideographyAR application.Markers with a rating of 3 produce the farthestdistance shorter than markers with a rating of 4.When tracking markers with a lower rating, thecamera on an android device must be closer to themarker less than 30 cm.

Especially for markers with the name ”DollyZoom” there is still confusion in displaying videocontent. The one that should appear is a dolly zoomvideography technique tutorial video, but at the timeof testing, several times the video tutorial on dollyvideography and the zoom videography techniquecame along. This is because the marker with the name”Dolly Zoom” contains the word dolly and zoom

which is also used in the marker ”Dolly” and ”Zoom”.So that when the marker design must be consideredso that between markers with one another do not havesimilarities.

3.6 Distribution

After the testing is done, the next is the distributionprocess. At this stage, all teaching materials,applications with .apk format and procedures forusing the application are stored in the same folderas VideografiAR. Then it is left to those who needaugmented reality teaching materials in learning thebasic techniques of videography.

4 CONCLUSION

The VideografiAR augmented reality applicationthat has been developed successfully displays videolearning tutorials to complete the videographylearning module by utilizing markers embedded inthe learning module. From the tests conductedMarkers printed on white paper are better at trackingat a distance than markers printed on opaque paper.Another factor influencing marker tracking is therating of the marker. The higher the marker’s ratingused, the further the range of marker tracking todisplay the learning tutorial video. In the design ofmarkers it is better to avoid the same word / form,because it has the potential to cause tracking errors bythe application, so the video tutorial displayed doesnot match the marker being tracked.

REFERENCES

Afdal, M., Irsyad, M., and Yanto, F. (2018). Penerapanteknologi augmented reality pada media pembelajaranlapisan permukaan bumi berbasis 3d. JurnalIlmiah Rekayasa dan Manajemen Sistem Informasi.,4(1):1–10.

Amir, I. (2017). Pengembangan Buku Ajar dan AugmentedReality (AR) pada Konsep Sistem Pencernaan.Makassar, Tesis. Universitas Negeri Makassar.

Azuma, R., Baillot, Y., Behringer, R., Feiner, S., Julier,S., and MacIntyre, B. (2001). Recent advances inaugmented reality. IEEE computer graphics andapplications, 21(6):34–47.

Azuma, R. T. (1997). A survey of augmented reality.Presence: Teleoperators & Virtual Environments,6(4):355–385.

Hanan, R. A., Fajar, I., Pramuditya, S. A., and Noto,M. S. (2018). Desain bahan ajar berbasis augmentedreality pada materi bangun ruang bidang datar.


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In Prosiding Seminar Nasional Matematika danPendidikan Matematika (SNMPM), volume 2, pages287–299.

Jung, T. and Dieck, M. C. (2018). Augmented Realityand Virtual Reality Empowering Human, Placeand Business. Springer International Publishing,Manchester.

Milgram, P., Takemura, H., Utsumi, A., and Kishino, F.(1995). Augmented reality: A class of displays onthe reality-virtuality continuum. In Telemanipulatorand telepresence technologies, volume 2351, pages282–292. International Society for Optics andPhotonics.

Republik Indonesia, . (2005). Peraturan PemerintahRepublik Indonesia No. 19 Tahun 2005 tentangStandar Nasional Pendidikan. Jakarta.

Riyanto, S. (2015). S. R. Pemanfaatan Augmented Realitypada Media Pembelajaran Interaktif PeredaranPlanet, 3(4):187–192.

Wulansari, O. D. E., Zaini, T. M., and Bahri, B.(2013). Penerapan teknologi augmented reality padamedia pembelajaran. Jurnal Informatika InstituteDarmajaya., 13:1.


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Green Building Performance Analysis in the Stimi Campus Building

Dian Febrianti and SamsunanCivil Engineering Department, University of Teuku Umar, Meulaboh, Aceh Barat


Keywords: Green Building, Greenship-GBCI, STIMI Campus Building Meulaboh.

Abstract: Every building construction must consider environmental conditions that have an impact on the qualityof life around it, the increase of global warming, and spend more than 1/3 of the world’s resources forconstruction. Green building is a building concept that pays more attention to the environment, not onlyapplied to buildings that will be built, but also applied to existing buildings. This study aims to determine thecriteria and performance of green building based on the Greenship Rating Tools Version 1.1 standard in builtbuildings. The research was conducted in Meulaboh, STIMI Campus building in West Aceh Regency. Themethods used were direct observation, interviews and distribution of questionnaires. All data are collectedbased on Greenship Rating Tools Version 1.1, consisting of 6 (six) categories, namely Land Use (AppropriateSite Development / ASD), Energy Efficiency and Conservation (EEC), Water Conservation (WAC), Materialand Cycle (MRC), Health and Comfort in Indoor Health and Comfort / IHC and Building and EnvironmentManagement (BEM), which consists of 40 criteria with a maximum total number of 117 points. . The resultsof the study are based on data collected on 40 Greenship criteria from six categories consists of ASD, EEC,WAC, MRC, IHC and BEM, each of which scores 8, 12, 3, 4, 13 and 2 points. The highest value is found onthe IHC criteria (13 points) and the lowest value on the BEM criteria (2 points). The overall results obtained avalue of 42 points, and have met the criteria as a building that applies the green building concept, including inthe bronze rank. But based on the results of interviews with building managers, the management concept hasnot yet applied the green building concept.

1 INTRODUCTION

Nowadays, big cities in Indonesia are developingto support economic development so that they needmany new buildings to develop their economies,such as the construction of business centers, officebuildings, educational buildings, shopping center,hospital etc. If the infrastructure continuesdeveloping without considering or paying attentionto environmental conditions such as the accuracyof land use, energy use (electricity) and water aswell as the use of building materials will certainlyhave an impact on the quality of life around it.This is what is considered to have a big role inincreasing global warming, so that the awareness andknowledge of construction actors on the influence ofthe existence of the building is very much needed(Green Building Council Indonesia, 2010; BadanStandarisasi Nasional, 2000b).

One of the mitigation actions taken is bymaking an international commitment framework withan achievement target called Intended NationallyDetermined Contributions (INDCs). INDCs are

national targets of each country requested by theFCC UN for COP 21, Paris. INDCs are reportedto have a higher binding capacity than nationalcommitments in 2009. INDC Indonesia has a targetof 29% reduction in emissions, 3% higher thanthe target set in 2009 (Badan Standarisasi Nasional,2000a; Badan Standarisasi Nasional, 2001; BadanStandarisasi Nasional, 2004).

In overcoming these problems, the GreenBuilding concept emerged as a solution. GreenBuilding is a building concept whose process ismore concerned with the environment, both fromthe use of resources, energy, the use of materials,eliminating negative impacts and improving thequality of human life. This concept is not only appliedto buildings that will be built, it can also be appliedto existing buildings, namely by applying the GreenBuilding concept when renovating and maintainingbuildings (Badan Standarisasi Nasional, 2005; BadanStandarisasi Nasional, 2009).

The Green Building Council Indonesia (GBCI)which was established in 2009 is an independent(non-government) and non-profit (non-profit)

194Febrianti, D. and SamsunanGreen Building Performance Analysis in the Stimi Campus Building.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 194-199ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

institution that is committed to community educationin applying environmental best practices and oneof its programs is to certify Green Buildings inIndonesia based on a typical Indonesian assessmenttool called greenship.

The application of the Green Building conceptis expected not only to be applied to commercialbuildings, but also to various other buildings suchas universities. The Eco-campus program is oneprogram that supports the implementation of greenbuildings on campus which also play a role inreducing global warming.

Therefore, the researchers wanted to know theextent of the application of Green Buiding on thecampus building of the Indonesian ManagementCollege (STIMI) in Meulaboh, West Aceh based onthe Greenship-GBCI.

2 LITERATURE REVIEW

2.1 Green Building

Regulation of the Minister of Environment No. 8 of2010 about Environmental Friendly Building Criteriaand Certification Chapter I Article 1, Green Buildingis a building that applies environmental principles inthe design, construction, operation and managementand important aspects of handling the effects ofclimate change.

According to the Green Building CouncilIndonesia / GBCI (2010), a Green Building is abuilding where from the planning, construction,operation to the operational stages of maintenanceshows aspects in protecting, saving, and reducing theuse of natural resources, maintaining quality fromquality air in the room, and pay attention to the healthof its inhabitants (Badan Standarisasi Nasional,2000b; Peraturan Menteri Negara Lingkungan Hidup,2010).

2.2 Green Building Concept

With the concept of green building, it is expectedto reduce the use of energy and pollution impactswhile building design is environmentally friendly 1.In the National Quality Month and World StandardDay, 2008 explained that in designing ”Intelligent andGreen building” must pay attention to:

• Sustainable use of materials,

1https://green.radenintan.ac.id/mau-tahuperingkat-kampus-terhijau-di-indonesia

• Linkages with local ecology,

• Energy conservation,

• Efficient use of water,

• Handling waste,

• Strengthening linkages with nature,

• Reuse / renovate buildings.

2.3 Case Study of the Application ofGreen Building in CampusBuildings

The Bandung Institute of Technology and ScienceCampus (ITSB) is the first Green Campus inIndonesia which has also been certified by GBCI andreceived the title Gold certified-Design Recognitionwith 107 points in total. The ITSB campusreceived the award for being able to efficientlyand economically save through the single buildingcorridor, application of double skins on site, wastemanagement, composting and rainwater utilization.This savings is done by maximizing natural lightingand reducing the use of air conditioning (AC).

In Indonesia, in addition to the Greenshipstandard, there is another ranking standard that isdevoted to conducting the greenest university ranking,namely UI GreenMetric conducted by the Universityof Indonesia. UI GreenMetric is the greenestuniversity ranking system that has received officialcredibility from the International Ranking ExpertGroup (IREG) at the IREG-6 conference in April2012 in Taipei. IREG is an institution based inBelgium and is an important institution because ofits role as a quality assurance institution with anaudit and certification program for world rankinginstitutions.

UI GreenMetric assessment is applied to allcampus areas, starting from lecture buildings,laboratories and campus supporting facilitiesand infrastructure. The assessment philosophyof GreenMetric UI is based on 3E, namelyEnvironmental, Economic and Equity & Education(Environment, Economics, and Justice & Education).

The aim of the Greenmetric UI is to provide onlinesurvey results based on actual conditions and policiesrelated to the implementation of Green Campus andcampus sustainability in all universities in the world.More attention will be drawn to efforts to preventglobal climate change, energy and conservation ofwater resources, recycling of solid waste, and greentransportation. (UI Greenmetric, 2012).

The implementation of the Greenmetric UI hasbeen implemented since 2010 and at that time 95


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universities from 35 countries participated. And theparticipation of tertiary institutions is increasing overthe years as found in Table 1.

Table 1: UI GreenMetric 2018 Ranking Results forGreenest Universities in Indonesia

NO UNIVERSITY SCORE1 Universitas Indonesia 76252 Institut Pertanian Bogor 74503 Universitas Dipenogoro 70254 Institut Teknologi Sepuluh November 69755 Universitas Negeri Semarang 69256 Universitas Gajah Mada 68507 Universitas Sebelas Maret 66008 Universitas Islam Indonesia 66509 Universitas Padjadjaran 6150

10 Telkom University 597511 Universitas Muhammadiyah Yogyakarta 565012 Universitas Brawijaya 557513 Universitas Multimedia Nusantara 537514 Universitas Sumatera Utara 530015 Universitas Riau 507516 Institut Teknologi Bandung 497517 Universitas Airlangga 490018 UIN Raden Intan Lampung 480019 Universitas Negeri Medan 447520 Universitas Lampung 440021 Universitas Teuku Umar 437522 Universitas Syiah Kuala 432523 Universitas Pelita Harapan 432524 Universitas Andalas 425025 Universitas Medan Area 422526 Yogyakarta State University 415027 Universitas Surabaya 412528 Universitas Hasanudin 412529 Universitas Bengkulu 410030 Universitas Mataram 4075

Source : UI Green Metric (2018)

The criteria in the greenship rating for Existingbuildings shows in Table 2 below.

Table 2: Criteria in Greenship for Existing Building

Category CriteriaPrecondition Credit Bonus

ASD 2 7 -EEC 2 7 -WAC 1 8 -MRC 3 5 -IHC 1 8 -BEM 1 5 -

Total of Criteria 10 40 -Source: GBCI (2011)

Credit criteria have certain points which if thebuilding can be achieved in accordance with theminimum total points required by GBCI, the buildingis certified with a predicate level as found in Table 3.

Table 3: Greenship Predicate Level for New Buildings

Predicate Minimum Point Percentage (%)Platinum 83 73

Gold 66 57Silver 53 46

Bronze 41 35Source: GBCI (2012)


This study was specifically examined at the STIMICampus Building in West Aceh Regency, locatedat National Road, Meulaboh-Tapak Tuan, LangungVillage, Meureubo District, and West Aceh Regency.The building used by lecturers, students, andother employees has an important role as campusmanagement facility to accommodate academicactivities.

In this study, data management was carriedout, while the data needed were primary data andsecondary data contained in the field or researchlocation, after the data was collected followed byanalyzing data with the help of several instruments,that is Greenship Rating Tools for Existing BuildingVersion 1.1, Indonesian National Standards andRegulations (SNI) related to the criteria stated in theGreenship, and Regulation of the Minister of PublicWorks concerning Green Buildings (Green building).

In analyzing the performance of green buildingmust use Greenship green building standardscompiled by GBCI which are applied in Indonesia asa tool of assessment consisting of:

• Greenship for residential homes

• Greenship for new buildings,

• Greenship for buildings built,

• Greenship for interior spaces.

This study uses the Greenship Rating Systemfor Building Built Version 1.1 This GreenshipPreparation is supported by the World Green BuildingCouncil and carried out by the Rating Commissionof GBCI, consisting of 6 (six) categories with atotal prerequisite criteria of 10 criteria and 41 creditcriteria. The six categories of Greenship in question,namely:

• Land Use (Appropriate Site Development / ASD),

• Energy Efficiency and Conservation (EnergyEfficiency and Conservation / EEC)

• Water Conservation (WAC)

• Sources and Material Cycles (Material Resourcesand Cycle / MRC)

• Health and Comfort in Indoor Health and IHC.

• Building Environment Management (BEM)


The study was conducted based on the data containedin Chapter III. The results showed in form of data


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on the requirements and feasibility of the MeulabohSTIMI campus building and describe the greenbuilding concept in this campus building.

Green Building Assessment is a criterion thatmust be fulfilled and applied in a building. InGreenship, if these criteria cannot be met, then thecriteria and benchmarks in a category cannot beevaluated and the Green Building assessment processcannot be continued. There are 10 prerequisites inthe Greenship Existing Building which represent 6categories.

4.1 Appropriate Site Development/ASD

Good land use by taking into account the developmentimpacts in an area on the environment and thesurrounding environment is a benchmark in thisaspect of land use. According to Briassoulis (2000)changes in land use are changes that occur in a landuse with a specific purpose.

The right aspect of land use is expected to be ableto reduce the negative influence of land use change bydevelopment on the environment. Next is the ratingand assessment in the aspect of ASD which consistsof 2 criteria prerequisites and 7 normal criteria with amaximum total score of 16 points.

Table 4: The results of the calculation of land use categories(ASD) at the Meulaboh STIMI campus building.

ASD CREDIT CRITERIA EVALUATIONPOINT

POINT

1 CommunityAccessibility

2 3

2 Motor VehicleReduction

1 0

3 Site Landscaping 2 24 Heat Island Effect 3 15 Stormwater

Management2 1

6 Site Management 2 17 Building

Neighbourhood2 1

TOTAL 16 9

4.2 Energy Efficiency andConservation/EEC

Energy conservation is an energy efficiencyimprovement that is used or commonly referredto as the energy saving process (Untoro et al. 2014).Electricity is one of the largest energy consumptionin a building; electricity is used in almost entireoperational cycle of the building. Electrical energyfor campus building of STIMI Meulaboh is suppliedfrom PLN and used to operate equipment such as airconditioning, lighting, pumps and others.

With the large energy consumption, an effortneeded to limit the use of energy with a system and

an efficient way. The following are the criteria andassessments in the EEC aspect which consists of 2criteria preconditions, 7 usual criteria and 2 bonuscriteria with a maximum total value of 36 points.

Table 5: Measurement results (EEC) Meulaboh STIMIcampus building

EEC CREDIT CRITERIAEVALUATION

POINT POINT

1Optimized Efficiency BuildingEnergy Performance 16 0

2Testing, Re-commissioning orRetro-commissioning 2 0

3 System Energy Performance 12 114 Energy Monitoring and Control 3 15 Operation and Maintenance 3 06 On Site Renewable Energy 5 B 07 Less Energy Emission 3 B 0

Total 36 12

4.3 Water Conservation/WAC

Stating that water conservation is an action takento reduce the use of clean water. Therefore,the benchmarks found in the aspect of waterconservation in GBCI’s greenship rating tools aregenerally regarding the application of water qualitymaintenance and maintenance measures, as well asmanagement of building management towards the useof clean water.

The WAC category consists of 1 criteriaprecondition, 8 usual criteria and 1 criterionbonus with maximum total points is 20 regular pointsand 2 bonus points.

Table 6: Criteria In Water Conservation (WAC)ASD CREDIT CRITERIA EVALUATION

POINTPOINT

1 Water Sub-Metering 1 02 Water Monitoring Control 2 03 Fresh Water Efficiency 8 04 Water Quality 1 05 Recycled Water 5 16 Potable Water 1 07 Deep Well Reduction 2 28 Water Tap Efficiency 2b 0

Total 20 3

4.4 Material Resource and Cycle /MRC

In a development, building materials are needed tosupport construction. These building materials comefrom natural resources, and nature has a limitednumber so that one day they will run out if exploitedcontinuously without any effort to maintain thesustainability of nature.

In addition to the impact on nature, another thingto consider is the health of the users of the buildingitself. If the building materials used do not payattention to the appropriate procedures. So the main


197

objective of this aspect is the management of a goodand environmentally friendly material life cycle.

Next is the rating and assessment in the MRCaspect which consists of 3 prerequisite criteria and5 usual criteria with a maximum total score of 12points.

Table 7: Criteria In categori Material Resouce and Cycle(MRC)

MRC CREDIT CRITERIA EVALUATIONPOINT

POINT

1 Usage Non ODS 2 12 Material Purchasing Practice 3 23 Waste Management Practice 4 24 Hazardous Waste Management 2 05 Management of Used Good 1 0

Total 12 3

4.5 Outdoor Health and Comfort

In the comfort and health category in space, there are1 prerequisite and 8 criteria that have a maximum totalvalue of 20 points.

Table 8: Criteria In Category Outdoor Health And ComfortASD CREDIT CRITERIA EVALUATION

POINTPOINT

1 Outdoor air introduction 2 02 Environmental tobacco smoke 2 13 CO2 and CO 2 04 Physical chemical and pollutans 6 65 Biological Pollutans 3 16 Visual convort 1 17 Acustic level 1 18 Building User survey 3 3

Total 19 13

4.6 Building EnvirinmentManagemennt

The BEM category consists of 1 criteria precondition,5 criteria and with maximum total points of 13 points.

Table 9: Criteria In Building Environment Management(BEM)

MRC CREDIT CRITERIA EVALUATIONPOINT

POINT

1 Innovation 5 22 Design Intent &

Owner Project2 0

3 Green Operational 2 04 Green

Occupancy/Lease2 0

5 Operation AndMaintenance

2 0

Total 13 2

After the measurement is done by interview anddirect observation of each green building criteria,each criterion will be assessed according to itsapplication. The results obtained in this study showthat there are still many prerequisites and criteria that

have not been fulfilled, along with the assessmentresults listed in the table.

Table 10: Criteria in Greenship for building builtNO CREDIT EVALUATION POINT POINT %

1 ASD 16 8 502 EEC 36 12 333 WAC 20 3 154 MRC 12 4 335 IHC 20 13 656 BEM 13 2 15

Total 117 42 40

From table 7 above, shows that the largestpercentage of the values obtained per day criteria isIHC, which is 65%. For more details the comparisonof the criteria values for the points obtained can beseen in Figure 1 below

Figure 1: Points obtained on the criteria of ASD, EEC,WAC, MRC, IHC and BEM.

5 CONCLUSION

Based on the 40 criteria in the Greenship category,Meulaboh STIMI campus building received 42 pointsfrom 117 maximum points, consisting of ASD = 8,EEC = 12, WAC = 3, MRC = 4, IHC = 13 andBEM = 2 points, so that it deserves a bronze rating.The the comparison results from the evaluations ofgreen building performance each obtained Land Use(Appropriate Site Development / ASD) 50%, EnergyEfficiency and Conservation (Energy Efficiency andConservation / EEC) 33%, Water Conservation(WAC) 15%, Source and Material Cycle (MaterialResources and Cycle / MRC) 33%, Health andComfort in Indoor Health and IHC 65%, and BuildingEnvironment Management (BEM) 15%. The highestvalue in the Energy Use Efficiency category (IHC) is13 points, and the lowest is in the category (BEM) 2points.


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6 SUGGESTIONS

• The attention from governments is needed andalso other institutions such as local regionaldevelopment agency (BAPPEDA) to improve theperformance of green building in built buildingsby giving awards to buildings that have appliedthe concept of green buildings.

• To the campus building management of STIMIMeulaboh be able to improve the understandingof environmentally friendly buildings and theapplication of the concept of green building, andpay attention to energy (electricity), water andmaterial use to make it more comfortable in theimpact of quality of life.

• It is expected that users of the Meulaboh STIMIcampus building can improve their understandingof environmentally friendly buildings and greenbuilding

• To the campus management, they can payattention to the development of campus buildingsin terms of green construction and green buildingsso that they become more comfortable andenvironmentally friendly campuses.

ACKNOWLEDGMENTS


REFERENCES

Badan Standarisasi Nasional, . (2000a). tentang KonservasiEnergi pada Sistem Pencahayaan. Badan StandarisasiNasional, Jakarta.

Badan Standarisasi Nasional, . (2000b). tentang ProsedurAudit Energi Pada Pembangunan Gedung. BadanStandarisasi Nasional, Jakarta.

Badan Standarisasi Nasional, . (2001). tentang TataCara Ventilasi dan Sistem Pengkondisian Udara padaBangunan Gedung. Badan Standarisasi Nasional,Jakarta.

Badan Standarisasi Nasional, . (2004). tentang PengukuranIntensitas Penerangan di Tempat Kerja, BadanStandarisasi Nasional. Badan Standarisasi Nasional,Jakarta.

Badan Standarisasi Nasional, . (2005). tentang Tata CaraPelaksanaan Sistem Plumbing. Badan StandarisasiNasional, Jakarta.

Badan Standarisasi Nasional, . (2009). tentang KonservasiEnergi pada Sistem Tata Udara Bangunan Gedung.Badan Standarisasi Nasional, Jakarta.

Green Building Council Indonesia, . (2010). PanduanPenerapan Perangkat Penilaian Bangunan HijauGREENSHIP Versi 1. 0.

Peraturan Menteri Negara Lingkungan Hidup, . (Nomor08 Tahun 2010). tentang Kriteria dan SertifikasiBangunan Ramah Lingkungan, Menteri NegaraLingkungan Hidup. Jakarta.


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Towing Service Ordering System based on Android:Study Case - Department of Transportation, Pekanbaru

Panji Rachmat Setiawan, Yudhi Arta and Rendi SutisnaDepartment of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

panji.r.setiawan, [email protected], [email protected]

Keywords: Car Users, Breaking Down, Towing Service, Android

Abstract: The department of transportation is an element from the government of Pekanbaru, led by the head of de-partment who responsible and work under mayor and regional secretary. Towing services from departmentof transportation are part of their task to implementing regional autonomy authority. Present increasinglyrapid technology demands government agencies push hard to maximize their performance in order to facilitateservices for the community. Four-wheel vehicle users who mostly don’t know about car engine and whensuddenly their vehicle is breaking down, it can cause panic. Sometimes car users who visit Pekanbaru, or onlypassing by, don’t know towing service’s telephone number, will have difficulty experiencing problem if theircar is breaking down. Then, from the government side will experience difficulties during pickup, because theofficer in charge doesn’t know where the shortest route or where’s the exact location. Meanwhile, for orderingservice still done manually and not computerize by using telephone. To overcome this problem, a system isbuilt in the form of an android application, so that it can overcome the problem. Using this system, cars userscan ordering towing services from their smartphone, and also the officer can easily locate their location fromthe system.

1 INTRODUCTION

Nowadays, mobile technology has given big impactfor our society. It can be seen by increasing num-ber of mobile technology users. As example, almosteveryone around us using mobile phones. They useit for work, entertainment, bank transaction, buyinggroceries and not closed every activities using mobilephone. But, not every activities has already using mo-bile technology, and there’s so many reason why notintegrated with mobile technology, like cost for inte-gration, or cost for development.

Mobile technology that is currently popular is An-droid. Android is an operating system that is modifiedfrom Linux Kernel which is based on open source, sothat it can be used by anyone. Android technology canbe used in a variety of human activities with the aimto making it easier, starting from facilitating commu-nication, learning, to service issues in the community.

The increasing number of residents in Indonesia,especially in Pekanbaru, does not rule out the pos-sibility of users four-wheel drive type is increasing.Car is no longer seen as a special item, it can be seenfrom the level of traffic congestion that is increasinglycrowded by many vehicles including cars.

The department of transportation is an elementfrom the government of Pekanbaru, led by the headof department who responsible and work under mayorand regional secretary. Towing services from depart-ment of transportation are part of their task to imple-menting regional autonomy authority.

Present increasingly rapid technology demandsgovernment agencies push hard to maximize theirperformance in order to facilitate services for com-munity. Four-wheel vehicle users who mostly don’tknow about car engine and when suddenly their vehi-cle is breaking down, it can cause panic. sometimescar users who visit Pekanbaru, or only passing by,don’t know towing service’s telephone number, willhave difficulty experiencing problem if their car isbreaking down. Then, from the government side willexperience difficulties during pickup, because the of-ficer in charge doesn’t know where the shortest routeor where’s the exact location. Meanwhile, for order-ing service still done manually and not computerizeby using telephone. To overcome this problem, a sys-tem is built in the form of an android application, sothat it can overcome the problem. Using this sys-tem, car users can ordering towing services from theirsmartphone, and also the officer can easily locate their

200Setiawan, P., Arta, Y. and Sutisna, R.Towing Service Ordering System based on Android: Study Case - Department of Transportation, Pekanbaru.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 200-204ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

location from the system.

2 RELATED RESEARCH

Based on research, (Akbar et al., 2014), the high tele-phone credit rates with limited service areas also helplazy customers to use this service. System like this isno longer feasible to use when time becomes very im-portant because the increase of human activities. Oneof popular operating system on smart phone is an An-droid, which experienced rapid development after itwas acquired by Google Inc. Android is a computercode-based software that can be distributed openly(open source), so that programmers can create newapplications in it. With the increasing growth of An-droid, it indicates that there are more Android-baseddevices, so many people will use android phones.Food delivery service application is an informationsystem on an Android-based mobile device to sim-plify restaurant food ordering process and optimizedelivery of food services at restaurant.

Next, based on research, (Hanaf et al., 2013), thatin the process of serving customers who come to re-pair or take their cars, PT. Surya Kencana experiencedvarious obstacle in conducting a transaction. Thesetransaction sometimes do not go according to planwhich cause various customers complaints. Amongthem is the recording of customer data and paymenttransactions that are still carried out using notes in thebook which can cause transaction process hampered.From the problems that described earlier, PT. SuryaKencana needs an information system as a tool to pro-vide right solution to solve the problem. Therefore, aweb-based car workshop information system will becreated at PT. Surya Kencana. It is expected that PT.Surya Kencana can solve these problems and can im-prove service to customers by using system.

And then, based on research, (Steven, 2015), thatPT. Isuindomas Putra still running their process man-ually, where customers come directly to workshop,register their car which is takes time, and others stillwaiting for their turn. Therefore the author makescomputerized web-based application for car serviceordering system. With the car service ordering sys-tem, customers is easier ordering service for theircars.

2.1 Basic Theory

2.1.1 Meaning of Ordering

Based on research, (Hermawan and Kurnia, 2016),meaning of ordering is the process, manufacture, how

to order, or order itself. The following is the definitionof ordering according to experts:• Order is receipt of an order from customer for

a product. Continuation from order is deliverygoods to the hands of buyer, safely.

• Reservation in general sense are booking agree-ment between two or more parties.

• Ordering is the entire process of activities relatedto managing inventory, product location distribu-tion, and records every booking transaction forboth passengers and goods.

2.1.2 Meaning of Service

Service is an activity carried out by interacting withpeople or with physical machine in order to producecustomer satisfaction. Service cannot be equated withsomething that tangible, because it is intangible andnot real. Service only can be felt and experienced byeach individual. (Rao, 2011).

Service is an activity originating from an individ-ual or organization by way of giving to other peopleor connoisseurs of service and basically the servicehas intangible properties and does not result in anyownership.(Chatterjee and Hevner, 2010).

According to (Kotler, 2012), determine that thereare 5 determinants of service quality, presented se-quentially based on their level of importance, includ-ing tangibles, empathy, reliability, responsiveness,and assurance.

Meanwhile, (Tjiptono, 2010) identified 10 factorsor main dimension which determine the quality of ser-vice, including reliability which is include 2 pointsperformance and dependability, responsiveness, com-petence, access, courtesy, communication, credibility,security, understanding, tangible.

According to (Saladin, 2012), there are 10 factorsin service quality, includes readiness of service facili-ties, good communication, employee must be skilled,good relations with consumers, employees must becustomer oriented, must be real, quick response, se-curity must be maintained, tangible, understand thedesires of consumers.

According to (Alma, 2010), types of services canbe classified as follows• Personalized Service, divided into 3 groups, per-

sonel service, professional service, business ser-vice

• financial service, consists of banking service, in-surance service, investment securities

• Public utility and transportation service• Entertainment• Hotel service

Towing Service Ordering System based on Android: Study Case - Department of Transportation, Pekanbaru

201

2.1.3 Mobile Apps

according to (Purnama, 2010), mobile app is an appli-cation that running on mobile device. By using a mo-bile application, can easily do every activities such asholiday, selling, studying, doing office work, brows-ing, etc. Mobile app has many types on size, design,even layout, but they have very different characteristicform desktop, which is smaller size, limited memory,limited processing, low voltage, strong and reliable,limited connectivity, and short life span.

Based on sources from the book, (Safaat, 2008),android is a robot who looks like human. Android isa operating system for smartphone and tablet.

2.1.4 API

According to (Tulach, 2008), API or Application Pro-gramming Interface, not just a set of classes andmethods or functions and simple signatures. But themain aim is to overcome the ”clueless” in buildinglarge size software, starting from something simpleto complex, and a component behavior that is diffi-cult to understand. It can be concluded that the APIis a collection of commands, functions, classes andprotocols that allows software to connect with eachother. The purpose of the API is to eliminate cluelessfrom the system by creating large blocks of softwarethroughout the world and reusing commands, func-tions, classes, or protocols that they or API has.

As noted by (Svennerberg, 2010), Google MapsAPI is the most popular API on internet. This recordhas been done at May 2010, this state that 43%mashup (applications and websites which combiningtwo or more data sources) using Google Maps API.Some of the purpose of using Google Maps API is tosee the location, look for an address, get driving in-structions, etc.

Location Based Service (LBS) is an informationservice that can be accessed using mobile devicethrough the internet and cellular network and utilizethe ability to pinpoint the locations on mobile device.(Razaq and Jananto, 2014).

3 RESEARCH METHOD

At this time, department of transportation at Pekan-baru, car towing system still done manually, orderingby telephone made by the driver, or ordering to theoperator at department of transportation’s office, thenthe operator will look the availability of crane unit andassign crane’s driver who’s willing to look availabletow truck, and tow the ordering car at the location

that has been ordering by phone and receive towingcost immediately after car has been delivered to thedestination.

Figure 1: Existing System

3.1 System Development and Design

The system that will be developed is citizen ordertowing service using their smartphones in this caseis Android which has already installed towing serviceordering system application. Then, ordering will re-ceive by server which will be processed immediatelyby spreading notifications to all active drivers, afterthat the driver will receive an order and immediatelypick up to the location that has been ordered and dothe towing.

Figure 2: Development System

This is a design of system that will be develop


After development has already done, next step authordoing a test for system, and it shows good result, justlike author’s expectations.

4.1 Car’s Users Register

At this stage of testing carried out by the driver (citi-zen) as a user on an android-based application, to reg-ister new account, then fill in user data form. Afterfilling in all fields, a successful message will appear,


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Figure 3: Design System

but if there’s something wrong, a warning messagewill appear.

Figure 4: Driver Registration

4.2 Driver Login Process Testing

At this stage of testing carried out by the driver (cit-izen) as a user on an android-based application, tolog in user must fill in username and password, afterfilling all fields, main page will appear, but if there’ssomething wrong, a warning message will appear.

Figure 5: Driver Registration

4.3 Testing of Towing Service OrderingProcess

At this stage of testing carried out by the driver (cit-izen) as a user on an android-based application, to

order the first thing to do is press order button andfill in all fields from filling form. User must fill pickup location and destination, then system will look forwhere driver is located. After getting location anddestination, next step is driver must fill in driver’s cardata and take pictures of the condition of the car willbe towed. The order data will be saved and will ap-pear on history tab menu.

Figure 6: Testing Towing Service

Figure 7: Order History

4.4 Towing Service Testing

Officer waits for order that has been sent by the driverthrough an android-based application, then it will beimmediately received by the officer by pressing ac-cept button, after that google map will appear and willfind the location of the driver. If driver’s location hasbeen found, officer must press pickup button, and af-ter pickup process is complete, officer must deliver

Towing Service Ordering System based on Android: Study Case - Department of Transportation, Pekanbaru

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to driver’s destination. After the delivery is finished,driver data will be saved and stored in the order his-tory.

Figure 8: Receive Message

Figure 9: Pickup Process

Figure 10: Pickup History

5 CONCLUSIONS

Based on the results of the analysis and discussionthat has been done, conclusions can be taken as fol-lows system can replace manual system that has beenused so far to be a more computerized system, easierfor people to process towing service reservation, canproduce towing report.

The suggestions that can be given for the develop-ment of this system are as follows further research isexpected to add payment features, and able add offi-cer’s location in real time, so the driver can find outwhere is officer’s location

REFERENCES

Akbar, M., Satoto, K. I., and Isnanto, R. R. (2014). Pembu-atan aplikasi layanan pesan antar makanan pada sis-tem operasi android. Transmisi, 16(4):170–174.

Alma, B. (2010). Kewirausahaan untuk mahasiswa danumum. Bandung: Alfabeta.

Chatterjee, S. and Hevner, A. R. (2010). Design research ininformation systems: theory and practice. Springer.

Hanaf, F. et al. (2013). Rancang bangun sistem infor-masi bengkel mobil berbasis web (studi kasus pt.surya kencana). Skripsi. Jurusan Sistem Informasi.Surabaya: Sekolah Tinggi Manajemen Informatika &Teknik Komputer.

Hermawan, I. and Kurnia, D. A. (2016). Sistem informasipemesanan paket pengantin berbasis web pada yunisalon duku puntang kabupaten cirebon. Jurnal ICT:Information Communication & Technology, 12(2).

Kotler, P. (2012). Kotler on marketing. Simon and Schuster.Purnama, R. (2010). Pengertian aplikasi mobile. Jakarta:

Mediakom.Rao, K. R. M. (2011). Services marketing. Pearson Educa-

tion India.Razaq, J. A. and Jananto, A. (2014). Sistem informasi pub-

lik layanan kesehatan menggunakan metode locationbased service di kota semarang. Dinamik, 19(1).

Safaat, N. (2008). Aplikasi Berbasis Android. Informatika.Saladin, D. (2012). Manajemen pemasaran, analisis peren-

canaan pelaksanaan, unsur-unsur pemasaran.Steven (2015). Perancangan Sistem Informasi Pemesanan

Servis Mobil di PT. Isuindomas Putra Berbasis Web.PhD thesis, Sekolah Tinggi Manajemen InformatikaDan Komputer.

Svennerberg, G. (2010). Beginning Google Maps API 3.Apress.

Tjiptono, F. (2010). Strategi pemasaran edisi ke dua, pener-bit andi.

Tulach, J. (2008). Practical API design: Confessions of aJava framework architect. Apress.


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Biosurvey of Mercury (Hg), Cadmium (Cd), and Lead (Pb)Contamination in Reclamation Island-Jakarta Bay

Salmita Salman1, Achmad Sjarmidi1 and Salman2

1Ecology Research Group, School of Life Science and Technology, Bandung Institute of Technology, Bandung, Indonesia2Faculty of Agriculture, Universitas Islam Riau, Pekanbaru, Indonesia


Keywords: Biosurvey, Heavy Metals, Jakarta Bay, Reclamation

Abstract: Man-made islands allegedly alter the coastline that slowing pollutants retention time. Green mussels (Pernaviridis) are one of the organisms known to accumulate heavy metals. Biosurvey needs to be conductedto acquire information on heavy metal content in man-made habitat and biota. The aims of this researchare to identify the water quality related to heavy metal presence; to measure heavy metal content in greenmussels (Perna viridis) around the reclaimed island to determine heavy metal level pollution on reclamationisland. Sampling was conducted in August 2017 in reclamation islands C and D. Heavy metal measurementvalues refer to the SNI method 3554-2015. Data of heavy metal content in water, sediment, and greenmussels were analyzed with quantitative descriptive method. The results show biological oxygen demands(BOD), and chemical oxygen demands (COD) has exceeded the water quality standard which indicates a highlevel of pollution. The results of the examination of the heavy metal in seawater show that mercury (Hg),cadmium (Cd), and lead (Pb) are below the tools detection limit (<0.0002; <0.00011; <0.00086 mg/L) andbelow seawater pollution standard for biota. Concentrations of heavy metals mercury, cadmium, and lead insediments around the reclaimed islands and Teluk Naga area are below heavy metal pollution standards forsediments. Mercury (Hg) levels below the tools detection limit (<0.0004 mg/L); cadmium (Cd) ranges from0.02-0.20 mg/L; lead (Pb) ranges from 0.50 to 5.46 mg/L. Heavy metals examination in green mussels indicatethat mercury (Hg), cadmium (Cd), and lead (Pb) are below the tools detection limit (<0.001; <0.00011;<0.00086 mg/L) and below the heavy metal pollution standard on bivalves. Generally, water and sedimentaround the reclaimed islands and natural habitat in August 2017 are not polluted by heavy metals so there is noharm to biota. Heavy metals quality in water, sediment and mussels are below the pollution standard and basedon the USEPA system belong to grade A. The heavy metal index on Reclaimed Island is 18 and consideredgood. Based on the results obtained, it can be concluded that the reclaimed islands C and D in August 2017were safe from heavy metal mercury, cadmium, and lead pollutions.

1 INTRODUCTION

One of the purposes of island reclamation in DKIJakarta Provincial Regulation is to comply withland needs with consideration of the ever-increasingpopulation. Modeling research by (Badriana, 2015;Aprilia and P., 2017)states that• There is current velocity value decrease after

reclamation, the current velocity value changeoccurs in the gap and around reclamation area

• The increase in sediment may potentially appeararound the inland/near coastal reclamation areaand in inter-island reclamation gap.Changes in currents around the reclaimed

island will decrease the retention time in washing

contaminants from the land. This results fromsedimentation rates increase around the estuary,eutrophication and contaminants cumulationincluding heavy metals. Research on heavymetal pollution in Jakarta Bay has been conductedbefore and indicating heavy metals detected withvarying levels (Cordova, 2011; Putri et al., 2012;Permanawati et al., 2013; Suryono, 2006).

Green mussels have a sedentary lifestyle, attachedto the substrate using byssus, and filter feeder thatallows heavy metals to enter the body (Cordovaet al., 2016). Green mussels are able to bind metalsand integrate metal concentration in water over time(Dumalagan et al., 2010) so they can be recommendedas heavy metal biofilter (Koropitan and Cordova,

Salman, S., Sjarmidi, A. and SalmanBiosurvey of Mercury (Hg), Cadmium (Cd), and Lead (Pb) Contamination in Reclamation Island-Jakarta Bay.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 205-210ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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2017). Currently, there is no information aboutthe content of metals in green mussels that live inreclaimed island C and D habitat. Based on thesecondition biosurvey of heavy metal content on greenmussels and their habitats is necessary. Thus theobjective of this research was to identify the waterquality related to the heavy metal presence and tomeasure heavy metal content in green mussels (Pernaviridis) around the reclaimed island.

2 MATERIAL AND METHODS

2.1 Research Location, Time, andDesign

The research was conducted from July to December2017. Sampling station determined purposively basedon green mussels presence at the point of biotamonitoring attached in Environmental ManagementPlan and Environmental Monitoring Plan (RKL-RPL)of C and D reclamation islands (A, B, C, andD) and Teluk Naga (figure 1). There arethree observation points at each station, positionedby Global Positioning System (GPS). Samplingwas conducted in August 2017 and expected toprovide an overview of water conditions in the dryseason. Descriptive method research was used todetermine levels of heavy metals in green mussels.Mussels were collected by hand-sorting techniques(Abdulgani and Aunurohim, 2010).

Figure 1: Sampling Station

2.2 Tools and Materials

Tools used in this research include water samplermodel JT-1 made in the USA, sediment sampler, 250ml and 500 ml polyethylene plastic bottle, GlobalPositioning System (GPS) Garmin GPSMAP64s,

coolbox, plastic clip bag, beaker glass, pipettes,meter, FiveGo pH meter, Atago refractometer madein Japan, turbidimeter, oven, funnel, vernier caliper,adhesive label paper, analytical balance, MettlerToledo Seven2Go dissolved oxygen (DO) meter,action camera for underwater photo and videography,Fujifilm Finepix s4800 camera, stage sieve, 700series inductive coupled plasma optical emissionspectrometry (ICP-OES) device year 2013 made inAustralia. Materials used include green mussels(Perna viridis), water samples, sediment samples,distilled water, preservative samples (86% H2SO4,70% HNO3).

2.3 Sample Storage, Preservation, andHandling

Sampling and handling of the sample refer toPuget Sound Water Quality Action (PSWQA)(PSWQA., 1997) and Standar Nasional Indonesia(SNI) 06-2412-1991 (SNI, 2008). The data takeninclude the measurement of several physical andchemical parameters of water quality. Measurementswere performed either in-situ or ex-situ throughlaboratory analysis and were done three times at eachobservation point. In-situ measurements includeddepth, temperature, pH, salinity and dissolved oxygen(DO). Ek-situ measurements for grain size analysiswas done at the Ecology Laboratory of Schoolof Life Science and Technology Institut TeknologiBandung (SITH ITB) and for Total Suspended Solid(TSS), Biological Oxygen Demand (BOD), ChemicalOxygen Demand (COD) and heavy metals sampleswere sent to Saraswanti Indo Genetech (SIG) Bogorlaboratory. Sediment texture was determined basedon (K., 1922) by filtering sediment using a stratifiedfilter. The sediment type is determined usingMiller’s triangle (Miller and White, 1998). TSS,sediment grain and green mussels samples are storedat 4C. Biological Oxygen Demand (BOD) samplesare stored in dark bottles at 4C. Chemical OxygenDemand (COD) samples were preserved with H2SO4.Water samples are preserved with HNO3.


3.1 Heavy Metals in Seawater andSediment

Analysis result of heavy metals cadmium (Cd),mercury (Hg) and lead (Pb) in the water and sedimentof Reclamation Island and Teluk Naga provided in


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Table 1. All metals values were below seawaterquality standards (Decree Ministry of Environmentand Development No. 51, 2004) so they are relativelysafe for biota. This result was similar to (Putri et al.,2012) that reported the concentration of mercury,cadmium, and lead in the waters of Muara Kamal isbelow the standard of seawater so it is suitable formussels and other biota growth. The concentrationof heavy metals in the aquatic ecosystem due to thepresence of natural heavy metals and heavy metalwaste. The concentrations of heavy metals are higherwith the input of waste into the waters and accumulatein the ecosystem. Heavy metals in an aquaticecosystem experiencing various processes such asprecipitation, dilution, dispersion, and absorptionby living organisms in aquatic habitat (Warner andPreston, 1974; HP., 1984).

Mercury (Hg) concentrations in sediments aroundReclamation Island and Teluk Naga are not hazardousto the environment and living organisms. Mercury(Hg) concentration in the research area probably lowthat it is undetectable. Cadmium (Cd) concentrationin sediments range from 0.07 to 0.15 mg/L.The concentration value was below the standardof IADC (International Association of DrillingContractors)/CEDA (Central Dredging Association)(1997). Cadmium (Cd) at that concentration has nopotential hazard to the living organism. The results ofCd analysis showed higher concentrations in sedimentthan water column in each research site. This happensdue to heavy metals have a tendency to settle becauseof the large mass. Lead concentrations in sedimentsrange from 2.10 to 4.62 mg/L. The concentrationvalues were below the standard of IADC/CEDA(1997). Presence of Pb metal allegedly due to theconcentration of Pb in the waters and the amountof organic and inorganic particles in the waters (CCet al., 2007; Begum et al., 2009; S and MH., 2010).

Metals content in sediment is influenced byseveral factors, among others; organic matter content,grain size, and mineralogy. High concentrationsof heavy metals are generally associated with grainsize texture (SE., 2001). Sediment textures onReclamation Island are mainly sand which maybe one of the reasons for the low metal content.Cadmium and lead content in sediment is greaterthan in seawater but below the pollution standard ofsediment. The levels of heavy metal sediment at eachstation can be said not to endanger marine organisms.It is accord to (Permanawati et al., 2013) which statesthat heavy metal content (copper (CU), lead (Pb), zinc(Zn), cadmium (Cd), and chromium (Cr)) in waterand sediments in Jakarta bay waters below pollutionstandard.

3.2 Heavy Metals in Green Mussels

Table 1 shows the concentration of heavy metalsmercury (Hg), cadmium (Cd), and lead (Pb) in thegreen mussels are not detected and below heavymetal pollution standards for bivalves accordingto Badan Standarisasi Nasional (BSN) 7387 (SNI,2009). Mercury, cadmium, and lead contained inwater and sediments have not exceeded the specifiedstandard threshold. This shows that heavy metalconcentration does not pollute the environment eventhough Jakarta bay has the potential to be highlypolluted. Bioaccumulation of heavy metals in greenmussels can occur because heavy metal enters intothe body of the living organism easily and quickly(de Astudillo L. R. et al., 2005). But this research didnot show the accumulation of mercury (Hg), cadmium(Cd), and lead (Pb) on the green mussels. This isprobably due to low of mercury (Hg), cadmium (Cd),and lead (Pb) content in water and sediment. Heavymetal accumulation in aquatic organism according to(SE., 2001) are influenced by many factors, amongothers:

• The concentration of heavy metals in water

• The concentration of heavy metals in sediment

• Acidity of the water and sediment

• Chemical oxygen demand (COD) level in water

• Sulfur content in water and sediment

• Types of aquatic organism

• Organism age and body weight and

• Organism life phases (eggs, larvae)

If concentrations of heavy metals in water arehigh then there is a tendency for heavy metalsconcentrations to be high in sediments, and theaccumulation of heavy metals in the demersalorganism occur (K. et al., 2004; IDL and SM., 1996).

• Seawater Standard Quality for MarineBiota, standard criterion set by IndonesiaGovernment Decree Ministry of Environmentand Development (DMED) No. 51/2004. Tooldetection limit for mercury (Hg) 0.0002 mg/L;cadmium (Cd) 0.00011 mg/L; lead (Pb) 0.00086mg/L.

• Sediments pollution standard in Indonesia hasnot been established. IADC (InternationalAssociation of Drilling Contractors)/ CEDA(Central Dredging Association) (1997) has beenused as standard. Tool detection limit for mercury(Hg) 0.0004 mg/L.

Biosurvey of Mercury (Hg), Cadmium (Cd), and Lead (Pb) Contamination in Reclamation Island-Jakarta Bay

207

Table 1: Water quality and heavy metal content in water, sediment and green mussels.

No. Parameter A B C D TN Standard Quality

Water

Physical

1 Bright(m) 0,9 1,8 1,4 0,9 1,7Coral: >5;mangrove: -;seagrass: >3;natural >0,5

2 Turbidity (NTU) 10,5* 7,0* 4,5 8,3* 5,5* <5

3 Total suspended solid(mg/L)

9,3 7,3 8,3 13,0 3,6 20

4 Waste - - 3 5 - Nihil

5 Temperature (0C) 28,9 28,7 29,0 29,1 30,2 Natural (20-30)

Chemical

pH 8,4 8,6 8,6 8,9* 8,6 7-8,5

1 Salinity (%) 29,3* 30,0 30,1 30,2 30,8 Natural (30-40)

2 Disolved oxygen (mg/L) 3,89* 4,70* 4,67* 4,55* 5,16 >5

3 COD (mg/L) 70,0* 85,1* 71,2* 79,6* 81,7* 20

4 BOD (mg/L) 265,3* 474,8* 373,8* 593,2* 418,2* 20

5 Mercury (mg/L) nd** nd** nd** nd** nd** 0.001

6 Cadmium (mg/L) nd** nd** nd** nd** nd** 0.001

7 Lead (mg/L) nd** nd** nd** nd** nd** 0.008

Sediment

1 Mercury (mg/L) nd** nd** nd** nd** nd** 0.03

2 Cadmium (mg/L) 0.14 0.07 0.08 0.15 0.09 0.8

3 Lead (mg/L) 3.19 2.29 2.1 4.62 2.5 85

Green mussels

1 Mercury (mg/l) nd** nd** nd** nd** nd** 1

2 Cadmium (mg/l) nd** nd** nd** nd** nd** 1

3 Lead (mg/l) nd** nd** nd** nd** nd** 1.5*value higher than pollution standard, ** nd=not detected

Figure 2: Mechanism of accumulation and detoxification of heavy metals by bivalves (Soto et al., 2003)

• Green mussels pollution standard based onStandar Nasional Indonesia (SNI) 7387: 2009[17] as the maximum limit of heavy metal

contamination in food. Tool detection limit formercury (Hg) 0.009 mg/L; cadmiun (Cd) 0.00011mg/L; lead (Pb) 0.00086 mg/L.


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The heavy metals entering cells through the lipidlayer of the membrane by endocytosis, through apumping and organic chelating system. Non-essentialmetals that enter the cells will compete with essentialmetal to bind to ligands. Binding mechanism ofmetal and proteins generally damages sulfide bonds(N. et al., 2004). Metals binding to biomolecules thenwill accumulate in hepatopancreas or be detoxify.The mechanism of accumulation and detoxificationof heavy metals in bivalve can be seen in Figure2. Heavy metals modify existing enzyme processesby interfering with and replace calcium (Ca) ionsthat affect oxidation. In this research-heavy metalmercury (Hg), cadmium (Cd), and lead (Pb) ofgreen mussels samples are inert within the acceptablelimit for green mussels and other predators. Thiscan be observed from the absence of heavy metalsaccumulation in mussels indicating that cadmium(Cd) and lead (Pb) in sediments that enter musselsbody has been detoxified.

3.3 Heavy Metal Pollution Level onReclamation Island

Pollution level of heavy metal on water, sediments,and biota are determining using STORET method(US-EPA/United States Environmental ProtectionAgency) based on scores (Decree of the Ministerof Environment (DMED) no. 115/2003 aboutGuidelines for Determining Status of Water Quality)(DMED No.115, 2003). Results show that heavymetal mercury, cadmium, and lead in water,sediments, and green mussels around reclamationisland are below standard quality so that it is includedin class A. This is probably due to the intensity ofwaste disposal consist of low heavy metals.

Although in this research there was no heavymetal pollution, it does not indicate the conditionaround the reclaimed island is good. Physical andchemical analysis of water shows that turbidity,Biological Oxygen Demand (BOD), ChemicalOxygen Demand (COD), and dissolved oxygen(DO) parameters do not comply with water qualitystandards in Decree Ministry of Environment andDevelopment No. 51/2004. Biological OxygenDemand (BOD) concentrations in water range from265,3 to 593,2 mg/L, it is much higher than thestandard quality which is 20 mg/L. Chemical OxygenDemand (COD) concentrations in water range from70,0 to 85,1 mg/L that higher than the standardquality which is 20 mg/L. dissolved oxygen (DO)concentrations in water range from 3,89 to 5,16 mg/Lthat below than the standard quality which is 5 mg/Lexcept for Teluk Naga station. These parameters

illustrated the high pollution around the reclaimedisland.

4 CONCLUSIONS

Based on the results it can be concluded that :

• Mercury (Hg), cadmium (Cd) and lead (Pb)content in the water below the water qualitystandard for biota. Mercury (Hg), cadmium (Cd)and lead (Pb) content in sediments below thestandard set by IADC/CEDA. The content ofheavy metal in water and sediment of reclamationislands are safe for biota. High Biological OxygenDemand (BOD) and Chemical Oxygen Demand(COD) content showed high organic pollutionaround reclaimed islands C and D

• There is no accumulation of heavy metal mercury(Hg), cadmium (Cd) and lead (Pb) occur in greenmussels.

• Heavy metal pollution level in the water,sediment, and green mussel organs based on theSTORET (US-EPA) method included in class Awhich is classified as not contaminated by heavymetals mercury (Hg), cadmium (Cd), and lead(Pb). Mercury (Hg), cadmium (Cd), and lead(Pb) quality index in reclamation island C and Damounts to 18 so that it is classified as good.

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Cordova, M. R., Purbonegoro, T., Puspitasari, R., andHindarti, D. (2016). Assessing contamination level ofjakarta bay nearshore sediments using green mussel(perna viridis) larvae. Mar. Res. Indonesia, 41:67–76.

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Cordova, R. M. (2011). Akumulasi logam berat pada keranghijau (perna viridis) di perairan teluk jakarta. JurnalMoluska Indonesia, 2:1–8.

de Astudillo L. R., C., Y. I., and I., B. (2005). Heavy metalsin sediments, mussels and oysters from trinidad andvenezuela. Int. J. Trop. Bio., 53(1):41–53.

Dumalagan, H., Gonzales, A., and Hallare, A. (2010). Tracemetal content in mussels, perna viridis l., obtainedfrom selected seafood markets in a metropolitancity. Bulletin of environmental contamination andtoxicology, 84(4):492–496.

HP., H. (1984). Logam berat dalam lingkungan laut.Pewarta Oceana IX, 1:12–19.

IDL, F. and SM., C. (1996). Heavy metals in thehydrological cycle: trends and explanation.

K., W. C. (1922). A scale of grade and class terms for clasticsediments. The Journal of Geology 30, 5:377–392.

K., Y. C., A., I., and G., T. S. (2004). Biomonitoringof heavy metals in the west coastal of peninsularmalaysia using the green-lipped mussel perna viridis,present status and what next? pertanika. J. Trop.Agric. Sci., 27(2):151–16.

Koropitan, A. F. and Cordova, M. R. (2017). Study of heavymetal distribution and hydrodynamic simulation ingreen mussel culture net, cilincing water-jakarta bay.Makara Journal of Science, 21(2).

Miller, D. A. and White, R. A. (1998). 1998: Aconterminous united states multi-layer soilcharacteristics data set for regional climate andhydrology modeling. Earth Interactions, 2.

N., A., V., R. T., and D., K. R. (2004). Biosorption of HeavyMetals. Bangalore, Indian Institute of Science.

Permanawati, Y., Zuraida, R., and Ibrahim, A. (2013).Kandungan logam berat (cu, pb, zn, cd dan cr) dalamair dan sedimen di perairan teluk jakarta. JurnalGeologi kelautan, 11(1).

PSWQA. (1997). Recommended guidelines for samplingmarine sediment, water column, and tissue in pugetsound. For. U.S. Environmental Protection AgencyRegion 10.

Putri, L. S. E., Prasetyo, A. D., and Arifin, Z. (2012).Green Mussel (Perna viridis L.) as Bioindicator ofHeavy Metals Pollution at Kamal Estuary jakartabay, indonesia. J. of Environmental Research andDevelopment, 6(3):389–396.

S, D. and MH., B. (2010). Industrial pollution and heavymetals profile of challawa river in kano. Nigeria. JAppl Sci Envi Sanitation, 5(1):23–29.

SE., M. (2001). Fundamental Of Environmental Chemistry.Lewis Publishers: United State of America.

SNI, B. (2008). Cara Uji Penentuan Kadar Air untuk Tanahdan Batuan di Laboratorium. Jakarta: BSN.

SNI, B. (2009). Batas Maksimum Cemaran Logam Beratdalam. Makanan, SNI, 7387:2009.

Soto, M., M., I., and C., I. (2003). Biological Aspects ofMetal Accumulation and Storage. University of theBasque Country: Bilbo.

Suryono, C. A. (2006). Kecepatan Filtrasi Kerang HijauPerna viridis terhadap Skeletonema sp pada Media

Tercemar Logam Berat Timbal (Pb) dan Tembaga(Cu). Ilmu Kelautan, 11(3):153 – 157.

Warner, M. L. and Preston, E. H. (1974). A reviewof environmental impact assessment methodologies,volume 3. Office of Research and Development, USEnvironmental Protection Agency: for . . . .


210

Expert System to Detect Early Depression in Adolescents using DASS 42

Nesi Syafitri, Yudhi Arta, Apri Siswanto and Sonya Parlina RizkiDepartment of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesianesisyafitri,yudhiarta,[email protected], [email protected]

Keywords: Case Based Reasoning, DASS 42, Expert System

Abstract: Around 5% adolescents in Indonesia suffer from depression at the certain time. To identify the level ofdepression, direct consultation with an expert like alienist or psychologist is needed. However, the problem isthe number of experts in hospital and culture social environment is limited, also the society is not used to doconsultation to alienist or psychologist. Therefore, a system that can help the medical to detect early depressiondisorder is needed, before the adolescents do the next consultation to the medical. The system called as expertsystem with web based which built by Case Based Reasoning (CBR) and using Simple Matching Coefficient(SMC) method also DASS 42 as the research instrument. Based on the 200 data testing on 500 and 700 casebase, this expert system can detect the early disorder with an precision rate more than 90%. So that, with thisexpert system the early disorder can be done accurately and fast.

1 INTRODUCTION

Depression is a mood disorder characterized by lossof feelings of control and subjective experience ofsevere suffering. Depression will cause feelingsof depression (sadness, disappointment, futility),loss of energy and interest, feelings of guilt,loss or difficulty concentrating, loss of appetiteto suicidal desires and sometimes self-degradingbehaviour (Faia et al., 2017; Shen et al., 2017).Depression that is not detected early in adolescentscan eventually lead to serious difficulties in school,work, and personal adjustment which often continuesin adulthood. To be able to correctly identify thelevel of depression experienced by a adolescents,parents or teachers must consult directly with experts,both psychiatrists and psychologists. However,the obstacle is the limited number of psychiatricexperts who are not available in all hospitals andthe sociocultural environment in the community thatis not accustomed to consulting a psychiatrist andpsychologist (Haryanto et al., 2016; Syafitri andApdian, 2016; Syafitri and Saputra, 2017).

Expert system is a computer program designedto solve problems like an expert, by transferringexpertise so that other people (non-experts) can solveproblems that are usually carried out by an expert (Guet al., 2017; Rahman et al., 2018). The representationof knowledge representation using Case BasedReasoning (CBR) is a collection case-based that has

never happened before. CBR uses solutions fromprevious cases that are similar to new cases to solveproblems. Various methods can be used to measurethe level of similarity of old cases with new cases.One of similarity methods used is Simple MatchingCoefficient (SMC).

Some studies in the domain of expert systems withCBR used as a reference are research conducted byFaizal, E (2014) applying CBR to build a systemthat has the ability to diagnose cardiovascular diseasebased on similarity in previous cases using methodSMC. The test results show that the system builthas a sensitivity value of 97.06%, specificity of64.29%, positive predictive value (PPV) of 86.84%,negative predictive value (NPV) of 90.00%, accuracyof 87.50% with level error (error rate) of 12.50%(Faizal, 2014; Syafitri and Sari, 2017; Syafitri et al.,2018).

2 RESEARCH METHOD

Research method is the stages passed by theresearcher to get description of the research. Thestages passed in the research method are follows:

2.1 Data Collection

The data collection techniques needed in making thissystem are as follows:

Syafitri, N., Arta, Y., Siswanto, A. and Rizki, S.Expert System to Detect Early Depression in Adolescents using DASS 42.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 211-218ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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• Interviews conducted directly with Psychologyexperts.

• Distribution of online questionnaires to 700adolescents aged 17 to 21 through Google Formsto obtain case base data and test data.

• Literature studies through scientific referencesfrom various sources related to the problem understudy, both from books, scientific journals andfrom other readings that can be justified.

2.2 Adolescents

In English adolescents are called adolescent, derivedfrom the word adolescent which means growingtoward maturity. Adolescents is a period of transitionbetween childhood and adulthood. At this time,adolescents experience the development of achievingphysical, mental, social and emotional maturity andthe emotional state of adolescents is still unstablebecause it is closely related to hormonal conditions.Hurlock (1980), divides adolescents into two parts,namely early adolescents and late adolescents. Earlyadolescents lasts approximately from the age of 13-16years and the late adolescents starts from the age of17-21 year(Holmbeck, 2018; Weis, 2017).

Adolescents is a period of developmentaltransition between childhood and adulthood whichincludes biological, cognitive and social emotionalchanges. In English teenagers are called adolescent,derived from the word adolescent which meansgrowing toward maturity. Adolescence is a periodof transition between childhood and adulthood. Atthis time, adolescents experience the developmentof achieving physical, mental, social and emotionalmaturity and the emotional state of adolescents isstill unstable because it is closely related to hormonalconditions. Emotional emotions dominate andcontrol themselves from a realistic mind (Rosenberg,2015; Coleman, 2006).

2.3 Depression

Depression is a period of disruption of humanfunction related to natural feelings of sadness andaccompanying symptoms, including changes in sleeppatterns and appetite, psychomotor, concentration,anhedonia, fatigue, hopelessness and helplessness,and suicide. Depression is likened to flu, becausedepression can occur in all circles, includingadolescents (Kaplan et al., 2010; Amelia et al., 2018).There are 3 levels of depression :

• Mild DepressionAt this level, the symptoms usually affect the

daily activities of people who experience it suchas being less interested in doing things that areusually done, easily angry, the motivation towork becomes less. This depression is not toodisturbing, but must be treated to prevent thecondition from getting worse.

• Middle Depression (Moderate Depression)At this level, this depression causes a person toexperience difficulties in terms of social, workand domestic activities. In moderate depression,usually a person becomes less confident sohe or she is less motivated to do something.Often a person starts to worry about things thatare unnecessary, more sensitive, and vulnerableto feelings of hurt or offense in personalrelationships.

• Severe DepressionAt this level, this depression causes a personto experience severe suffering such as feelinga loss of self-esteem or feeling useless andguilty, and wanting to commit suicide. A personwho is severely depressed cannot manage hisemotions so that he easily experiences feelings ofdespair. People with severe depression may alsosuffer from delusions, hallucinations or stupordepressive.

Anxiety can be divided according to the sourceof reason, namely: Anxiety that comes from theenvironment, called objective anxiety that is anxietycaused by the environment and does not needtreatment, because it is one of the factors ”self-care”.Anxiety in the body is called vital anxiety, namelyanxiety that originates in the body and functions asa definition mechanism that protects the individual.Awareness of consciousness is called conscienceanxiety, that is, individuals have an awareness ofmorality that will protect individuals against acts thatare immoral (Lovibond and Lovibond, 1995).

Problems experienced by adolescents in fulfillingthe tasks of adolescent development, namely:

• Personal problems, namely problems related tosituations and conditions in the home, school,physical condition, appearance, emotions, socialadjustment, duties, and values.

• Typical teen problems, namely problems thatarise due to unclear status in adolescents, suchas the problem of achieving independence,misunderstanding, the existence of greater rightsand fewer obligations imposed by parents.


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2.4 Expert

Systems Knowledge-based systems, also knownas expert systems, are one branch of artificialintelligence, which in the commercial world iscalled a system that can effectively and efficientlycarry out tasks that do not really require experts.Expert systems are also known as advisory systems,knowledge systems, intelligent work assistancesystems or operational systems (Aronson et al., 2005).

2.5 Case Based Reasoning (CBR)

Case Based Reasoning (CBR) is a system that aims toresolve a new case by adapting the solutions foundin the previous case that are similar to the newcase. The basic idea of CBR is to imitate humanabilities, namely solving new problems using answersor experiences from old problems. Representation ofknowledge is made in the form of cases. Each casecontains problems and answers, so the case is morelike a certain pattern. The way CBR works is tocompare new cases with old cases. If the new casebears a resemblance to the old case, the CBR willprovide an answer to the old case for the new case.If there is no match, the CBR will adapt, by insertingthe new case into a case base, so that indirectly CBRknowledge will increase (Li et al., 2018).

Figure 1: System Architecture CBR.

2.6 Simple Matching Coefficient (SMC)

There are a variety of techniques that can be used tomeasure the similarity of a case with an old case on acase base. One of methods similarity that can be usedis Simple Matching Coefficient (SMC) with equation(1) (Faizal, 2014).

SMC(X ,Y ) =M11 +M00

M01 +M10 +M11 ++M00(1)

Description:X = Old caseY = New caseM11 = Number of attributes where X = 1 and Y = 1M00 = Number of attributes where X = 0 and Y = 0M01 = Number of attributes where X = 0 and Y = 1M10 = Number of attributes where X = 1 and Y = 0

2.7 Feasibility System

Feasibility system is obtained by finding the value ofprecision and recall systems based on comparison ofthe results of detection by experts using the DASS42 calculation with the results of detection by thesystem. Before getting precision and recall values,need the True Positive (TP), True negative (TN), FalsePositive (FP) and False Negative (FN). These valuesare measured using information retrieval (Huiberset al., 1996). Precision and recall can go through theformulas in equations (2) and (3).

Precision(P) =| T PT P+FT

| ∗100% (2)

Recall(R) =| T PT P+FN

| ∗100% (3)

2.8 DASS 42

The severity of depression, anxiety, and stress whata person experiences can be measured on manyscales including using the Depression Anxiety StressScale 42 or abbreviated with DASS 42 developed byLovibond & Lovibond (1995). DASS is a 42-itemquestionnaire that includes three scales to measurenegative emotional states of depression, anxiety andstress. Each of the three scales contains 14 items.Scores for each respondent during each sub-scale,then evaluated according to their severity (Lovibondand Lovibond, 1995).


213

Table 1: Score DASS 42 (Lovibond & Lovibond 1995).

Level of Depression Anxiety Stress

Normal 0-9 0-7 0-14Mild 10-13 8-9 15-18Medium 14-20 10-14 19-25Severe 21-27 15 - 19 26 - 33Extremely severe >28 >20 >34


3.1 Testing on 500 Case Bases

There are 100 test data with an equal number ofdetection rates of 20: 20: 20: 20: 20 in anxietydetection, 20: 20: 20: 20: 20 in stress detection and20: 20: 20: 20: 20 in depression detection . Thecomparison sample of detection results is shown intable 2.

Based on table 2, the number of detection levelsin the test data is shown in table 3.

Testing on Detection of Depression

Figure 2: Information Retrieval on Comparison ofDetection Results of Depression (Based on Table 3).

Based on figure 2, the precision and recall valuesof depression detection can be found as follows:

(4)

Precision(P) =[ T P

T P+FT

]∗ 100%

=[ 94

94+6

]∗ 100%

=[ 94

100

]∗ 100%

= 94% .

(5)

Recall(R) =[ T P

T P+FN

]∗ 100%

=[ 94

94+406

]∗ 500%

=[ 94

500

]∗ 100%

= 18,80% .

Testing the Amount of Random Detection Rate.There are 100 test data with a number of random

detection rates of 14: 15: 30: 25: 16 in anxietydetection, 11: 22: 41: 17: 9 in stress detectionand 8: 13: 35: 35: 9 in depression detection. Thecomparison sample of detection results is shown intable 4.

Based on table 4, the number of detection levelsobtained in the test data is shown in table 5.


Figure 3: Retrieval of Information on Comparative ResultsDetection of Depression (Based on Table 5).

Based on Figure 3, the precision and recall valuesof depression detection can be found as follows:

(6)

Precision(P) =[ T P

T P+FT

]∗ 100%

=[ 97

97+3

]∗ 100%

=[ 97

100

]∗ 100%

= 97% .

(7)

Recall(R) =[ T P

T P+FN

]∗ 100%

=[ 97

97+403

]∗ 100%

=[ 97

500

]∗ 100%

= 19,40% .


214

Table 2: Comparison of Test Data Detection Results by Experts with a System with an Equal Alignment Detection Level.

NoAnxiety Detection

ResultsStress Detection

ResultsDepression Detection

ResultsExpertResults

ExpertResults

ExpertResults

ExpertResults

ExpertResults

ExpertResults

1 Normal Normal Normal Normal Normal Normal2 Normal Normal Normal Normal Normal Normal3 Normal Normal Normal Normal Normal Normal4 Normal Normal Normal Normal Normal Normal5 Normal Normal Normal Normal Normal Normal6 Normal Normal Normal Normal Normal Normal. . . . . . .. . . . . . .. . . . . . .

97 Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe98 Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe99 Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe

100 Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe

Table 3: Number of Detection Levels on Test Data (Basedon Expert Results).

No Anxiety Detection Results Stress Detection Results Depression Detection ResultsDetection rate Total Detection rate Total Detection rate Total

1 Normal 20 Normal 20 Normal 202 Mild 20 Mild 20 Mild 203 Medum 20 Medum 20 Medum 204 Severe 20 Severe 20 Severe 205 Extremely severe 20 Extremely severe 20 Extremely severe 20

Total 100 Total 100 Total 100

Table 4: Comparison of Test Data Detection Results byExperts with a System with an Equal Alignment DetectionLevel.




3.2 Testing on 700 Case Bases

Testing is focused on similarity testing, where thedata to be tested consists of 200 depression data testthat are tested on 500 case base and on 700 casebase. 200 data test on the detection of depression aresubdivided into 2 which 100 data test with an equalnumber of detection levels with 20:20:20:20:20 dataand 100 data test with a random number of detectionlevels with 8:13:35:35:9 data. Experts will look fordetection results in the data test on each test using theDASS 42 calculation.

Based on table 6, obtained the number of detectionlevels in the test data shown in table 7.


Based on figure 2, the precision and recall valuesof depression detection can be found as follows:


(8)

Precision(P) =[ T P

T P+FT

]∗ 100%

=[ 100

100+0

]∗ 100%

=[ 100

100

]∗ 100%

= 100% .

(9)

Recall(R) =[ T P

T P+FN

]∗ 100%

=[ 100

100+600

]∗ 100%

=[ 100

700

]∗ 100%

= 14,29% .

Testing the Amount of Random Detection Rate


215

Table 5: Number of Detection Levels on Test Data (Based on Expert Results).

No Anxiety Detection Results Stress Detection Results Depression Detection ResultsExpert Results Expert Results Expert Results Expert Results Expert Results Expert Results

1 Mild Mild Extremely severe Extremely severe Extremely severe Extremely severe2 Mild Mild Severe Severe Extremely severe Extremely severe3 Mild Medium Severe Severe Mild Medium4 Normal Normal Severe Severe Severe Severe5 Mild Mild Severe Severe Medium Medium6 Mild Mild Severe Severe Severe Severe. . . . . . .. . . . . . .. . . . . . .

97 Extremely severe Extremely severe Mild Mild Medium Medium98 Extremely severe Extremely severe Medium Medium Medium Medium99 Severe Severe Mild Mild Severe Severe

100 Severe Medium Medium Medium Medium Medium

Table 6: Comparison of Test Data Detection Resultsby Experts with Systems with Amount of Equal LevelDetection.




There are 100 test data with a number of randomdetection rates of 14: 15: 30: 25: 16 in anxietydetection, 11: 22: 41: 17: 9 in stress detectionand 8: 13: 35: 35: 9 in depression detection. Thecomparison sample of detection results is shown intable 8.

Based on table 8, the number of detection levelsin the test data is shown in table 9.

Testing on Detection of DepressionBased on figure 5, we can find the value of

precision and recall value of depression detection asfollows:

(10)

Precision(P) =[ T P

T P+FT

]∗ 100%

=[ 100

100+0

]∗ 100%

=[ 100

100

]∗ 100%

= 100% .

(11)

Recall(R) =[ T P

T P+FN

]∗ 100%

=[ 100

100+600

]∗ 100%

=[ 100

700

]∗ 100%

= 14,29% .

Based on Table 10, the first with 100 test data withthe equal number of detection with 20:20:20:20:20data which tested at 500 case base explained thatpercentage of precision is 94% and percentage ofrecall is 18.80%. The second test with 100 data


test with the random number of detection with8:13:35:35:9 data which tested at 500 case baseexplained that percentage of precision is 97% andpercentage of recall is 19.40%.

Based on table 11, both the third test with 100 withthe equal number of detection with 20:20:20:20:20data and the fourth test with 100 test data with therandom number of detection with 8:13:35:35:9 datawhich was tested at 700 case base explained that allpercentages of precision is 100

Based on the testing, the percentage of precisionis 100% at 700 case base and are ¿ 90% at 500 casebase so it can be concluded that the number of casebase affects the percentage of precision in the system.


216

Table 7: Number of Detection Levels on Test Data (Based on Expert Results).

NoAnxiety Detection

ResultsStress Detection

ResultsDepression Detection

ResultsExpert Results Expert Results Expert Results Expert Results Expert Results Expert Results

1 Normal Normal Normal Normal Normal Normal2 Normal Normal Normal Normal Normal Normal3 Normal Normal Normal Normal Normal Normal4 Normal Normal Normal Normal Normal Normal5 Normal Normal Normal Normal Normal Normal6 Normal Normal Normal Normal Normal Normal. . . . . . .. . . . . . .. . . . . . .

97 Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe98 Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe99 Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe

100 Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe Extremely severe

Table 8: NumberComparison of Detection Results of Test Data by Experts with Systems with Amount of Random DetectionRate.

No Anxiety Detection Results Stress Detection Results Depression Detection ResultsExpert Results Expert Results Expert Results Expert Results Expert Results Expert Results

1 Mild Mild Extremely Severe Extremely Severe Extremely Severe Extremely Severe2 Mild Mild Severe Severe Extremely Severe Extremely Severe3 Mild Mild Severe Severe Mild Mild4 Normal Normal Severe Severe Severe Severe5 Mild Mild Severe Severe Medium Medium6 Mild Mild Severe Severe Severe Severe. . . . . . .. . . . . . .. . . . . . .

97 Extremely Severe Extremely Severe Mild Mild Medium Medium98 Extremely Severe Extremely Severe Medium Medium Medium Medium99 Severe Severe Mild Mild Severe Severe

100 Severe Severe Medium Medium Medium Medium

Table 9: Number of Detection Levels on Test Data (Basedon Expert Results).




Table 10: Testing Conclusions on 500 Case Base.

DetectionTested on 500 Case Base

100 Equal Data Test 100 Random Data TestPrecision Recall Precision Recall

Depression 94% 18,80% 97% 19,40%Average 95,33% 19,07% 95,67% 19,13%

Table 11: Test Conclusions on 700 Case Base.

DetectionTested on 700 Case Base

100 Equal Data Test 100 Random Data TestPrecision Recall Precision Recall

Depression 100% 14,29% 100% 14,29%Average 100% 14,29% 100% 14,29%

4 CONCLUSIONSTesting is focused on similarity testing, where thedata to be tested consists of 200 depression data test

that are tested on 500 case base and on 700 casebased. 200 data test on the detection of depression aresubdivided into 2 which 100 data test with an equalnumber of detection levels with 20:20:20:20:20 dataand 100 data test with a random number of detectionlevels with 8:13:35:35:9 data. Experts will look fordetection results in the data test on each test using theDASS 42 calculation.

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Geotechnics Analysis: Soil Hardness on Stability of Davit Kecil’s Weir inUlu Maras, Kepulauan Anambas, Kepulauan Riau

Miftahul Jannah1, Dewandra Bagus Eka Putra1, Firman Syarif2, Joni Tripardi3, Nopiyanto3 andHusnul Kausarian1

1Department of Geological Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Department of Civil Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

3Water Resources, Department of Public Works and Housing, Kepulauan Anambas, [email protected], dewandra.bagus, [email protected], [email protected],


Keywords: Geotechnics, Weir Stabillity, Sieve Analysis, Direct Shear Stress, Kepulauan Riau.

Abstract: Davit Kecil’s weir is an irrigation area that located in Ulu Maras Village, East Jemaja District, KepulauanAnambas Regency, Kepulauan Riau Province. The needs of a geotechnical study are important to determinethe soil properties and soil stability of the study area, those parameters will be used to identify the stability ofthe weir structure. Methods used are field study by taking soil samples and conduct laboratory analysis suchas sieve analysis, hydrometer analysis, atterberg limits and direct shear stress that useful for soil resistanceidentification. Based on the laboratory test result, Hb.2 and Hb.3 are non- plastic soils with uniformitycoefficient are 20.92 – 45.38 and coefficient of gradation is 6 – 15.68. So, the soils as categorized as verygood on uniformity and good on gradation. The value of direct shear stress with cohesion (c) is 0.06 and φobtained were in the range of 33.78 – 34.33. Soil grain size identified from sieve analysis is gravel-clay. Basedon the analysis result, the stability of Davit Kecil’s weir that was observed from normal water condition andflood water condition is categorized into strong-safe weir characterized by sufficient eccentricity and bearingcapacity control. In addition, the weir is withstand rolling and sliding failures.

1 INTRODUCTION

Weir is an across building on river channel thatfunctions to raise the river’s water level. Weir isa solution in various problems that related to waterresources, utilization, management and preservation(Sadono et al., 2017). It was commonly built fromsoil and rock materials (Athani et al., 2015), thatcollected a water reserve as a reservoir in order tomaintain stable water supply both in rainy and dryseasons (Sompie et al., 2015). Weir is a buildingthat perpetually related with the water (Harseno andDaryanto, 2008). It could also be defined as a buildingthat planted in the river or water flow to deflect waterinto irrigation (Gunasti, 2016; Putra et al., 2016).

Jemaja’s irrigation area is located in JemajaIsland, Kepulauan Anambas Regency, KepulauanRiau Province. Based on the regulation fromMinistry of Public Works and Housing (PUPR)No.14/PRT/M/2015 about The Criteria andStipulation of Irrigation Area Status, KepulauanAnambas Regency has the authorization of irrigation

area as wide as ±386 ha. A study by BWS SumatraIV said this time around 637,48 ha Irrigation Areawas indicated as irrigation area and ±793,43 ha thathas the potency to be convert into irrigation area.

As a follow-up, the management of irrigationthat could be utilized effectively and optimally thendeveloped an irrigation area that potentially as anirrigation area. Other than that, the aims to planthe development irrigation area should estimating thetechnique, economical and environmental aspects.

The weir conditions need to fulfill several factorsto be stable and able to control a flood condition. Theweir construction should be calculated the strength ofbearing capacity of subsurface soil, the weir must beable to hold-out a seepage caused by river water flowand water infiltration into the soil, the weir heightmust be able to fulfill the minimum water level whichis needed for the whole irrigation area and the form ofa boiler must be calculated so the water can transporta sand, gravel and any stones from upstream and notcause damage to the weir’s body (Erman and M.,2010).

Jannah, M., Putra, D., Syarif, F., Tripardi, J., Nopiyanto and Kausarian, H.Geotechnics Analysis: Soil Hardness on Stability of Davit Kecil’s Weir in Ulu Maras, Kepulauan Anambas, Kepulauan Riau.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 219-228ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

219

Figure 1: The administration map of Kepulauan Anambasregency.

2 METHODOLOGY

Methods used in this study are field survey, laboratoryanalysis and the calculation of dam stability. Theexplanation of each analysis is as follows:

2.1 Field Survey

The field survey was done to obtain primary data suchas planning location, identified soil layers by usingborehole data in several points. In addition, drillingis done to take soil sample which would be analyzedin the laboratory (Susanto H, 2014). Field surveyalso conducted by using hand bore that useful to findout the soil layers on the subsurface. The standardprocedure that used in hand bore work is ASTM D –1452 – 80. There are 2 boreholes that can be seen intable (1) and figure (1) below.

Based on the Regional Geology Map (Samodra,1995), in this two points, the study area was includein Granit Anambas Formation. There are granite,granodiorite and syenite in this formation. Thegeneral soil condition is grey, brown and pink incolour.

Table 1: Borehole location and soil testing.

No Locationname

CoordinatesX Y

1 HB.2 N255’19.64” E105244’17.83”2 HB.3 N255’18.50” E105244’18.64”

Figure 2: The topography map in the study area shows handbore points and weir location

2.2 Laboratory Test

Laboratory test consists of undisturbed and disturbedsamples taken from selected locations (Sompie et al.,2015). Laboratory test used to determine the mosteffective and suitable location of dam constructionin the study area. Several laboratory tests hadbeen conducted such as sieve analysis, hydrometeranalysis, atterberg limits and direct shear stress.

2.2.1 Sieve and Hydrometer Analysis

Sieve and hydrometer analysis are the methods todetermine the soil grain size at the borehole points.Soil classification calculated based on particle sizefrom sieve and hydrometer analysis (ASTM, 2007).

There are uniformity coefficient (Cu) andcoefficient of gradation (Cc) that obtained from sieveand hydrometer curve. The calculation (1) and (2)are:

Cu =D60

D10(1)

Cc =D302

D10×D60(2)

where:

Cc = coefficient of gradation


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Figure 3: The USCS triangle

Cu = uniformity coefficient

D10 = diameter of 10% finer



2.2.2 Atterberg Limit

Atterberg Limit used to identify the soil propertiessuch as Liquid Limit (LL), Plastic Limit (PL)and Plasticity Index (PI). The type of soil can bedetermined based on the Plasticity Index’s (PI) valueand then the value is inserted into the plasticity chart.When the atterberg limit’s status is non-plastic, thetriangle (figure 3) can be used.

Other than that, here is the formula of AtterbergLimits to calculated Plastic limit from ASTM D 424-54 (3), Liquid limit from ASTM D 422 – 66 (4) andPlasticity index from ASTM D 424 – 74 (5).

w =(m2−m3

m3−m1

)×100% (3)

LL = w×(N0.121

25)

(4)

PI = LL−PL (5)

wherein:

w = water content (%)

N = number of beats

m1 = container mass (gr)

m2 = container mass + wet soil (gr)

m3 = container mass + dry soil (gr)

PI = Plastic Index (%)

LL = Liquid limit (%)

PL = Plastic limit (%)

2.2.3 Direct Shear Stress

This test is used to determine the soil shear stress afterits experienced a consolidation by loaded with two-way drainage. On the soil mechanics calculation, thedirect shear stress is stated as cohesion (c) and deepfriction angle () (Adama, 2017). The deep frictionangle used to determine the main material in the weir.

2.3 Weir Stability

Weir stability analysis is useful to indicating theforces that worked on the weir. The calculationused are own gravity (G), Earthquake force (K),hydrostatic force (W), Mud pressure (L) and upliftpressure (Px). To calculated own gravity andhydrostatic force the weir was partially divide intoseveral shape such as triangles, rectangulars ortrapezoid (Ali, 2014). The earthquake coefficientdepends on the construction site. In this study area,K is 0,15. According to Radjulaini (2012), on theconstruction by using stone should not occur tensilestress. Moment of resistance (Mt) must greater thanthe moment of rolling (Mg) with the safety factorbetween 1.5-2. The construction should not shift withthe safety factor is 1.2-2.

E =Wbs.α (6)

Lp =γs.h2

2.(1− sin ϕ

1+ sin ϕ)

(7)

Px = Hx−Lx

L.∆H (8)

wherein:

E = earthquake forces (ton)

Wbs = own gravity in the vertical direction (ton)

α = earthquake coefficient

Lp = force located at 2/3 of the depth of the top ofthe mud that works horizontally (m)

γs = mud specific gravity (γs = 1.6 kN/m 3 )

H = thick mud (m)

ϕ = friction angle in mud (ϕ=20 o )

Px = uplift force on x point (kg/m 2 )

Hx = height x (m)

∆ = high difference (m)

L = total length of creep line on the weir (m)

Lx = length of creep line until x point (m)

Geotechnics Analysis: Soil Hardness on Stability of Davit Kecil’s Weir in Ulu Maras, Kepulauan Anambas, Kepulauan Riau

221

Dam stability in terms of rolling, sliding,eccentricity and soil bearing capacity were calculated.The dam stability analysis is observed from 2 (two)water level conditions, that is normal water conditionand flood water condition. The following areformulas used in this calculation.

Fx =∑MT∑MG

> 1.25 (9)

Fx =∑V.tan ϕ

∑H> 1.00 (10)

a =∑MT −∑MG

∑H

e =B2−a <

B6

(11)

σ =∑VB×(1± 6e

B

)< σi jin (12)

where:Fx = safety value

∑ V = total of vertical force

∑ H = total of horizontal force

∑ MT = total of the moment of resistance

∑ MG = total of the moment of rollinge = eccentricityσ = soil stress (σijin = 3.75 kg/m2)


The result and discussion of each analysis that hasbeen done in this study are:

3.1 Field Survey

The following are soil layers in the drill point at adepth of 4 meters.

In this location (figure 4), the description of layerssoil are:

- At depth 30 – 100 cm there is silty sand, the colouris brownish yellow, solid and low plasticity.

- At depth 100 – 400 cm there is silty clay with sandinsert, the colour is yellow, rather soft – medium,medium – high plasticity.In this location, the description of layer soil (figure

5) is:- At depth 0 – 50 cm there is sandy-silt with fine

sand grains, the colour is brownish yellow, ratherloose and hard.

- At depth 50 – 400 cm there is sand with mediumsand grains, the colour is yellow, rather loose –solid.

Figure 4: The sediment log at HB.2

3.2 Laboratory Test

The result of laboratory analysis in the study areaare sieve and hydrometer analysis, atterbeg limit anddirect shear stress.

3.2.1 Sieve and Hydrometer Analysis

There are the result of sieve and hydrometer analysisfrom the soil samples taken at 3.5 – 4.00 m in each


222

Figure 5: The sediment log at HB.3

borehole. Based on the table below, the value will beplotted into the grain-size curve (figure 6).

From the curve, it could be seen that the resultof grain size curve has gap graded because it has acombination of more than 2 fractions with the similargradation. The type of grain size on sieve analysisfromvthe curve above are gravel – fine sand.

Whereas, hydrometer analysis indicated the grainsize type as silt – clay. Based on the classification ofgrain size, the type of soil is sandy loam (SM) withtexture non-sticky and non-plastic (figure 7).

The uniformity coefficient (Cu) calculation andcoefficient of gradation were carried out using thediameter value that obtained from the curve areD10 = 0.006, D30 = 0.15852 and D60 = 0.2723.

So, the value of Cu and Cc based on the diameterby curve are 45.38 and 15.68. Accordingly, the soilsample has a very good grain uniformity and goodgradation.

For HB.3, the result of sieve and hydrometeranalysis are (table 3):

From the curve above, indicated the gap graded

Table 2: Result of Sieve and hydrometer analysis of HB.2

SIEVE

Sievenumber

HB.2Diameter

(mm)Percentage

(%)0 0.00 100.04 4.75 96.80

10 2.00 95.6020 0.85 95.1030 0.6 94.2040 0.425 89.0060 0.25 64.70

100 0.15 29.50200 0.075 29.00

HYDROMETER

0.073 27.070.052 26.140.038 25.220.028 23.370.019 18.750.011 15.060.008 13.210.006 9.520.003 8.590.001 4.9

Table 3: Result of Sieve and hydrometer analysis of HB.3

SIEVE

Sievenumber

HB.3Diameter

(mm)Percentage

(%)0 0.00 100.04 4.75 97.80

10 2.00 97.2020 0.85 96.7030 0.6 95.5040 0.425 94.6060 0.25 89.70

100 0.15 65.50200 0.075 28.90

HYDROMETER

0.073 27.020.052 26.090.038 25.170.028 21.480.019 17.800.011 15.030.008 12.260.006 8.580.003 5.810.001 3.96

soil and has a combination of more than 2 fractionswith the same gradation. The type of grain size fromsieve analysis are gravel – fine sand. Whereas, from


223

Figure 6: The grain size curve of HB.2

Figure 7: Type soil in HB.2

hydrometer analysis shows silt – clay grain size. Soiltype determine from the grain class (figure 9).

The uniformity coefficient (Cu) and coefficient ofgradation were calculated with diameter value thatdetermine from the curve are D10 = 0.00698, D30 =0.075892 and D60 = 0.146.

So, the value of Cu and Cc are 20.92 and6. Accordingly, the soil sampleo has very goduniformity of grain and good gradation.

3.2.2 Atterberg Limits

The atterberg limit analysis that performed wereliquid limits, plastic limits and index plastic. The testcarried out using the sample from 3,50 m – 4,00 mdepth in each borehole. The following are the resultsof liquid limit, plastic limit and plasticity index.

Table 4: Atterberg Limit analysis result

Drill no. Depth(m)

Atterberg limitsWl(%) Wp(%) Ip(%)

HB.2 3.50- 4.00 *NP *NP *NPHB.3 3.50- 4.00 *NP *NP *NP

*NP = non-plastic

This sample has non-plastic properties becauseat that depth, the soil layers are clay-silt with sandinsertion (HB.2) and medium sand (HB.3).

3.2.3 Direct Shear Stress

This test was done with three-loads, those are 13.4kg, 28,4 kg and 54.80 kg. After that the value ofnormal stress and shear stress would be plotted intoshear stress graph (figure 10 and figure 11).

The result of direct shear stress from the graphabove could be seen in the table below (Table 5).

Table 5: The direct shear stress’s value

BoreNumber

Cohesion(kg/cm2)

Friction Angle(degree)

(2) 0.06 34.33(3) 0.06 33.78

From the table above, could be determined thematerial that used is stone. Whereas the volumeweight is 22 kN/m3.


224



Figure 10: The shear stress graph of HB.2

3.3 Weir Stability

Weir stability is determined based on the calculationof workforces. The result of forces that worked atDavit Kecil’s Dam during normal water condition and

Figure 11: The shear stress graph of HB.3

flood water condition.Table 6: a. The forces that worked at Davit Kecil’s Weir innormal water condition

No Kind of forces Vertical styles Horizontal stylesV Direction H Direction

1. Own gravity -43.07

2. Earthquakeforce 7.69

3. Hydrostaticpressure 0.26 7.28

4. Mud pressure 0.2 5.71

5. Uplift-pressure 8.00 -10.99

Total -34.6 9.79

The forces that work on normal and a floodcondition could be seen by moment direction. On thetable above could be seen that MT is -180.21 (normal


225

Table 7: b. The forces that worked at Davit Kecil’s Weir innormal water condition

No Kind of forces MomentMT Direction MG Direction



3. Hydrostaticpressure -1.48 24.25

4. Mud pressure -1.15 19.87


Total -171.50 28.72

Table 8: a. The forces that worked at Davit Kecil’s Weir innormal water condition

No Kind of forces Vertical styles Horizontal stylesV Direction H Direction



3. Hydrostaticpressure 3.17 15.28

4. Mud pressure 0.2 5.71

5. Uplift-pressure -11.06 -15.27

Total -34.6 -50.75 13.42

Table 9: b. The forces that worked at Davit Kecil’s Weir inflood water condition

No Kind of forces MomentMT Direction MG Direction



3. Hydrostaticpressure -14.95 57.77

4. Mud pressure -1.15 19.87


Total -180.92 41.67

condition) and -180.208 (flood condition). So, thevertical direction from this force is rotated to the rightor counter-clockwise (Figure 12).

On the earthquake force, the MG value is 17.35 soas to turn the left or clockwise (Figure 13).

These hydrostatic forces have a two-moment,those are MT and MG that have a different direction.On the normal condition, the MT (righting moment)value is -1.481 and on the flood condition, the MT

Figure 12: Own gravity on the weir

Figure 13: Earthquake force on the weir

(righting moment) value is -14.950. The verticaldirection of this force is changed by turn the right orcounter-clockwise (Figure 14).

While MG on the normal condition is 24.25 andon the flood condition is 57.77. So the horizontaldirection from this force is turned the left or clockwise(Figure 15).

From the table above (6b) (7b), noted that MTvalue in both conditions is the same, that is -1.15on the normal and flood condition. So, the verticaldirection of this force is changed by turn the right orcounter-clockwise (Figure 16).

On the MG, the value of mud pressure is 19.87 onboth conditions. So the horizontal direction this forceis to turn the left or clockwise (figure 17).

On the uplift-pressure, the MT’s value is 11.33 innormal condition and flood condition is 15.39. So


226

Figure 14: A hydrostatic force of MT

Figure 15: A hydrostatic force of MG

the horizontal direction of MT is turned the right orcounter-clockwise (figure 18).

On the uplift-pressure, the MG’s value is -32.75in normal condition and flood condition is -53.32. Sothe horizontal direction of MG is turned the left orclockwise (figure 19).

The calculation of weir stability are reviewed fromrolling, sliding, eccentricity and soil bearing capacityfor each water level conditions, there are normal watercondition and flood water condition. The calculationcan be seen in the table below.

Based on the calculation above, the control ofstability weir by rolling in normal and flood waterconditions as strong, that is ≥1,5. Davit Kecil’s weiris strong to against shear because in the normal watercondition the value is ≥1,5 and flood water conditionis ≥1,00. This weir is also safe to eccentricity control

Figure 16: Mud pressure of MT

Figure 17: Mud pressure of MG

Table 10: The calculation of stability at Davit Kecil’s Weirin normal water condition and flood water condition

No. Weir stability Water level conditionsNormal Flood

1. Rolling stability 5.971 -4.3412. Sliding stability -2.676 3.706

3. Eccentricitystability

a 4.127 m -2.744 me -0.127 m 1.256 m

4. Soil bearingcapacity

c0.391

kg/cm31.232

kg/cm3

c 0.474kg/cm3

0.037kg/cm3

with value -0,127≥1,333 in normal water conditionand in flood water condition is 1,256≥1,333. The soilbearing capacity at this weir was done twice in waterlevel conditions with the terms of value≤ σi jin is 3,75


227

Figure 18: Uplift-pressure of MT

Figure 19: Uplift-pressure of MG

kg/cm3. The normal water condition with value σ1 is0,391 kg/cm3 and σ2 is 0.474 kg/cm3, while in floodwater condition with value σ1 is 1.232 kg/cm3 andσ2 is 0,037 kg/cm3. So it is concluded that DavitKecil’s weir in 2 water level conditions has fulfilledthat are strongly resist of rolling, strongly resist ofsliding, safe of eccentricity and strongly resist of soilbearing capacity.

4 CONCLUSION

Based on the result and discussion in the study areaabove, then conclusions could be drawn as follows:

• Safety factor to rolling mode is greater than the

minimum safety factor requirement.

• Safety factor to sliding mode is greater than theminimum safety factor.

• Safety factor to eccentricity mode is safe.

• Safety factor to bearing soil capacity is in therange of requirement value for wire building.

ACKNOWLEDGMENTS

Thanks to the Department of Public Works andHousing (Dinas PUPR) Kepulauan Anambas thatgiving permission and access to the study area.

REFERENCES

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Ali, I. M. (2014). Tinjauan Kestabilan Bendung Alopohu diKabupaten Gorontalo. Universitas Negeri Gorontalo(Thesis).

ASTM (2007). Astm d422-63: Standard test method forparticle-size analysis of soils.

Athani, S. S., Solanki, C., Dodagoudar, G., et al. (2015).Seepage and stability analyses of earth dam usingfinite element method. Aquatic Procedia, 4:876–883.

Erman, M. M. and M. (2010). Desain Bendung Tetap untukIrigasi. Bandung: Alfabeta.

Gunasti, Z. K. N. S. A. (2016). Kajian teknis damsembah patrang kabupaten jember. Jurnal RekayasaInfrastruktur Hexagon, 1(1).

Harseno, E. and Daryanto, E. (2008). Tinjauan tinggitekanan air di bawah bendung dengan turap dan tanpaturap pada tanah berbutir halus. Majalah IlmiahUKRIM Edisi, 2.

Putra, D. B. E., Choanji, T., et al. (2016). Preliminaryanalysis of slope stability in kuok and surroundingareas. Journal of Geoscience, Engineering,Environment, and Technology, 1(1):41–44.

Sadono, K. W., Goji, P., Rachdian, E. S., and Tommy,S. (2017). Analisis geologi teknik pada kegagalanbendung cipamingkis, bogor. Provinsi Jawa Barat.Proceeding Seminar Nasional Kebumian ke, 10.

Samodra, H. (1995). Geological Map of The Tarempa andJemaja Sheet. Riau.

Sompie, O. B. A., S., D., and Ilyas, T. (2015). (2015).Pengaruh Proses Konsolidasi Terhadap Deformasidan Faktor Keamanan Lereng Embankment (StudiKasus Bendungan Kosinggolan),. Prosiding seminarTeknik Sipil, 1.


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Support for Heritage Tourism Development: The Case of Ombilin CoalMining Heritage of Sawahlunto, Indonesia

Jonny Wongso1, Desi Ilona2, Zaitul1, Bahrul Anif1

1Universitas Bung Hatta, Padang, Indonesia2Universitas Putra Indonesia YPTK, Padang, Indonesia

[email protected], [email protected], zaitul, [email protected]

Keywords: Positive Impact, Negative Impact, Support For Heritage Tourism Develpoment

Abstract: This study aims to invetigate the effect of negative economic, social cultural, and environment impact on sup-port for tourism development. Besides, this study also seek whether there is a significant effect of negativeeconomic, social cultural, and environment impact on support for tourism development. Social exchange the-ory is applied to undertand these relationships. Seventy seven residents of Sawahlunto are participated in thisstudy. This study apply SEM-PLS (Smart-PLS) to analys the data. measurement and structural model assess-ment is conducted before concluding whether there is a significant effect of latent independent variables onsupport for tourism development. The result reveals that out of sixt variables being tested, only two latent in-dependent variables have a positive relationship with support for tourism development: positive social culturalimpact and positive environment impact. This study has two implications: theoritical and practical. Theo-ritically, this study contribute to the social exchagne theory in the sense that resident gains positive impact islikely willing to exchange with positive attitude toward suporting the tourism development in the context of In-donesia’s enviroment. Practically, this study can be used by govenement in how to gain the residents’ supportof Sawahlunto by increasing the positive social cultural and environment impact from tourism deevelopment

1 BACKGROUND OF STUDY

One of an effective way to regenerate the commercial-isation of destination is tourism development (Chenand Chen 2010). One of the theme for tourism de-velopment is heritage. Chen and Chen (Chen et al.,2010) add that heritage tourism is usually regards tothe domains of cultural tourism and urban tourism.The word of heritage has been introduced and becomea buzz in 1990 (Palmer, 1999). In the Urban con-text, heritage places are midst the crucial sectors oftourism (Jung and Han 2014). There are several or-ganizations to promote the heritage site (Dieck et al.,2015). Two examples of that organization are the In-ternational Council on Monuments and Sites (ICO-MOS) and UNESCO which conserve monument andsites around the world. Urban heritage sites have beendeveloping in many countries. It is as consequencesof several factor affects on tourism outcome, such asmaterial impact because of reduced season ability, ex-panded stays and expanded customer based (Changet al., 1996; Patuelli et al., 2013). Jung and Han (Junget al., 2014) state that there are several negative im-pacts due to urban heritage tourism development re-

garding to use of space. In fact, Chen and Chen (Chenet al., 2010) documented that several factors affect-ing the attitude toward heritage tourism development:economic, social-cultural, and environments.

Central and local government, in every countryhave been developing the tourism destination, includ-ing heritage tourism. However, they forget about her-itage management and suitability and it is critical con-cerns from both party of practitioners and academics.Chen and Chen (Chen et al., 2010) argue that the res-idents’ support for tourism development is the suc-cess of heritage tourism. Besides, the succes of fac-tors are also attractive heritage resources, uniqueness,successful tourism policy and maintainability. Re-search on residents’ support for tourism developmenthas been done by previous researcher (Perdue et al.,1990; Sirakaya et al., 2002; Stylidis et al., 2014; Lee,2013; Chen et al., 2010).

Perdue et al. (Perdue et al., 1990) investigate thefactors affecting the supporting for additional tourismdevelopment in 16 rural Colorado community andfound that there are several significant factors, suchas positive or negative impact on tourism. In ad-dition, (Sirakaya et al., 2002) assess the determi-

Wongso, J., Ilona, D., Zaitul and Anif, B.Support for Heritage Tourism Development: The Case of Ombilin Coal Mining Heritage of Sawahlunto, Indonesia.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 229-236ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

229

nants of supporting for tourism development in Ghanaand conclude that social-psychological factors influ-ence the supporting for tourism development, suchas tourism’s impact. Chen and Chen (Chen et al.,2010) investigate the interrelationship between eco-nomic dependence on tourism, community attach-ment, perceived negative tourism impact, perceivedpositive tourism impacts and support for tourism de-velopment in Taiwan. Lee (Lee, 2013) study the ef-fect of community attachment, community involve-ment, perceived benefit, and perceived cost on sup-port for sustainable tourism development, in south-west Taiwan and found that community involvementand community attachment have a significant effecton level of support for tourism development. Fi-nally, (Stylidis et al., 2014) investigate the support fortourism development in northern Greece and foundthat the higher the economics, social-culture and en-vironmental tourism impacts, the greater the supportfor tourism development.

Previous studies on support for tourism develop-ment much more focus on general tourism develop-ment. Study on heritage tourism development hasbeen examined, but emphasize on cultural heritagetourism development (Chen et al., 2010). There isa lack of study investigating the urban or historicalvalue heritage tourism development. Besides, studieson effect of tourism impact on support for tourism de-velopment has been seen from economic, social cul-tural and environmental impact (Gursoy et al., 2002;Gursoy et al., 2004; Lindberg et al., 1997; Yoonet al., 2001; Ko et al., 2002; Sharma et al., 2009; Ju-rowski et al., 1997; Chen et al., 2010; Lee, 2013),but the result is inconclusive. Most of support fortourism development studies are underpinned by so-cial exchange theory (Emerson, 1976). In addition,there is an effort of Indonesia’s government to de-velop a world heritage called “ Ombilin Coal MiningHeritage of Sawahlunto” or OCMHS, in west Suma-tra, Indonesia. It is being nominated by UNESCOas one of world heritages which will be conducteda plenary session in June 2019. Ombilin Coal Min-ing Heritage of Sawahlunto is representative and out-standing example of a pioneering technological en-semble planned and built by European engineers intheir colonies designed to extract strategic coal re-sources 1.

Government of Sawahlunto, West SumatraProvince government and central of government ofIndonesia have economic objective to develop this

1Ombilin Coal Mining Heritage of Sawahlunto, a shortguide: nomination for inscription on the world heritage list,available at office of cultural affair, historical remains andmuseum of Sawahlunto municipality.

site to be world heritage: tourism purpose. However,there is no study investigating the residents’ supportfor this historical value and urban heritage tourismdevelopment. Therefore, this kind of study is com-pulsory to be conducted, otherwise the governmentsdoes not have knowledge of resident’s support forthis heritage tourism development. Thus, this studyaims to investigate the effect of the positive and neg-ative of economic, social-cultural, and environmentimpact on residents’ support for heritage tourismdevelopment in Indonesia. The research frameworkis shown in Figure 2 below. This paper is significantfor government of Indonesia, and Sawahlunto mu-nicipality to have a sustainability heritage tourism.This article can contribute to the literature of her-itage tourism management. Due to uniqueness ofIndonesia’s culture, social and law system, this studydiffer compared to previous studies which done indifference environment, such as study done by Chenand Chen (Chen et al., 2010). The remaining of thispaper is organised as follow. Method and material aresecond part of this paper. The third session is aboutresult and discussion. the final session is conclusionand recommendation. Thus, we test six hypotheses inthis study as follow.

H1: there is positive effect of positive economicimpact on support for OCMHS development H2:there is negative effect of negative economic impacton support for OCMHS development H3: there ispositive effect of positive social cultural impact onsupport for OCMHS development H4: there is neg-ative effect of negative social cultural impact on sup-port for OCMHS development H5: there is positiveeffect of positive environment impact on support forOCMHS development H6: there is negative effect ofnegative environment impact on support for OCMHSdevelopment

2 RESEARCH METHOD

There are seventy-seven respondents fromSawahlunto participated in this study. Primarydata is used for this study which collected usingquestioners. The online survey is conducted duringNovember to December 2018. There are two type ofvariables employed (latent dependent variable andlatent independent variables). Support for tourismdevelopment is two items of questioner developed byKo and Stewart (Ko et al., 2002). Tourism impact isdeveloped by Ko and Stewart (Ko et al., 2002) andused by Chen and Chen (2010) which consists ofeconomic impact (8 items), social cultural impact (10items) and environmental items (8 items). Each im-


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Figure 1: Location and area of nominated property.

Figure 2: Research framework.

pact has two sessions: negative and positive impacts.This study applies SEM-PLS (smart-pls) methodto analysis the data. There are two assessment ofsmart-pls: measurement model and structural model(Hair et al., 2017). Measurement model is assessingthe construct validity which consists of convergentvalidity and discriminant validity (Vinzi et al., 2010).

The structural model assesses the predictive relevanceand predictive power. Acceptance or rejection ofhypotheses employ original sample means and tstatistic or p-value (Hair et al., 2013).


This session is discusssed about respondent profile,outer model assessment (MMA), and inner model as-sessment (SMA). Table 1 show the demographic datafrom respondent. Seventy-seven respondents returnedthe questioners. From gender perspective, forty-tworespondents are male or 54.55% and the rests are fe-male (45.45%). In addition, education level of re-spondent is dominated by graduating from senior highschool (38.96%) and followed by bachelor’s degreegraduation (32.47%). Further, respondents workingwith government are 32.47%, followed by 10.39% asentrepreneurs, 33.77% as students and the rest is oth-ers. Finally, the respondents’ income with less thanRp. 3 million is 61.04%. It is followed by 27.00%of respondent with the income of Rp. 3.1 to Rp. 6million. The rest is income above Rp. 6 million.

The convergent validity applies the three property:

Support for Heritage Tourism Development: The Case of Ombilin Coal Mining Heritage of Sawahlunto, Indonesia

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Table 1: Respondent Profile.

Demographic Category Number %Gender Male 42 54.55

Female 35 45.45Education(Graduated)

Senior highschool

30 38.96

Diploma 7 9.09Bachelor 25 32.47Master 10 12.99Others 5 6.49

Occupation Governmentservant

20 25.97

Entrepreneur 8 10.39Students 26 33.77Others 23 29.87

Income < Rp. 3 Mil-lion

47 61.04

Rp 3.1 to Rp.6 M

21 27.00

Rp. 6.1 to Rp.9 M

6 7.79

> Rp. 9 Mil-lion

3 3.39

indicator reliability (outer loading), internal consis-tency reliability and AVE. The result of MMA is seenin Table 2. The construct of negative economic im-pact (NEI) has three items and all items have an outerloading greater than 0.700 (Hulland, 1999). In ad-dition, the internal consistency for NEI also indicatethe reliable due to the value of Cronbach’s alpha (CA)and composite reliability (CR) are greater than 0.800(Bagozzi et al., 1988). Finally, the value of aver-age variance extracted (AVE) is 0.636 and it reachedthe cut-off value (Bagozzi et al., 1988). The secondconstruct is negative environmental impact (NENI).NENI has four items and all items have an outer load-ing above 0.700 (Hulland, 1999). In addition, thevalue of CA and CR for this construct is also greaterthan 0.700 and therefore it can be said that the inter-nal consistency reliability is reached (Bagozzi et al.,1988). Further, NENI also has a higher value of AVE,greater than 0.500 (Bagozzi et al., 1988).

The third construct, negative social culture impact(NSCI) has five items and having calculate the outerloading, only two items has the value of outer loadinggreater than 0.700 (Hulland, 1999), that is nsci2 andnsci5. In addition, this construct has a value of CAand CR greater than 0.700 and it can be concluded theinternal consistency of construct is reliable (Bagozziet al., 1988). Further, this construct also has AVE’svalue greater than 0.500 and it is reached the cut off

value (Bagozzi et al., 1988). The fourth constructis positive economic impact. This construct has fiveitems and all items have outer loading value above0.700 and thus, it can be concluded that the constructhas an higher indicator reliability (Hulland 1999). Inaddition, this construct has satisfied (Bagozzi et al.,1988). Finally, the AVE is also greater 0.500 and it issatisfied (Bagozzi et al., 1988).

The fifth construct is positive environment impact(PEI). This construct has four items and all itemsare reliable due to outer loading above 0.700 (Hul-land, 1999). the internal consistency of construct isalso reliable because of CA and CR’s value above0.700 (Bagozzi et al., 1988). In addition, the value ofAVE also indicate above 0.5 and it satisfy the require-ment of convergent validity (Bagozzi and Yi 1988).The sixth construct is positive social culture impact(PSCI) and has five items. All items have an outerloading more than 0.700 and therefore, it reached thecut off value (Hulland, 1999). In addition, the valueof CA and CR for this construct is 0.803 and 0.902respectively and it can be concluded that the internalconsistency is reliable (Bagozzi et al., 1988). Fur-ther, the AVE’s value indicate above the cut off value(0.500) and it can be concluded that the convergentvalidity is achieved (Bagozzi et al., 1988). Finally,the latent dependent variable has an achieved con-vergent validity with outer loading above 0.700 (twovalid items) (Hulland, 1999), the value of CA and CRis more than 0.700 (Bagozzi et al., 1988), and AVE’svalue is greater than 0.500 (Bagozzi et al., 1988).

The discriminant validity is second construct va-lidity assessment. Hair et al (Hair et al., 2013), statedthat there are two property that can be used to checkthe discriminant validity: Fornel-Lacker criterion andcross-loading. Table 3 indicates the result of Fornel-Lacker criterion and based on this result, it achievethe discriminant validity rule in which the square rootof AVE a construct must be higher than the correla-tion that construct with other construct (Fornell et al.,1981). For example, the value of square root AVEfor NEI (0.797) is higher than correlation of NEI withconstruct of NENI, NSCI and etc.

Discriminant validity also can be assessed fromthe cross loading of construct with its items. Henseler(Henseler, 2010) argue that the loadings of an in-dicator on its assignment latent variable should behigher than its loadings on all other latent variables.From the result (see Table 4), we can conclude that itachieve the rule stated by Henseler (Henseler, 2010).For example, the loading of items nei1, nei2 and nei3have a loading on its NEI construct with value of0.835, 0.755, and 0.800 respectively. The measure-ment model can be seen in Figure 3.


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Figure 3: Measurement model .

The result of assessment of structural model isdemonstrated in Table 5. Vinzi et al (Vinzi et al.,2010), argue that there are two type of structuralmodel assessment, that is predictive relevance andpredictive power. Predictive relevance uses the Qsquare and model has a good predictive relevance ifits Q square above 0 (Hair et al., 2013). From Table5, we can see that the value of Q square is greater than0. In fact, the value is categorised as strong predictiverelevance (Henseler, 2010). In addition, model pre-dictive power is moderate (Hair et al., 2014). R squareis 0.356 and it means that 35.60% variation in latentdependent variable is explained by latent independentvariables. the rest is explained by other variables.

The effect of latent independent variable on la-tent dependent variable is determined by path coeffi-cient and t statistic or p-value. Out of six latent inde-pendent variables, only two latent independent vari-ables have a significant positively effect on supportfor tourism development in Sawahlunto: positive en-vironment impact (PEI) and positive social culturalimpact (PSCI). PEI has path coefficient of 0.290 withp value 0.090 (significant at 10%). In addition, pathcoefficient for PSCI is 0.285 with t statistic 1.871 (sig-nificant at 10%). Negative and positive economic im-

pact do not have a significant effect on support fortourism development due to the p value greater than10%. Negative environment and social cultural im-pact also do not have a significant effect on supportfor tourism development because of its t value is lowerthan 1.69. The structural model is shown by figure 4.

Based on the result above, there are two latent in-dependent variables influencing the support for her-itage tourism development: positive social culturalimpact and positive environment impacts. The rea-son why positive social cultural impact has a positiverelationship with support for tourism development isthat the resident is likely to participate in an exchangewith tourists if they believe that they are likely to gainadvantages (Yoon et al., 2001). Furthermore, if resi-dents perceive that the positive impact of tourism de-velopment will be greater than the negative impacts,they will endorse a tourism development. Thus, thisfinding confirms to the social exchange theory (Emer-son, 1976). The effect of positive social cultural im-pact on support of tourism development is alignedwith (Chen et al., 2010) who conclude that there isa positively significant relationship between positivetourism impact on support for tourism development(t value=5.45). in addition, other scholar who sup-


233

Figure 4: Structural Model .

port this finding is (Gursoy et al., 2002) who alsofound that perceived benefit that had almost equal topositive impact has a positive impact on support fortourism (path coef. = 0.37, t stat.=6.36). Further, thepositive relationship between positive social culturalimpact on support for tourism development is alsosupported by Gursoy and Rutherford (Gursoy et al.,2004), Jurowski et al (Jurowski et al., 1997), Ko andStewart (Ko et al., 2002), and Yoon et al (Yoon et al.,2001). Other four latent independent variables whichdo not have a significant relationship with support fortourism development are not consistent with previousstudies, such as Chen and Chen (Chen et al., 2010),Jurowski et al (Jurowski et al., 1997), Ko and Stewart(Ko et al., 2002), and Yoon et al (Yoon et al., 2001).

4 CONCLUSION ANDRECOMMENDATION

Tourism development is an effort made by govern-ment to promote the culture or historic value of cer-tain location. thus, it becomes an attraction that caninvite tourism coming to the tourism sites. One oftourism development in Indonesia is OCMHS. In fact,this site is being nominated by UNESCO to be one

of world heritages. Thus, it will be decided in June2019. However, there is no studies investigating theresidents’ supporting of this heritage tourism devel-opment. Therefore, this objective study of this studyis to investigate the effect of economic, social cul-tural and environment impact on supporting for thistourism development. These impacts are divided intopositive and negative. By surveying the Sawahluntoresidents, we reveal that only two latent independentvariables have a significant effect on supporting forheritage tourism development: positive social culturalimpact and positive environment impact. This studycontributes to the social exchange theory.


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Table 2: Convergent Validity.

Construct Item OuterLoad-ing

CA CR AVE

Negativeeco-nomicimpact

nei1 0.84 0.75 0.84 0.64

nei2 0.76nei3 0.80

negativeenviron-mentalimpact

neni1 0.70 0.91 0.90 0.69

neni2 0.99neni3 0.82neni4 0.80

negativesocialcultureimpact

nsci2 0.79 0.74 0.87 0.77

nsci5 0.96positiveeco-nomicimpact

pei1 0.91 0.94 0.95 0.77

pei2 0.80pei3 0.81pei4 0.88pei5 0.92pei6 0.94

positiveenvi-ronmentimpact

peni1 0.75 0.90 0.93 0.78

peni2 0.93peni3 0.91peni4 0.93

positivesocialculturalimpact

psci1 0.90 0.86 0.90 0.65

psci2 0.70psci3 0.87psci4 0.83psci5 0.75

supportfortourismdevelop-ment

std1 0.95 0.88 0.94 0.89

std2 0.94

Table 3: Discriminant validity-Fornel-Lacker Criterion.Construct NEI NENI NSCI PEI PENI PSCI STDNEI 0.80NENI 0.24 0.83NSCI 0.35 0.28 0.88PEI 0.61 -0.09 0.17 0.88PENI 0.52 -0.02 0.16 0.76 0.88PSCI 0.61 -0.03 0.20 0.77 0.78 0.85STD 0.39 -0.06 0.16 0.48 0.55 0.56 0.95

Table 4: Discriminant Validity-Cross Loading.

Items NEI NENI NSCI PEI PENI PSCI STDnei1 0.84 0.05 0.14 0.75 0.63 0.68 0.42nei2 0.76 0.38 0.41 0.19 0.21 0.29 0.20nei3 0.80 0.30 0.42 0.29 0.22 0.32 0.22neni1 0.45 0.67 0.38 0.02 0.08 0.04 0.00neni2 0.23 0.99 0.24 -0.10 -0.03 -

0.04-0.07

neni3 0.32 0.82 0.47 -0.01 0.04 0.02 -0.01neni4 0.34 0.80 0.48 0.02 0.03 0.05 0.00nsci2 0.49 0.41 0.79 0.11 0.09 0.08 0.08nsci5 0.24 0.19 0.96 0.17 0.17 0.22 0.17pei1 0.55 -0.06 0.17 0.91 0.66 0.67 0.37pei2 0.47 -0.08 0.17 0.79 0.69 0.65 0.40pei3 0.50 0.02 0.13 0.81 0.68 0.60 0.44pei4 0.55 -0.15 0.13 0.88 0.59 0.69 0.46pei5 0.54 -0.12 0.12 0.92 0.69 0.73 0.42pei6 0.59 -0.11 0.17 0.94 0.68 0.72 0.40peni1 0.41 0.09 0.15 0.63 0.75 0.65 0.47peni2 0.46 -0.05 0.06 0.70 0.93 0.70 0.54peni3 0.48 -0.06 0.20 0.67 0.91 0.73 0.48peni4 0.49 -0.05 0.17 0.68 0.93 0.74 0.45psci1 0.59 -0.05 0.20 0.71 0.76 0.90 0.60psci2 0.48 -0.01 0.13 0.46 0.47 0.66 0.38psci3 0.49 -0.01 0.22 0.74 0.66 0.87 0.43psci4 0.40 0.01 0.11 0.59 0.67 0.83 0.45psci5 0.47 -0.07 0.11 0.61 0.62 0.75 0.36std1 0.377 -0.07 0.15 0.52 0.54 0.59 0.95std2 0.360 -0.05 0.14 0.37 0.50 0.47 0.94

Table 5: Structural Model Assessment.

EndogenousCon-struct

Q2 Decision R2 Decision

STD 0.26 strong 0.36 moderaterelationship path

coeft statis-tic

pvalue

Decision

NEI ->STD

0.10 0.78 0.43 not-accepted

NENI ->STD

-0.09 0.78 0.44 not-accepted

NSCI ->STD

0.05 0.51 0.61 not-accepted

PEI ->STD

-0.03 0.26 0.79 not-accepted

PEI ->STD

0.29 1.70 0.09* accepted

PSCI->STD

0.29 1.87 0.06* accepted


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Aerial Photogrammetry and Object-based Image Analysis for BridgeMapping: A Case Study on Bintan Bridge, Riau Islands, Indonesia

Husnul Kausarian1, Muhammad Zainuddin Lubis2, Primawati3, Dewandra Bagus Eka Putra1, AdiSuryadi1 and Batara1

1Department of Geological Engineering , Universitas Islam Riau, Pekanbaru, Indonesia2Department of Informatics Engineering, Politeknik Negeri Batam, Batam-Kepulauan Riau, Indonesia

3Mechanical Engineering, Engineering Faculty, Universitas Negeri Padang, Padang-West Sumatra, [email protected], [email protected], [email protected], dewandra.bagus,


Keywords: Photogrammetry, Unmanned Aerial Vehicle (UAV), Bintan Bridge, Structure, Specify Second Distance.

Abstract: Photogrammetry is a good method for determining the geometric properties of an object from the images. Thegeometry of the object obtained from two or more drawings that are overlaid. It is completely autonomous,ultra-lightweight so-called Unmanned Aerial Vehicle (UAV) which has been commercially available at veryeconomical prices in the community or researchers, and photogrammetric applications. The study area waslocated at Bintan Island, Riau Islands Province, Indonesia, collecting data on 8th may, 2017 (1 3’45.98”N- 10427’49.22”E), with DJI phantom 4 including control range small format air photography (SFAP) whichis a low-cost, cost-effective solution for obtaining bridge surface imagery and can also be proposed as along-distance bridge inspection technique to complement the current bridge visual inspection in Indonesia.Some examples of evaluations on bridges using SFAP are presented to provide remote sensing informationand capabilities that serve as an essential tool for monitoring and assessing the construction of the bridge.The measurement of Bintan Bridge is 193 m, the photos were taken from the airplanes around 70 meters andproviding top-down views. Bintan Bridge’s structure have specify second distance in left wide is 1.057 <1560, and specify second distance in right wide is 0.9981 < 1570.

1 INTRODUCTION

Modelling on object information with building in-stances becomes a famous technology for some in-frastructure such as bridges, road systems, tunnels,dams, water, and sewage networks. In the Riau Is-lands, Bintan Island does not have much informa-tion on mapping air information using remote sensingtechniques on building any object, and buildings mod-elling information is very limited. The latest map-ping information on the Riau islands is still domi-nantly small, and still in the general mapping of ob-jects such as sea grass beds, settlements, seafloor (Lu-bis and Daya, 2017; Lubis et al., 2017; Farizki andAnurogo, 2017; Kausarian et al., 2016b; Kausarianet al., 2016a; Kausarian et al., 2017; Kausarian et al.,2018; Kausarian et al., 2019).

In terms of the image analysis, the contempo-rary and existing construction is one of the signifi-cant problem (Agapiou et al., 2015; Patraucean et al.,2015; Tang et al., 2010; Volk et al., 2014; Cuca

et al., 2014; Kausarian et al., 2017). The mappingon the current geomorphology field relies more andmore on automatic techniques that serve to classify animage from the results of remote sensing techniquesand a digital elevation model (DEMs) (Lardeux et al.,2016). Parameters are seen in the morphometric sec-tion, such as the slope or curvature of the region orthe inherited object for the result of characterizationof the shape and result of the geomorphological pro-cess. Arithmetic in the process of operation with thedrawing band can clarify the class on a particular ob-ject. The vegetation index is often also used to clas-sify vegetation and separate objects from other classesin a remote sensing data. In the object image of theentity on the basic technique in the drawing (in ourcase is the bridge), in each group of objects in the im-age, the pixel results consist of the same digital value,and has a relationship to the intrinsic size and shape,and the intrinsic ecology real-world scene componentis a model (Hay et al., 2001). In the results of a re-cent study informed by the American Civil of Society

Kausarian, H., Lubis, M., Primawati, Putra, D., Suryadi, A. and BataraAerial Photogrammetry and Object-based Image Analysis for Bridge Mapping: A Case Study on Bintan Bridge, Riau Islands, Indonesia.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 237-242ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

237

(Chen et al., 2009) indicate that conditions improveon all systems in the current infrastructure, with ob-jects such as roads and bridges.

UAVs have been used successfully in a research,for mapping (Hardin and Jackson, 2005; Kausarianet al., 2018), for the nitrogen and biomass measure-ment in a plant object (Izumi et al., 2018; Izumi et al.,2019; Widodo et al., 2018; Widodo et al., 2019),for document the crop at the value of water pressure(Berni et al., 2009), and for results on rangeland veg-etation mapping. In this study, we were interested inthe utilization of aerial mapping object-based image(Bintan Bridge) for structure and position analyst inKepri islands, Indonesia

2 DATA AND METHODS

2.1 Study Location

Our study site was located on Bintan Island, Riau Is-lands, Indonesia, collecting data on 8th May 2017 (13’45.98”N - 10427’49.22”E) (Figure 1). The areaover which imagery was acquired was located within1.5 km of is Bintan Bridge.

2.2 Study Location

Agisoft Photoscan Professional version 1.2.7 build3100 64 bit was used to extract all mosaic from quad-copter DJI phantom 4 (Figure 2) and the tiles ofpoint cloud data converted into photogrammetry im-ages. The 1-m resolution DTM used for normalizingthe terrain model on the object based images (BintanBridge) height, and photo captured of Bintan Bridgewith altitude 70 meters can be seen in Figure 2.

2.3 Flight Planning

The take-off and landing operations are stronglylinked to the vehicle and the level of characteristicsemployed, but can usually be controlled from theground by the pilot (e.g. with a remote controller).Research mission (aviation and data acquisition) isplanned in laboratory with special software, startingfrom the area of interest (AOI), the distance of re-quired soil sample (GSD) or path, and knowing whatis the intrinsic parameter of camera digital installedfrom DJI Phantom 4. During the flight process, theplatform is usually observed with a control stationshowing real-time flight data such as position, speed,stance and distance, GNSS observations, battery orfuel status, rotor speed, altitude, etc.


Nearly 325 images (Figure 4) obtained through pho-togrammetry and object-based image analysis (BintanBridge) in Figure 3. 4-rotor quadcopter DJI phantom4 with GNSS addition system equipped with 12 MPpixel camera, GPS & GLONASS satellite system, -90 to + 30 Pitch Gimbal Control Range. The mea-surement of the Bintan Bridge is 193 m, measured byAgisoft software, in solid mode and in shaded modeas shown in Figure 4.

Image objects for each individual on the bridgeare simultaneously archived for viewing in a geo-graphic information system (GIS) (Ellenberg et al.,2016; Yeum and Dyke, 2015; Reagan et al., 2018).The technique used in the results is ”manually match-ing features” with mosaic images already availablefrom ArcMap 10.2 and Agisoft Photoscan Profes-sional. The classification process is used to extract theinformation performed by clarifying different coloursto each object class to distinguish them by rapid iden-tification. Figure 4 shows the results of the objectdetection of the bridge structure shown as a featurewith darker pixels than surrounding adjacent imagesand may be marked as possible identification objects.By viewing the surface with visuals and other surfaceconditions may also appear like cracks seen in bridgestructures and figures. The same problem will ariseif the colour identification technique used on the sur-face of the concrete. The flight crew must functionafter the process of airing and flying near the point ofthe camera direction that has been set for each bridge.Accurate communication of the cockpit and air trafficcontrol officer is essential in completing the researchsafely. Identifying the large and wide bridge objectson the surface is relatively easy to observe. Analy-sis of the bridge object and counting the width usingthe method of air photography effectively identifiesthe width which is 6 m and signed as a yellow colourin Figure 5 which is also shows the condition of thebridge connection and expansion.

The length of Bintan Bridge is 193 m from imageprocessing using Agisoft Software (Figure 4). Exten-sive recapitulation of the entire procedure for generat-ing the same 3D cloud point as the results of this studycan be found on applying the Scale Invariant FeatureTransform (SIFT) to perform button detection as in-troduced (Lowe, 2004). The existence of field processthat occurs in traffic on the highway is always outsidethe control of the flight pilot to take the photos. Thearea of the sweep by the pilot in the process of trafficcan be such that large areas on the road surface arenot blocked by car objects. When performing aerialphotography analysis for this study, 2 (two) cars were


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Figure 1: The Map of Research location and Object Based (Modified from Google Earth).

Figure 2: The image of Bintan Bridge, captured by Quadcopter DJI Phantom 4.

Figure 3: The point cloud computed with PhotoScan.

Figure 4: Automated image perspective 30 0 results for the UAV, left: with solid mode, right: with shaded mode.

present at the bridge statically. Taking vehicles from aerial photography is required (Figure 6). Structure

Aerial Photogrammetry and Object-based Image Analysis for Bridge Mapping: A Case Study on Bintan Bridge, Riau Islands, Indonesia

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Figure 5: Aerial track object identification, left: original image, right: zoomed image.

Figure 6: Detection of two vehicles, left: original image, right: zoomed image.

Figure 7: Above: Structure of Bintan Bridge, left below: Specify Second Distance in Left Wide (1.057 < 1560), right below:Specify Second Distance in Right Wide (0.9981 < 1570).

of Bintan Bridge can be seen in Figure 7 that havespecify second distance in left wide in range 1.057< 1560, and specify second distance in right wide is0.9981 < 1570.

4 CONCLUSIONS

In this study, remote sensing is used as a tool in or-der to see the structure of Bintan Bridge with high-resolution air photography. The procedures of imageprocessing and data collection as a detailed processare described. The results of this study indicate that


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the technology of remote sensing is able to detect veryclear objects and bridge structures. Accurate posi-tioning and tracking results through bridges are donewithout a robust test and the use of GPS units includedin the Instruments used on the correct scale to suit theneeds. It is necessary for pilots to remember that thewide area augmented system (WAAS) enables GPSaccuracy of up to 6-8 inches/pixels. In this paper, wediscuss the process of making the whole drawing onthe object of the bridge by separating other objects,including plants, etc. to keep in view the focus of theBintan bridge structure results, and the vehicles of theaerial photogrammetr.

ACKNOWLEDGEMENTS

This study is supported by P2M, Geomatics Engi-neering Program, Batam State Polytechnic, Kepu-lauan Riau, Indonesia, and Engineering GeologicalProgram, Universitas Islam Riau.

REFERENCES

Agapiou, A., Lysandrou, V., Alexakis, D. D., Themisto-cleous, K., Cuca, B., Argyriou, A., Sarris, A., andHadjimitsis, D. G. (2015). Cultural heritage manage-ment and monitoring using remote sensing data andGIS: The case study of Paphos area. Cyprus.

Berni, J. A., Zarco-Tejada, P. J., Surez, L., and Fereres, E.(2009). Thermal and narrowband multispectral re-mote sensing for vegetation monitoring from an un-manned aerial vehicle. IEEE Transactions on Geo-science and Remote Sensing.

Chen, S. E., Hauser, E., Eguchi, R., Liu, W. Q., Rice, C.,Hu, Z., Boyle, C., and Chung, H. (2009). Bridgehealth monitoring using commercial remote sensing.In Proceedings, 7th International Workshop on Struc-tural Health Monitoring, Stanford, CA.

Cuca, B., Agapiou, A., Kkolos, A., and Hadjimitsis, D.(2014). Integration of innovative surveying technolo-gies for purposes of 3D documentation and valorisa-tion of St. Herakleidios Monastery in Cyprus.

Ellenberg, A., Kontsos, A., Moon, F., and Bartoli, I.(2016). Bridge related damage quantification usingunmanned aerial vehicle imagery. Structural Controland Health Monitoring.

Farizki, M. and Anurogo, W. (2017). Pemetaan kuali-tas permukiman dengan menggunakan penginderaanjauh dan SIG di kecamatan Batam kota. Batam.

Hardin, P. J. and Jackson, M. W. (2005). An unmannedaerial vehicle for rangeland photography. RangelandEcology & Management.

Hay, G. J., Marceau, D. J., Dube, P., and Bouchard, A.(2001). A multiscale framework for landscape analy-

sis: object-specific analysis and upscaling. LandscapeEcology.

Izumi, Y., Widodo, J., Kausarian, H., Demirci, S., Taka-hashi, A., Razi, P., Nasucha, M., Yang, H., and J., T.S. S. (2019). Potential of soil moisture retrieval fortropical peatlands in Indonesia using ALOS-2 L-bandfull-polarimetric SAR data. International Journal ofRemote Sensing.

Izumi, Y., Widodo, J., Kausarian, H., Demirci, S., Taka-hashi, A., Sumantyo, J. T. S., and Sato, M. (2018).Soil moisture retrieval by means of adaptive polari-metric two-scale two-component model with fully po-larimetric ALOS-2 data. In IGARSS 2018-2018 IEEEInternational Geoscience and Remote Sensing Sympo-sium. IEEE.

Kausarian, H., Lei, S., Lai, G. T., Cui, Y., and Suryadi, A.(2019). A New Geological Map of Formation Distri-bution on Southern Part of South China Sea:; NatunaIsland. Indonesia, In IOP Conference Series.

Kausarian, H., Sumantyo, J. T. S., Kuze, H., Karya, D., andPanggabean, G. F. (2016a). Silica Sand Identificationusing ALOS PALSAR Full Polarimetry on The North-ern Coastline of Rupat Island. Indonesia.

Kausarian, H., Sumantyo, J. T. S., Kuze, H., Karya, D.,and Wiyono, S. (2016b). The origin and distributionof silica mineral on the recent surface sediment area.Northern Coastline of Rupat Island, Indonesia.

Kausarian, H., Sumantyo, J. T. S., Putra, D. B. E., Suryadi,A., and Gevisioner (2018). Image processing of alospalsar satellite data. small unmanned aerial vehicle(UAV), and field measurement of land deformation.

Kausarian, H., Sumantyo, S., T., J., Kuze, H., Aminuddin,J., and Waqar, M. M. (2017). Analysis of polarimetricdecomposition. backscattering coefficient, and sampleproperties for identification and layer thickness esti-mation of silica sand distribution using L-band syn-thetic aperture radar.

Lardeux, P., Glasser, N., Holt, T., and Hubbard, B. (2016).Glaciological and geomorphological map of GlacierNoir and Glacier Blanc. French Alps.

Lowe, D. (2004). Distinctive image features from scalein-variant keypoints. International Journal of ComputerVision.

Lubis, M. Z., Anurogo, W., Khoirunnisa, H., Irawan, S.,Gustin, O., and Roziqin, A. (2017). Using Side-ScanSonar instrument to Characterize and map of seabedidentification target in punggur sea of the Riau Is-lands. Indonesia.

Lubis, M. Z. Z. and Daya, A. P. (2017). Pemetaan Param-eter Oseanografi Fisik Menggunakan Citra Landsat 8di Wilayah Perairan Nongsa Pulau Batam. Jurnal In-tegrasi.

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Widodo, J., Izumi, Y., Takahashi, A., Kausarian, H., Kuze,H., and Sumantyo, J. T. S. (2018). Detection of dry-flammable peatland area by using backscattering coef-ficient information of ALOS-2 data L-band frequency.In 2018 Progress in Electromagnetics Research Sym-posium (PIERS-Toyama), IEEE.

Widodo, J., Izumi, Y., Takahashi, A., Kausarian, H.,Perissin, D., and Sumantyo, J. T. S. (2019). Detectionof Peat Fire Risk Area Based on Impedance Model andDInSAR Approaches Using ALOS-2 PALSAR-2 Data.IEEE Access.

Yeum, C. M. and Dyke, S. J. (2015). Vision-basedautomated crack detection for bridge inspection.Computer-Aided Civil and Infrastructure Engineer-ing.


242

Monitoring Single Site Verification (SSV) System and Optimization BTSNetwork based on Android

Abdul Syukur, Siti Rahmadhani Sabri and Yudhi ArtaDepartment of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia


Keywords: PT. GCI Indonesia, BTS, Maintenance, Android.

Abstract: Information technology is characterized by the birth of a computer and its rapid development. It started withthe creation of the first generation computers to the fifth generation computers today. PT. GCI Indonesia is acompany engaged in telecommunications. This company provides professional consulting and technical ser-vices to work on wireless networks, transmission networks, data communication, and several other services.Of course, going to BTS requires a variety of preparations, starting from the BTS data, the types of mainte-nance performed, the development of maintenance, the costs needed and so forth. For now, PT. GCI Indonesiaitself still uses preparation and reporting by recording on sheets of paper which will later be reported. So fromthat, the purpose of this research is to produce a monitoring system with Android and able to archive a lot ofdata into the database as the report that will be used for the report.

1 INTRODUCTION

PT. GCI Indonesia is a company engaged in telecom-munications. This company provides professionalconsulting and technical services to work on wire-less networks, transmission networks, data communi-cation, and several other services. PT. GCI Indonesiasends professional technicians to check, repair or re-new the system at the Base Transceiver Station (BTS).Of course, going to BTS requires a variety of prepara-tions, starting from the BTS data, the types of main-tenance carried out, the development of maintenance,the costs needed and so on.

To overcome this, currently PT. GCI Indonesia isstill preparing and reporting on performance in BTSby recording on sheets of paper to be reported to rel-evant parties. This method is fairly ineffective, con-sidering the time, effort and efficiency of reporting bytechnical and the receipt of reports by related parties.To improve performance, monitoring should be donemore quickly and effectively. In this study, the authortries to find a solution to these problems.

2 LITERATURE REVIEW

According to Nabil Bawafie in the e-ISSN journal:2338-5197 discusses the Design of SMS-Based In-ternet Bandwidth Monitoring System. In this study,

an automated system was developed that can pro-vide information to engineers when there is troubleon a network. A server is a computer system thatprovides certain types of services in a computer net-work. Servers are supported by scalable processorsand large RAM, also equipped with special operat-ing systems, which are referred to as network op-erating systems or network operating systems. Theserver also runs administrative software that controlsaccess to the network and the resources contained init, such as files or printers, and provides access to net-work member workstations (Bawafie and Muslihudin,2013).

According to Nelly Indriani Widiastuti conductedresearch on monitoring System Study of UNIKOM’sInformatics Engineering Accreditation Document.The system developed monitors activities accordingto planning, identifies problems that arise so thatthey can be addressed immediately, evaluates workpatterns and management used, knows the bond be-tween activities and objectives and adjusts activitiesto changing environments. This system was devel-oped based on the web as a user interface (Widiastutiand Susanto, 2014).

According to Asti Herliana in the journal ISSN:2355-6579 researched Information Systems Monitor-ing of Software Development in the DevelopmentPhase of Web Development. This system was de-veloped to help the projects carried out by Devel-

Syukur, A., Sabri, S. and Arta, Y.Monitoring Single Site Verification (SSV) System and Optimization BTS Network based on Android.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 243-249ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

243

opment completed on time. In essence, this sys-tem monitors the execution of the software and thetime tested according to the agreement (Herliana andRasyid, 2016).


3.1 Data Collection Technique

The research methodology is the stages that arepassed by the researcher to obtain a clear pictureof the research so the preparation of the researchmethodology is as follows (Sulihati, 2016; Jumri,2013; Risnandar et al., 2015):

1. Data Collecting is data collected, namely symp-tom data, disease data, case data, the data is ob-tained by conducting a search or research

2. Literature Studies conducted by collecting andstudying all kinds of information relating to themonitoring system and everything related to theprogramming model

3. System Design that is at this stage carried outsoftware system design that will be made basedon the results of existing literature studies. Thissoftware design includes data structure design, in-formation flow design, interface design, algorithmdesign and programming

4. System Implementation, namely the system im-plementation phase is carried out in stages withreference to literature studies and system designthat has been made

5. Testing and Evaluation At this stage a programtrial is carried out to look for possible problems,evaluate the course of the program, and make im-provements if there are shortcomings

6. Preparation of Research Reports is carried out atthe final stage as documentation. This documen-tation is made to explain the application to makeit easier for others who want to develop the appli-cation further

3.2 System Planning

The description of the ssv monitoring and opti-mization system process that is currently runningat PT. GCI Indonesia is as follows (Hutasoit andMubarakah, ; Auliq and Prasojo, 2018; Cahyadi et al.,2016):

Figure 1 the manual process that occurs at thistime starts from the management of project data by

Figure 1: The Process System Manual

the Project manager, after that the BTS data accordingto the agreed project will be managed by the projectcoordinator and admin. The RF engineer will sched-ule BTS that has been managed by the Project Coor-dinator and admin. Before leaving the field, DT Engi-neer will request operational funds to the admin withpermission from the project manager. DT Engineerwill input data services and Project Manager can seethe report on the system that is running.

3.3 Flowchart of Program

The program logic flow is illustrated through the fol-lowing flowchart:

Figure 2 from the program flowchart it can be seenthat there is a login form display, then the user canenter the username and password. There are 4 userson this system, namely, Project Manager, Admin andProject Coordinator, Drive Test Engineer and RadioFrequency Engineer.

The program logic project manager flow is illus-trated through the following flowchart:

Figure 3 is the access menu used by the projectmanager. The menu provided for access has been ad-justed to the conditions in the field and the rules thatapply at PT. GCI Indonesia

The program logic coordinator admin project flowis illustrated through the following flowchart:

Figure 4 is the access menu used by the ProjectCoordinator and Admin. The menu provided for ac-cess has been adjusted to the conditions in the field


244

Figure 2: Flowchart of Program

Figure 3: Flowchart of Project Manager

and the rules that apply at PT. GCI IndonesiaThe program logic RF engineer flow is illustrated

through the following flowchart:Figure 5 is the access menu used by RF Engineer.

The menu provided for access has been adjusted to

Figure 4: Flowchart of Koordinator Admin Project

Figure 5: Flowchart of RF Engineer

the conditions in the field and the rules that apply at

Monitoring Single Site Verification (SSV) System and Optimization BTS Network based on Android

245

PT. GCI IndonesiaThe program logic DT engineer flow is illustrated

through the following flowchart:

Figure 6: Flowchart of DT Engineer

Figure 6 is the access menu used by DT Engineer.The menu provided for access has been adjusted tothe conditions in the field and the rules that apply atPT. GCI Indonesia

4 RESULT

4.1 Testing Login Access Rights Admin,Radio Frequency Engineer, DriveTest Engineer, Project Manager

The testing login admin access rights, radio frequencyengineer, drive test engineer, and project manager fol-lowing:

Figure 7 To be able to process data on the system,Admin PT.GCI Indonesia must log into the system.Admin must enter the username and password that hasbeen registered to the system. The following is thepicture of the PT.GCI Indonesia Admin committee’slogin page in figure 6. The following is the display ofPT. GCI Indonesia Admin login form

Figure 7: Testing Form Login Admin and Main Menu Ad-min

4.2 Testing Form Login RadioFrequency Engineer (RF)

The testing form login radio frequency engineer fol-lowing:

Figure 8: Testing Form Login Radio Frequency Engineer(RF) and Main Menu RF

Figure 8 when going to do data processing on thesystem, the Radio Frequency Engineer (RF) first loginto enter the system by entering a username and pass-word that has been registered in the system database.The following is a test image of the login form of Ra-dio Frequency Engineer (RF) PT. GCI Indonesia

4.3 Testing Form Login Drive TestEngineer (DT)

The testing form login drive test engineer following:Figure 9 when going to do data processing on the

system, the Test Drive Engineer (DT) first login to


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Figure 9: Form Login Drive Test Engineer (DT) and MenuDT

enter the system by entering the username and pass-word that has been registered in the system database.The following is a picture of testing the login form ofDrive Test Engineer (DT) PT. GCI Indonesia

4.4 Testing Form Login ProjectManager

The testing form login project manager following:

Figure 10: Testing Form Login and Main Menu ProjectManager

Figure 10 when going to do data processing on thesystem, the Project Manager first login to enter thesystem by entering a username and password that hasbeen registered in the system database. The followingis a test picture of the Project Manager (DT) PT. GCIIndonesia login form

4.5 Form Data Service

The form data service following:

Figure 11: Form Data Service

In Figure 11 above explains that the data servicethat has been inputted by the Drive Test Engineer(DT) will be displayed in the table above where thedata is stored in the database and can use ascendingor descending shorting according to column selection

4.6 Form Graph Project per Week

The form graph project following:

Figure 12: Form Graph Project

4.7 Form Graph Project per Month

The form graph project per month following:


247

Figure 13: Form Graph Project Per Month

4.8 Form Graph Project per Year

The form graph project per year following:In pictures 12, 13, and 14 display graph reports

weekly, monthly and annually that can be seen by theproject manager.

5 CONCLUSIONS

After conducting research, designing and testingthe SSV Monitoring System and BTS network Op-timization using the Android case study of PT. GCIIndonesia, conclusions can be taken as follows:

Has successfully made the SSV Monitoring Sys-tem and BTS network Optimization using the An-droid case study of PT. GCI Indonesia, and based onthe results of testing that has been done using Blackbox, SSV Monitoring System and BTS network Opti-

Figure 14: Form Graph Project Per Year

mization using the Android case study of PT. GCI In-donesia has achieved efficiency as a monitoring sys-tem, and the last based on the results of testing thathas been done using the White box, SSV MonitoringSystem and BTS network Optimization using the An-droid case study of PT. GCI Indonesia facilitates thedata storage process in accordance with field condi-tions.

REFERENCES

Auliq, M. A. and Prasojo, K. S. (2018). Perancangan sistemmonitoring power bts (base transceiver station) meng-gunakan sms gateway berbasis mikrokontroler atmega8535. PROSIDING SENSEI 2017, 1(1).

Bawafie, N. and Muslihudin, M. (2013). Perancangan sis-tem monitoring bandwidth internet berbasis sms. Jur-nal Sarjana Teknik Informatika, 1(1):241–247.

Cahyadi, D., Agus, F., and Iman, M. (2016). Studi peman-faatan network monitoring system pada intra/inter-netpemerintah provinsi kalimantan timur sebagai bahanrekomendasi untuk memaksimalkan utilisasi jaringanintra/inter-net. Informatika Mulawarman: JurnalIlmiah Ilmu Komputer, 5(2):38–49.

Herliana, A. and Rasyid, P. M. (2016). Sistem informasimonitoring pengembangan software pada tahap devel-opment berbasis web. Jurnal Informatika, 3(1).

Hutasoit, E. F. and Mubarakah, N. Analisis unjuk kerja


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jaringan pada sistem cdma (studi kasus telkom fleximedan). Singuda ENSIKOM, 7(1):23–29.

Jumri, J. P. (2013). Perancangan sistem monitoring kon-sultasi bimbingan akademik mahasiswa dengan noti-fikasi realtime berbasis sms gateway. Jurnal Sistemdan Teknologi Informasi (JustIN), 1(1):21–25.

Putro, M. R. D., Susanto, T., and Sutomo, E. (2014). Ran-cang bangun sistem informasi monitoring antrian padakoperasi setia bhakti wanita berbasis web. JurnalJSIKA, 3(1):204–211.

Risnandar, E. et al. (2015). Pembuatan Aplikasi SistemInformasi Monitoring Kegiatan Mahasiswa BerbasisWeb dan Android Client. PhD thesis, UNIVERSITASNEGERI SEMARANG.

Sulihati, A. (2016). Aplikasi akademik online berbasis mo-bile android pada universitas tama jagakarsa, volumexi, nomor 1, hal 18-19. Universitas Tama. Jagakarsa.

Widiastuti, N. I. and Susanto, R. (2014). Kajian sistemmonitoring dokumen akreditasi teknik informatikaunikom. majalah ilmiah UNIKOM, 12(2).


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Characterization of the Ethnobotany of Riau Province Mascot Flora(Oncosperma tigillarium (Jack) Ridl.)

Desti1, Fitmawati2, Putri Ade Rahma Yulis1 and Mayta Novaliza Isda2

1Biology Education Program, Universitas Islam Riau, Pekanbaru, Indonesia2Biology Department, Universitas Riau, Pekanbaru, Indonesia

[email protected], [email protected], [email protected], [email protected]

Keywords: Ethnobotany, Oncosperma Tigillarium, Plant Use, Riau’s Mascot Flora.

Abstract: Nibung (Oncosperma tigillarium) is the identity of Riau flora’s mascot. This research aims to characterize theethnobotany of that flora. The survey method used in this research. The research method used included fieldobservations, discussions and deeply personal interview with local community. Data collection techniqueswere carried out directly with questionnaire assisted communication. Ethnobotanical information was gatheredfrom the local community through interviews of the respondents. Data collection were conducted at Bukitbatu,Bengkalis District, Riau Province, Indonesia. Data collected from the informants were selected randomly. Wefound that all of the parts of nibung plant have high economic value that support the local community lives,hence used much as construction materials, for example: buildings, furniture, and shipyards. Therefore,nibung has an ideal plant to support its wide use in the community.

1 INTRODUCTION

Nibung is a member of Arecaceae. The members ofthis family of plants are the oldest species that havebeen found since the time of Cretaceous period, ap-proximately 120 million years ago. The Aracaceae inthe world is estimated to have 200 - 300 genus evenmore and about 2000 - 3000 species spread in trop-ical and sub-tropical regions (A., 2000). Aracaceae,which is a group of monocot plants, is the only familyin the Aracales order that is very interesting in termsof botany, its beauty shape, diversity of species and itsusefulness (Anderson, ).

Nibung tree is one of the important germplasmsin Riau Province. In addition, yet the abundance ofinformation on characters of nibung in Riau Provincecausing the plant not known by people. Therefore, itis expected that with the characterization of the eth-nobotanical study can be a reference in the socializa-tion and exploration efforts nibung plants as the Riaumascot flora.

Our previous research showed the characterizationof morphological of nibung plant was observed by us-ing of the instrument to observe of sample of nibungplants in the Bengkalis District, Riau Province. It isaccordance with Dransfield, et al. (2008), Shengji,et al. (2009), and Baba, et al. (2013) that nibung asone of the Plamae family has those characteristic as a

coastal plants (P et al., 2009; J et al., ; S et al., 2013).More than 25 characters are used to describe the

characteristic of morphological nibung plants. The re-sult shows that nibung in Riau have a compound lifehabit. Vegetative organ that has been observed is com-posed of parts of the roots, stems, and leaves.

Furthermore, morphological observation in thefield can provide useful information for determiningthe character of a plant that wants to be developed orbe a special identifier in distinguishing a plant. Mor-phological characters of the identifier is important canbe the identity of the plants. Morphological marker isthe first step of the observed directly based on the na-ture of the morphological characteristics among oth-ers are secondary (Jamsari, ). It can be assumed thatthe characterization of nibung as a mascot flora ofRiau is importance aspects.

On the other hand, characterization of the ethnob-otany study of nibung (O. tigillarium) is expected toprovide information about all the characters. So that itcan help in the effort of development and conservationof plants nibung for the future. The information on thecharacterization of nibung in Riau Province is still notthere. The less of the information about how the uti-lization of nibung plants in Riau Province support im-portance of this sudy. Therefore, the activities of thecharacterization in Riau Province nibung is very im-portant to observed. The aim of this study was to char-

250Desti, Fitmawati, Yulis, P. and Isda, M.Characterization of the Ethnobotany of Riau Province Mascot Flora (Oncosperma tigillarium (Jack) Ridl.).In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 250-253ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

acterize ethnobotany aspect of nibung (Oncospermatigillarium).

2 MATERIALS AND METHODS

Data collection were conducted at Bukitbatu,Bengkalis District, Riau Province, Indonesia (Figure1). Samples collected from the field were thenexamined for the ethnobotanical study of nibung(Figure 2).

Figure 1: Map of the location of the research.

Figure 2: Nibung plants in the field of the research.

The research method used in conducting this re-search is to use a survey method with interview tech-niques. Data collection techniques were carried outdirectly with questionnaire assisted communication(Singarimbun and Effendi, 1989).

The research method used included field observa-tions, discussions and deeply personal interview withlocal community. Data collected from the informantswere selected randomly. Interviews were conductedinvolving 24 respondents. Information was obtain byopen-ended interviewing, free, direct observations atcommunity location, sample collection, literature andits analyses.

Data collected from the respondents about theuses of nibung plants for type of plants, parts ofplants, the preparation and applications of plants, andthe kind of the use of parts of plants of nibung. Thosedata were compiled and presented descriptively.


Based on the results of interviews that have beenmade known that in general the community hasknown about the nibung plants. This is because theseplants are often found in the environment around theirhome. However, local people do not know that nibungwas a plant that has been used as a mascot flora RiauProvince.

It was found approximately more than five kindof useful of nibung plants in Bengkalis district, Riau(usefulness of parts of nibung plants in Riau Provinceshown in Table 1) were used by the communities.

Table 1: Usefulness of parts of nibung plants in Riau.

Parts ofnibung Usefulness Description

Root Herbal medicine

Water immersionroot nibung plantused by the communityas an abdominalpain medication

Stem

Building materials,shipyards, furniture,

and traditional

Malay weapons

Utilized as the mainmaterial of woodsubstitute, the materialof ”spear” ”for catchingthe fish in the river”

The BarkMaterials for roofingof houses and wallsof houses

Used as materials forbuilding materials

Leaves Roofing materialsand baskets

The leaves of nibungused for wicker materials

Flos As a fragrance of rice Used as food ingredients

Shoot offlower(“umbut”)

As a source of food

“umbut” used by thecommunity as a sourceof food with highnutritional value

In Riau Province, nibung’s stem are used for wa-ter pipes, floors of houses on stilts, or simple bridges.The bark can be woven into the roof or wall of thehouse. The leaves can be woven for the roof of the

Characterization of the Ethnobotany of Riau Province Mascot Flora (Oncosperma tigillarium (Jack) Ridl.)

251

house or basket. Flower buds (“umbut”) can be madefor vegetables.

Furthermore, part of the young shoots of plants ni-bung rated to have a better taste compared to bambooshoots of bamboo. From the inflorescence can be usedas a fragrance of rice. And while the fruit, can serveas a substitute of peanut to eat. In addition, nibunghas also been used by the people of Riau both for car-pentry materials, bridge poles and for weapons in theform of swords and spears, in the independence of thefighters in Riau who are in the coastal areas using ni-bung as a “spear”. It is linked to anatomical structureof nibung’s stem as same as the other palm plant suchas Bactris (TM et al., ).

In the traditional life of the Malay people of Riau,nibung was known hundreds of years ago. Closelylinked nibung with the people of Riau, among oth-ers, reflected from the name of this flora used for thename of a village or a particular place in Riau. In ad-dition, many traditional expressions and rhymes linkit to those plant. Nibung as a one of the characteristicof mangrove habitat have a potency for educotourismand to protected areas. It was been studied by the oth-ers researchers in Pahang, Malaysia (ZS et al., 2015).

Nibung plant has a uniqueness that is on the fiberthat is famous for its strength until. The fibers inthe tangential section (Figure 1) is different from thefibers in the radial section and this is what makes ni-bung a perfect wood substitute for the furniture in-dustry. That fact is accordance with the other re-search that has been conducted by Ernawati (2009)and Nurlia, et al. (2013) that nibung used by the com-munities in the pattern of utilization of marketing ni-bung from the habitat of that plant (Ernawati, 2009; Aet al., ).

The identity of the nibung plant that has been usedas the flora mascot of Riau Province is related to thestrength of the stem that symbolizes the character ofRiau Malay people who have persistence, have highfighting power, strong holds the customs of Malayculture. Therefore, nibung plant is also used as a sym-bol of the fraternal community of Riau Malay proper-ties, especially for Riau community.

Type of nibung plant rooting is root-shaped fibers.The stem and leaves are protected by spines hard longblack. Its leaves are arranged pinnatus with com-pound leaves type. Generative organs observed iscomposed of organs of the flowers and fruit. Flow-ers plants nibung arrayed in yellow. While the fruitis round-shaped, dark green to dark purple. Types offlowering and fruit plants observed nibung pertainedtype compound interest. Pollen of nibung has sin-gle type. It can be used to character palino on someplace. It is accordance with Winantris, et al. (2012)

that pollen of nibung flowers are can be used to iden-tify a part of delta plain character in Delta Mahakam,Kalimantan, Indonesia (I and Syafri, ).

Some parts of nibung plants used by the local peo-ple for traditional herbal medicines and wood substi-tute for the construction, fishery and furniture indus-try. Nibung leaves is also used for herbal medicine.The results of this study are in accordance withthe results of previous research conducted by Heyne(1987). It shows that it was one of the economic plantin Indonesia that used to medical usefull. It has thepotential as vary utilization (BE and G Hardiansyah, ;K., 1987).

4 CONCLUSIONS

Based on the results of the research that has been con-ducted, it can be conclude that nibung has an idealplant to support its wide use in the community. Ni-bung’s stem are used for water pipes, floors of houseson stilts, or simple bridges. The bark can be woveninto the roof or wall of the house. The leaves can bewoven for the roof of the house or basket. Flowerbuds can be made vegetables by the community.

Nibung has also been used by the people of Riauboth for carpentry materials, bridge poles and forweapons in the form of swords and spears. All of theparts of nibung plant have high economic value thatsupport the local community lives, hence used muchas construction materials, for example: buildings, fur-niture, and shipyards.

ACKNOWLEDGEMENTS

Directorate of Research and Public Service,Directorate-General of Research and Develop-ment for the Strengthening of the Ministry ofResearch, Technology and Higher Education,According to the Research Contract Number:284/KONTRAK/LPPM/4-2019 through ResearchandServices Institutes of Universitas Islam Riau (LPPMUIR).

REFERENCES

A., H. (2000). Arecaceae (Palmae). Flora NeotropicaMonograph 79.

A, N., H, S., and AH., L. 2013. The Pattern of Utiliza-tion of Marketing Nibung Around Sembilang NationalPark Area of South Sumatra Province. Journal Of For-est Research Plant. Vol. 10 No, 10:241–251.


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Anderson. 2009. Mangrove Guidebook for Southeast Asia.Part.

BE, K. and G Hardiansyah, I. 2015. Ethnobotany of DayakSociety relatives in the village of Perodah Sub-districtTapang Sekadau Regency Sekadau Upstream. JournalOf Sustainable Forest. Vol. 3, 3.

Ernawati, E. (2009). Ethnobotany Of The Malay TribesCommunity Land (A Case Study Of Village Aur Yel-low Excl. Kampar Kiri Hulu Kab. Kampar).

I, W. and Syafri, R. A. 2012. Oncosperma tigillarium is Partof Delta Plain Character Palino on Delta Mahakam,Kalimantan. Bionatura Journal of Science Biologicaland Physical Sciences. Vol. 14 No, 14:228–236.

J, D., NW, U., CB, A., WJ, B., MM, H., and CE., L. 2008.Genera Palmarum.

Jamsari. 2008. Introduction to Breeding, the cornerstone ofMolecular, Biological and Genetic.

K., H. (1987). The usefull plant of indonesia. 1.P, S., C, S., and A., L. G. H. (2009). Arecaceae (palmae).

In: Pei Shengji & Chen Sanyang. Edisi Fl. Reipubl.Popularis Sin.

S, B., HT, C., and S., A. (2013). Useful Product from Man-grove and other Coastal Plants. ISME Mangrove Edu-cational Book Series No, 3.

Singarimbun, M. and Effendi, S. (1989). Survey ResearchMethods. LP3ES. Jakarta.

TM, M., PB, T., and Huggett, B. 2015. Stem AnatomyIn The Spiny American Palm Bactris (Arecaceae-Bactridinae). Hoehnea.

ZS, S., MH, A., MH, M. R. K., Yusof, N. N., and Mukai,Y. (2015). 2015. Assessing the Potential of Man-grove Educotourism to Marine Protected Areas: ACase of Tioman and Tulai Islands, Pahang, Malaysia.The Natural Resources. 2015, 6:442–449.

Characterization of the Ethnobotany of Riau Province Mascot Flora (Oncosperma tigillarium (Jack) Ridl.)

253

Effect Stocking Density on Growth and Survival Rate of Larval SelaisFish (Kryptopterus lais) Cultured in Recirculation System

Agusnimar Muchtar and RosyadiDepartement of Aquaculture, Universitas Islam Riau, Pekanbaru, Indonesia

agusnimar, [email protected]

Keywords: Kryptopterus lais, Stocking Density, Recirculation, Survival, Growth.

Abstract: An experiment about the effect of three stocking densities (10, 30 and 50 larvae L -1) on growth and survival ofthe selais fish larvae, an important commercial species, and the source of income for the rural community wasconducted at the Fish Hatchery of the Agriculture Faculty, Universitas Islam Riau, Indonesia. Three-day post-hatched larvae (0.0012±0.00 g in weight ; and 0.03±0.00 cm in length) were used as test fish that obtainedfrom the artificial spawning of the selais fish broods. The fish larvae reared in recirculation system with awater flow rate of 0.05 L

-1, and fed with silkworms (Tubifex sp).This study used a completely randomized,

non-factor design with three treatments and three replications. The best growth in weight and growth in length(of 0.87±0.00 grams and 5.39±0.49 cm, respectively) were found in the T1 (stocking density was 10 larvaeL-1). The highest survival rate (57.33±7.72) was attained in T1 (stocking density was 10 larvae L-1) while thelowest survival (51.60%) attained in T3 (stocking density was 50 larvae L-1) . Growth rate and survival rate ofthe selais fish larvae were inversely proportional to the density of the fish larvae.There’s no significant effectof stocking density on the growth and survival of the selais fish larva (P>0.05).

1 INTRODUCTION

Selais fish (Kryptopterus lais) is a kind of freshwa-ter fish inhabits floodplain river ecosystems (Elvyraet al., 2010), and peatland waters in the Bukit-Batu Biosphere Reserve, (Fahmi et al., 2015), anecosystem that has unique characteristics in the RiauProvince. The selais fish is an important economiccommodity in Riau Province due to (1) it is very de-licious food ingredient, liked by many peoples so thatit become important trading commodity, (2) this fishis also a source of income for rural people becauseis the main source of raw materials for the fish indus-try, (3) these fish have the potential to be developed aseconomically valuable ornamental fish (Fahmi et al.,2015), (4) the selais are endemic fish that have thepotential to enrich fish populations in waters (stockenhancement) and restocking to lakes and reservoirs(Rengi et al., 2013; ?).

The population of the selais fish inhabiting fresh-water in Riau Province decline continuously (Rengiet al., 2013; Simanjuntak C P. H., 2008) due tohigh-intensity fishing, environmental damage and thethreat of the introduction of exotic fish against nativespecies. The impact of the this decline in fish pop-ulation did not only cause a decrease in fishermen’s

catches yield but also affects the stock of raw mate-rials for the smocked fish industry and the income ofrural people.

To overcome this problem, fish farming needs tobe developed. Domestication of fish selais has beencarried out through a series of studies so that thesefish can be artificially spawned, have received artifi-cial feed (Agusnimar and Rosyadi, 2013) and growoptimally in cultivated with the artificial feed in float-ing net cages (Rosyadi and Agusnimar, 2016) and inpond (Agusnimar et al., 2015).

Stocking density is a key factor affecting the pro-duction of cultured fish seeds, in addition to food sup-ply and quality, genetics, and environmental condi-tions.

An increasing in fish stocking density can in-crease fish seed production however the increase infish stocking density in culture media can reduce wa-ter quality, fish growth rate and degree of heterogene-ity of live fish (Slembrouck, 2005) therefore, to in-crease fish larval production by increased stockingdensities must be followed by the increasing of dis-solved oxygen because the rate of the dissolved oxy-gen in water can be a barrier to the survival of fishlarvae and can cause their death.

There is much larval death because there is not

254Muchtar, A. and RosyadiEffect Stocking Density on Growth and Survival rate of Larval Selais Fish (Kryptopterus lais) Cultured in Recirculation System.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 254-257ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

enough oxygen. The recirculation system can in-crease the support of the cultivation media (Kadariniet al., 2010).

The purpose of this study was to determine the ef-fect of differences in stocking density on the growthand survival of fish larvae (Kripthopterus lais) whichare maintained by a water recirculation system.

2 METHODOLOGY

The experiment was conducted at the Fish Hatcheryof the Agriculture Faculty, Universitas Islam Riau,Indonesia, from May 10 to June 25, 2016. Three-day post-hatched larvae (mean weight 0.0012±0.00g; mean length and 0.03±0.00 cm) were used as testfish that obtained from artificial spawning result of se-lected selais fish broods in total length 90-110 cm andaverage weight equal 100-120 gram.

Nine cylindrical plastic topless units were used asexperimental containers. the capacity of each toplesswas 15 liters, filled with 10 liters of water A recir-culation system connected to the physical filter and awater pump with a water flow rate of 0.05 L-1 was in-stalled in this experiment. Fish larvae were stocked inexperimental media at three different density levels:(10 larvae L-1 , 30 larvae L-1, 50 larvae L-1) . Fish lar-vae were fed silkworms (Tubifex sp) collected fromSail river in Pekanbaru. The silkworms were givento larvae using the ad libitum method. Fish growthdata were taken randomly and measured at the begin-ning and the end of the experiment. Both weight andlength were measured (nearest 0.01 g, total length ofthe closest cm, respectively). This study used a com-pletely randomized, non-factor design with 3 treat-ments and 3 replications as follows:

Treatment 1 (T1): rearing selais larvae with stockdensity 10 larvae in 1liter water (L-1); Treatment 2(T2): rearing selais larvae with stock density 30 lar-vae in 1 liter water (L-1); Treatment 3 (T3): rearingselais larvae with stock density 50 larvae in 1 liter wa-ter (L-1).

The parameters observed consists of initial and fi-nal ( weight and length) growth and survival fish lar-vae. Base on that data the performance growth andsurvival of selais fish larvae were calculated base onthe equation :

• Weight Gain (WG) = Mean final weight – Meaninitial weight

• Daily Weight Gain (DWG) = Fresh weight gain infish (g) / t

• Specific growth rate/day (SGR) = [(Log finalweight – Log initial weight) x 100] / t

• Survival rate (SR) = (Final number of fish/Initialnumber of fish) x 100.

Performance of the growth and survival data wereanalyzed by one-way analysis of variance (ANOVA)to determine the difference in density for each treat-ment and the least -squares difference (LSD) test wasapplied when significant differences were found.

The water quality parameters such as temperature,pH and DO was measured straight from the mediaexperiment in Fish Hatchery of Agriculture Faculty,Islamic University of Riau, while ammonia was ana-lyzed in the laboratory of the Environmental Qualityof Riau University.


3.1 Growth and Survival Rate

The weight growth of selais fish larvae effected bydifferent stocking density presented in table 1.

Table 1: The weight growth of selais fish larvae cultured ondiffrent stocking density.

Parameters Weight Growth of Selais Fish LarvaeT1 T2 T3

Average Initialweight (g)=ALW 0.0012±0.00 0.0012±0.00 0.0012±0.00

Average Finalweight (g)=AFW 0.88±0.00 66±0.00 0.64±0.00

Wight pain (g)= WG 0.87±0.00 0.66±0.00 0.64±0.14Daily wight rate(g) = DWG 0.04±0.00 0.03±0.00 0.03±0.01

Specific growthrate (%/day) = SGR 13.63±0.15 13.042±0.25 12.96±0.26

As shown in table 1 that the performance ofgrowth weight of selais fish larvae was varied in dif-ferent stocking densities. However base on analy-sis of variance we found that there were no appar-ent effects of stocking density (10, 30, 50 larvae L-1)on the growth at the levels tested (P>0.05). Thebest wight rate (WG, DWR, and SGR, 0.87±0.00g/day: 0.04±0.00, and 13,63 ±0.15%, respectively)was found in treatement of T1 (stocking density of10 larvae L-1) while lowest growth rate (WG, DWRand SGR: 0.64±0.14 g/day, 0.03±0.01, and 12,96±0.26%, respectively ) was found at treatement of T3(stocking density of 50 larvae L-1).

This result indicated that the higher stocking den-sity the slower the weight gain, daily weight rate, andspecific growth rate/day. Prior research (Darmawanand Suharyanto, 2017) reported the similar effects ofhigh stocking densities on growth of Jambal catfish(Pangasius djambal).

The length growth of selais fish larvae effect bydiffrent stocking density presented in table 2.

Effect Stocking Density on Growth and Survival rate of Larval Selais Fish (Kryptopterus lais) Cultured in Recirculation System

255

Table 2: The Length Growth of Selais Fish Larvae Culturedon Different Stock Density.

ParametersLength Growth of Selais Fish LarvaeT1 T2 T3

Average InitialLength (g)=ALW

0.03±0.00 0.03±0.00 0.03±0.00

Average FinalLength(g)=AFW

5.42±0.49 5.31±0.02 5.20±0.24

Length pain (g)= WG 5.39±0.48 5.28+0.02 5.17+0.24Daily Length rate(g) = DWG

0.26+0.02 0.25+0.01 0.25+0.02

Specific Lengthrate (%/day) = SGR

10.74+0.00 10.70+0.00 10.55+0.00

Similar with performance of the growth weight,the highest length growth (LG,DLR, and SLR, 5.39±0.48 cm/day: 0.26±0.02, and 10,74 ±0.10%, re-spectively ) of selais fish larvae was found at treate-ment of T1 (stocking density of 10 larvae L-1), whilelowest length growth (LG, DLR, and SLR were5.17±0.00 g/day : 0.25±0.02 , and 10.55±0.00%, re-spectively) was found at treatement of T3 (stockingdensity of 50 larvae L-1).

It was mean that the best length growth of selaisfish larvae found in the lowest stoking density. Sim-ilar findings were recorded in other reared species(Herrera, 2015; Huet, 1971) who achieved the bestgrowth of fish larvae at lower stocking densities.

The high growth (weight and length) of fish larvaein treatment of T1 compared to T2, and T3 may bedue to fish larvae maintained with low stocking den-sity do not spend much energy to compete using morespace and food. Haque et al. (Haque et al., 1984) saidthat the fish that were kept with the lowest stockingdensity provide more space, food, and less competi-tion. So that the fish larvae in the T1 treatment (thelowest stock density of fish larvae in this experiment)have more energy to support the growth of fish larvaein the treatment of T1.

Survival rate of selais fish larvae on differentstocking density was shown ini table 3.

Table 3: The Survival Rate Of Selais Fish Larvae CulturedOn Different Stock Density.

Replication Survival rate selais fish larvae(%)T1 T2 T3

1 68,00 50,67 54,002 54,00 62,67 52,003 50,00 52,00 48,80

Total 172,00 163,33 154,80Average 57,33 55,11 51,60

In table 3 was shown that the survival rate of selaisfish larvae was varied (T1,T2, and T3 was 57,33%,55,11%, and 51,60%, respectively) in different stock-ing densities. However base on analysis of variance

we found that there were no apparent effects of stock-ing density (10, 30, 50 larvae L-1) on the survival atthe levels tested (P>0.05). The best survival rate wasfound in T1 (stocking density of 10 larvae L-1) whilelowest growth was found at T3 (stocking density of50 larvae L-1).

The results of this study also show that the sur-vival rate of selais fish larvae is inversely proportionalto stocking density. The higher stocking density, thelower the survival of fish larvae. This means thatstocking density is a determining factor for the sur-vival of fish larvae. According to Herrera (Herrera,2015) stocking density affects survival, growth, be-havior, health, water quality, food, and production.

The survival rate of fish larvae in this study wasrelatively low (<58%) because of the high mortalityof larvae during the study. The high mortality rate offish larvae in this experiment may be caused the testfish larvae used in this experiment were pre-larvae ofselais fish (three-day post-hatched larvae mean weight0.0012±0.00 g; mean length and 0.03±0.00 cm).while another research (Efendi et al., 2016) found thatthe survival rate of post- larvae of selais fish larvaefeed Tubifex sp enriched with probiotic was reached98%, The survival rate of selais fish larvae can be in-creased by giving probiotics through natural feed suchas Tubifex sp.

3.2 Water Quality

The result of measurement on water quality parame-ters can be seen in table 4. The average temperaturefound in all treatment was the same about 260C-300C.It means the water temperature for fish larvae in alltreatment was optimal. It is stated the optimal tem-perature for fish life is 250C- 320C (Boyd, 1989; ?).The degree of water acidity [pH] in media culture atall treatment were ranged among 6,0-6,5. Even if thepH of the water in the research was not optimal forfish larvae, but it still supports the growth and sur-vival of the selais fish, According to (Elvyra et al.,2010) selais fish (K. limpok) be able to live in the wa-ter with a little bit acidic water that ranged between5,5-6,0. Dissolved Oxygen (DO) in this research were5,0 – 5,2 ppm higher than the amount of the DO(3,16–3,45ppm) in the aerated container using aera-tor. The height of dissolved oxygen in this researchcaused by the using of recirculation system while thedebit water that entered in research container 0.05 1/second.

The concentration ammonia (NH3) in culture me-dia ranged between 0.29-0,63 ppm. It means theamount of ammonia in the culture media was still inthe eligibility limit on the selais fish larvae. Boyd


256

Table 4: The Water Quality Parameters.

Water Quality TreatmentsParameters T1 T2 T3Temperaturs (OC) 26-30 26-30 26-30pH 5.0-6.0 5.0 - 6.0 5.0 - 6.0DO (ppm) 5,2 5 5Amoniak (NH3) 0,29 0,29 0,63

(Boyd, 1989) stated that the NH3 concentration withranged between 0,6-2 ppm is still good for the fishlife.

The concentration of ammonia in each treatmentwas treated differently. The ammonia content in treat-ment of T1 (0,29 ppm) is the same as the ammonia intreatment of T2, while the highest ammonia contentis in the treatment of T3 ( 0.63). It means, the higherthe stock density, the higher the ammonia content.

4 CONCLUSIONS

Base on result and discussions, there’s no effect ofstocking densities on the growth and survival of theselais fish larvae cultured in the recirculation system.

The growth rate and the survival rate of selais fishlarvae were inversely proportional to the density offish larvae. The higher the stocking density the slowergrowth rate (weight and length), and survival rate.The optimal growth rate and survival rate found atlower stocking densities (10 larvae L−1).

REFERENCES

Agusnimar, A. and Rosyadi, R. (2013). Pengaruh kombi-nasi pakan alami dan buatan terhadap kelulushidupandan pertumbuhan larva ikan selais (kryptopterus lais).DINAMIKA PERTANIAN, 28(3):255–264.

Agusnimar, A., Sholihin, S., and Rasyidi, A. F. (2015). Ke-langsungan hidup dan pertumbuhan larva ikan selais(kryptopterus lais) yang diberi cacing sutera (tubifextubifex) utuh dan olahan. DINAMIKA PERTANIAN,30(1):77–82.

Boyd, C. E. (1989). Water quality management and aerationin shrimp farming.

Darmawan, J. and Suharyanto, E. (2017). Growth and sur-vival of larva/patih jambal fish seed (pangasius djam-bal) maintained solidly different distribution. j fishaqua dev: Jfad-121. doi: 10.29011. Technical report,JFAD-121/100021.

Efendi, H., Agusnimar, A., and Warman, E. (2016). Pen-garuh perbedaan rentang waktu perendaman larvadalam larutan probitik terhadap kelulushidupan danpertumbuhan ikan selais (kryptopterus lais). DI-NAMIKA PERTANIAN, 32(2):143–150.

Elvyra, R., Dedy, D., Ridwan, A., and Zairin, J. (2010).Kajian aspek reproduksi ikan lais ompok hypophthal-mus di sungai kampar, kecamatan langgam, kabupatenpelalawan, provinsi riau. Jurnal Natur Indonesia,12(2):117–123.

Fahmi, M. R., Ginanjar, R., and Kusumah, R. V. (2015).Diversity of ornamental fish in peatlands biospherereserve bukit-batu, riau province. In Prosiding Sem-inar Nasional Masyarakat Biodiversitas Indonesia,volume 1, pages 51–58.

Haque, M. M., Islam, M. A., Ahmed, G. U., Haq, andS., M. (1984). Intensive culture of Java tilapia (Ore-ochromis mossambica) in floating pond at differentstocking density. Bangladesh J. Fish., 7:55–59.

Herrera, L. C. (2015). The effect of stocking density ongrowth rate, survival and yield of GIFT tilapia (Ore-ochromis niloticus) in Cuba: case study fish farm LaJuventud. United Nations University Fisheries Train-ing Programme.

Huet, M. (1971). Textbook of fish culture. Breeding Culti-vation of Fish. Fishing New Book, 456.

Kadarini, T., Sholichah, L., and Gladiyakti, M. (2010).Pengaruh padat penebaran terhadap sintasan dan per-tumbuhan benih ikan hias silver dolar (metynnis hyp-sauchen) dalam sistem resirkulasi. Jurnal UniversitasDiponegoro, Semarang.

Rengi, P., Alawi, H., et al. (2013). Kajian stok ikan selais(cryptopterus spp) di perairan umum kabupaten kuan-tan singingi. Berkala Perikanan Terubuk, 41(2):40–57.

Rosyadi, R. and Agusnimar, A. (2016). Pemberian je-nis pakan berbeda terhadap pertumbuhan ikan selais(kryptopterus lais) di perairan tasik betung sungaimandau. DINAMIKA PERTANIAN, 32(2):97–106.

Simanjuntak C P. H., M. F. R. A. S. S. . (2008). Spawn-ing Season and Fecundity of Ompok hypophthalmusIn Floodplain of Kampar Kiri River, Riau. JurnalPerikanan (J. FISH. Sci) X.

Slembrouck, J. (2005). Technical manual for artificial prop-agation of the indonesian catfish, pangasius djambalenglish.

Effect Stocking Density on Growth and Survival rate of Larval Selais Fish (Kryptopterus lais) Cultured in Recirculation System

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Development of Safety Plan to Improve OHS (Occupational Healthand Safety) Performance for Construction of Dam SupportingInfrastructure based on WBS (Work Breakdown Structure)

Aprilia Dhiya Ulhaq, Yusuf Latief and Rossy Armyn MachfudiyantoDepartment of Civil Engineering, Universitas Indonesia, Jakarta, Indonesia


Keywords: Safety Plan, Risk Identification, Dams, Access Roads, Bridges, Tunnels, Dodge Channel, OHS Performance.

Abstract: Of all existing construction projects such as buildings, roads, dams, irrigation channels, bridges and tunnels,Dam is one of the construction projects that has the highest probability of a workplace accident in the world.By developing a safety plan based on the use of WBS (Work Breakdown Structure) that has been standardizedas an object in this research to obtain risks that have an impact on workplace accidents, it is expected to reducethe level of workplace accidents that occur. This study aims to develop a safety plan to reduce the level ofworkplace accidents as one indicator of OHS (Occupational Health and Safety) performance using qualitativemethods. The results of this study are sources of risk and risk that are classified as high which have potentialhazards and have an influence on OHS performance on the components of the Road Access and Bridges aswell as Tunnels and Dodge Channels. In addition, a safety plan document will be developed based on theRK3K PU 05 / PRT / M / 2014 format and refers to the high risks that have been identified based on the WBSto achieve improved OHS performance by reducing the rate of workplace accidents.

1 INTRODUCTION

Dams are buildings in the form of land, stones, con-crete, or stone pairs that are built in addition to hold-ing and storing water, can also be built to hold and ac-commodate mine waste (tailings) or to collect mud sothat reservoirs are formed (PP No. 37 of 2010). In the2014-2019 period, dam projects in Indonesia will becarried out on a large scale. Indonesian government iscurrently keen to realize this infrastructure (Kausarianet al., ). Given a large number of stakeholders / partiesinvolved in the construction process, then in its plan-ning, a standard that can be used by various partiesthat carry out its construction needs to be used. Thestandard was created in a systematic form in the formof WBS (Work Breakdown Structure) that has beenstudied by (Hidayah et al., 2018). The existence ofthis WBS standard will present uniform requirementsin the estimation, monitoring and control (PMBOK,2017).

According to (Hidayah et al., 2018) Standard DamWBS consists of 8 supporting infrastructure / subpro-ject jobs in naming the level at the WBS, namely:Preparation, Access Roads and Bridges, Cofferdam,Tunnels and Dodge Channel, Main Dam, Spillway,Intakes, and other public facilities work. The lowest

level on the WBS will present a series of detailed ac-tivities on the project. Each predetermined WBS levelbrings the WBS to a more complex level of activity, inwhich case activities are strongly affected by risk andrisk will have an impact on the safety planning (Elsyeand Latief, 2018). This plan is an attempt to preventthe occurrence of undesirable things that can lead toworkplace accidents (Maengga, 2015).

Based on the 2014 Data and Information Center ofthe Indonesian Ministry of Health, every job alwayscontains potential hazard risks in the form of work ac-cidents where the amount of potential depends on thetype of production, technology used, materials used,spatial planning and building environment as well asthe quality of management and implementing staff.Of all the existing construction projects, the dam isa construction project with the highest work accidentrate in the world. ICOLD since 1965 conducted stud-ies until 1973, there were at least 236 accidents ofvarious types of dams caused by various things and76 accidents caused by design and 41 caused by con-struction (Asiyanto, 2011).

Workplace accidents can be prevented if all partiesinvolved in construction projects start from the high-est level such as reaching the lowest level such as theworkers paying attention to and prioritizing OHS (Oc-

258Ulhaq, A., Latief, Y. and Machfudiyanto, R.Development of Safety Plan to Improve OHS (Occupational Health and Safety) Performance for Construction of Dam Supporting Infrastructure based on WBS (Work Breakdown Structure).In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 258-267ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

cupational Health and Safety) aspects in each stage ofthe construction work carried out by creating a haz-ard handling strategy. Strategies for handling occu-pational hazards in construction can remove poten-tial hazards, further investigation of hazards that oftenoccur and can produce a safety plan on constructionprojects (Albert, 2014). Therefore, it is necessary todevelop a safety plan with a WBS (Work BreakdownStructure) as a tool that will be used to compile thecategory and urgency of project risk assessment as asystematic risk system based on its source (Mhetreet al., 2016).

2 RESEARCH OBJECTIVES

The objective of this study is:

• To Identify sources of high potential hazard riskthat affect OHS performance indicators (work-place accidents) at Access Road and BridgeWorks and Tunnel and Evacuation Channels fromDam WBS (RQ1)

• To develop a risk-based safety plan from WBSDam for Access and Bridge Road Works and Tun-nel and Dodge Channels (RQ2)

3 LITERATURE REVIEW

3.1 Work Breakdown Structure (WBS)in Dam Construction

The WBS (Work Breakdown Structure) is a hier-archical decomposition of the entire scope of workthat must be done by the project team to achieveproject objectives and create the necessary work re-sults, where each level decrease shows a more de-tailed definition (Institute, 2017).

Based on (Hidayah et al., 2018), the WBS Stan-dard for dam construction projects for each subpro-ject consists of 4 levels. Dam projects can be dividedinto 8 (eight) work subprojects, namely Preparation,Access Roads and Bridges, Cofferdam, Tunnels andDodge Channel, Main Dam, Spillway, Intakes, andother public facilities work. The following is an ex-ample of Standard WBS Identification in tunnel anddodge channel construction:

• Level 1 is the name of the project (dam subproject:tunnel and dodge channel)

• Level 2 is the Work Section (dewatering, soil, sup-port and protection, concrete, drilling, and grout-ing)

• Level 3 is the Sub Work Section (for a sub worksection of support and protection there are supportand protection for open excavation work and sup-porting work for tunnel excavation)

• Level 4 is the Work Package (for work package ofsupport and protection for open excavation workconsisting of a shortcrete wire mesh protectionpackage, grouted anchor protection, masonry pro-tection, and dolken wood protection)

• Alternative Methods / Design between Level 4and Level 5

• Level 5 is an activity which is a derivative of awork package

• Level 6 is resources such as material, equipment,and labor resources

3.2 Risk Management

Risk is a variation in terms of what might happen(Fisk, 1997). Risk is considered a negative term, butin the engineering construction industry, managingrisks that arise is very necessary and carried out ina structured manner, knowledge of risk managementthat can nullify and minimize the risk of occurring inconstruction projects (Mhetre et al., 2016). Risks arethreats to life, property, or financial impacts due to thedangers that occur (Duffield and Trigunarsyah, 1999).

Risk management is all series of activities relatedto risk, namely planning, assessment, handling, andmonitoring (Kerzner, 2001). According to risk as-sessment carried out with 2 methods namely qualita-tive analysis and quantitative analysis (Mhetre et al.,2016). The qualitative analysis focuses more on de-termining priority risks, identifying risks, seeing theirimpact on projects and relying on experts as a compar-ison, while quantitative analysis is more on statisticalcalculations (Institute, 2017). This study uses qual-itative risk analysis with a probability / Impact RiskRating Matrix that is referenced by PMBOK becausethe results of validated questionnaires to experts arebased on priority risk assessments using probabilities,impacts and other influential factors.

Risk handling (RR) can be categorized into 4 cat-egories, namely: Avoid / V, Mitigation / M, Transfer/ T, and Accept / A (Labombang, 2011). Accordingto (Mhetre et al., 2016) Avoid is done by reducing allcauses of risk, Mitigation is done to reduce the possi-bility or impact of risk, Transfer by transferring riskto other parties to be responsible for the managementand if it occurs, Accept is done when it is impossibleto reduce or take advantage of risk.

Development of Safety Plan to Improve OHS (Occupational Health and Safety) Performance for Construction of Dam SupportingInfrastructure based on WBS (Work Breakdown Structure)

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3.3 Concept of OHS or SafetyPerformance

3.3.1 Definition of OHS or Safety Performance

Based on OHSAS 18001: 2007 Clause 3.15, OHS(Occupational Health and Safety) Performance is ameasurable result of managing an organization’s OHSrisk, with a note:

• OHS performance measurement includes a mea-surement of control effectiveness implemented bythe organization.

• In the context of the OHS management system,the results can be measured compared to the orga-nization’s OHS policy, the objectives of the OHS,and the OHS performance requirements

3.3.2 OHS or Safety Performance Indicators

According to (Wu et al., 2015) and (Lu et al., 2016)Indicators of safety performance consist of 6 things,namely:

• Safety awareness, the safety awareness of a con-struction project is the awareness of all stakehold-ers from the leadership to the workers

• Safety costs, Safety Costs must be part of theinvestment that is measured and carried out inSMK3 which includes training, incentives, andsalaries of safety supervisors.

• Accident Level, Safety documentation of con-struction projects is an element of awareness andsecurity of construction project performance andcan be considered as a measure for performanceevaluation

• Productivity, Safety, and productivity are the mostimportant requirements in improving the perfor-mance of construction projects

• Management of self-discipline, to ensure con-struction safety, the company has good control ofall aspects, such as security objectives, mecha-nism for construction assessment procedures andresource mobilization

• Performance Measurement, Companies can iden-tify deficiencies in occupational health perfor-mance according to previous historical knowl-edge, and then make a quick and effective re-sponse.

According to (Garza et al., 1998) measurement ofwork safety performance can be viewed from 5 as-pects, namely:

• Injury frequency rate

• Injury severity rate

• Average days change per disabling injury

• Project accident cost figures

• Number of incidents of work accidents

3.4 Safety Plan Concept inConstruction Projects

3.4.1 Definition of Safety Plan

The safety plan is a plan document that contains prac-tical safety that can help companies avoid potentialhazards and can control them in the best way when inthese hazard conditions (Elsye and Latief, 2018). Inprojects carried out by the Ministry of Public Works,the Safety Plan is known as RK3K or OHS ContractPlan.

RK3K is a complete document of the plan for theimplementation of the Management System of OHS(SMK3) in the PU Sector and is a unit with the con-tract document of a construction work made by theservice provider and approved by service users andsubsequently used as a means of interaction betweenservice providers and service users in implementingManagement System of OHS (SMK3) of the PU (TheMinistry of Public Works) field. In the standard safetyplan, the document created is a document for the oper-ational safety issues by covering hazard identification,risk assessment, and mitigation steps and conditionsthat must be met to maintain the level of safety.

3.4.2 Safety Plan Format

The ministry of manpower as a stakeholder develops asafety program indicates the variable (Machfudiyantoet al., 2018). Based on the format stated in govern-ment regulations PU 05 / PRT / M / 2014, this docu-ment consists of several parts, namely:

• OHS Policy

• OHS Organization

• OHS Planning

– Hazard Identification, Risk Assessment, Pri-ority Scale, Safety Risk Control, ResponsiblePerson

– Compliance with laws and regulations andother requirements

– OHS Objectives and Programs

• OHS Operational Control

• Examination and Evaluation of OHS Performance

• OHS Performance Review


260

All the parts mentioned above already have theirrespective writing formats.

4 METHODOLOGY

This research was conducted with a qualitative ap-proach to answer the research objectives. Surveys anddiscussions were carried out using structured researchinstruments in the form of questionnaires to expertsfrom dam work with more than 10 years of experi-ence. The flow of research can be seen from the fol-lowing picture

Figure 1: The research flow diagram


5.1 To Answer RQ1

5.1.1 Risks Affecting OHS PerformanceIndicators

Potentially hazardous risk identification is carried outfor each activity of each work package derived fromthe results of a literature study taking into account thedetailed methods and resources of the Standard DamWBS (Work Breakdown Structure) for the work of ac-cess and bridge roads and tunnel and duct ducts. Fromthe results of identification of these risks 507 risks thathave the potential to be hazardous and affect the OHS(Occupational Health and Safety) performance indi-cators are the accident rates.

The results of risk identification are then verified,clarified, and validated for content and contract by ex-perts. This strategy is carried out with a discussionwith experts related to whether the risks include po-tentially dangerous risk factors, relevant or not withtheir activities and whether there are additional risksthat have not been included.

The results of the discussion found 323 risks af-fecting the OHS performance indicators, namely thelevel of accidents in the access and bridge road sub-projects and 312 risks for tunnel and evacuation sub-projects from the dam WBS. Due to the number ofrepetitions of the same risk due to repetition of thesame activity, the recalculation of the risk is carriedout. To obtain 160 risks in the access road and bridgesubprojects and 125 risks of tunnel and dodge subpro-jects.

Then a pilot survey is conducted to the respondentto find out whether all the risks that have been identi-fied previously can be understood by everyone in theproject environment.

5.1.2 Risk Assessment

Risk evaluation of a project depends on the probabil-ity of occurrence (frequency) and its impact (Duffieldand Trigunarsyah, 1999).

FR = FxD (1)

Risk evaluation which is then called risk levelanalysis (FR) is a multiplication between frequency(F) and impact (D) which in this study was obtainedfrom the distribution of questionnaires with a likeli-hood scale of 1-5. The following are indicators of thescale:


261

Table 1: Frequency Scale Indicator (F).

Scale Criteria Indicators

1 Very Low Very unlikely to occur

2 Low It is less likely to occur

3 Moderate Pretty likely to occur

4 High May occur

5 Very High Very possible to occur

Table 2: Impact Scale Limit (D).

Scale Severity/Loss/Impact IndicatorPerson Property

1 Does not cause laborto be injured

Do not causeinterference tovehicles or heavyequipment orsurrounding facilitiesor cause physical carefor at least 15 minutes

2

The workers arelightly injured(enough first aidtreatment or clinic)and can continue towork

Causes minimaldisruption to vehiclesor heavy equipmentbut does not causework to be hampered

4

Workers are severelyinjured to disabilityof functions or organsand need treatmentoutside the projectlocation (clinic orhospital) 2x24 Hours

Facilities andequipment wereseverely damaged,requiring 1-7 days ofrecovery

5Workers experiencepermanent disabilityor die

Facilities andequipment wereseverely damaged,requiring more than 7days of recovery

From the likelihood scale, the weighting will becarried out on the PMBOK scale. The following isthe weighting:

Table 3: Weighting Frequency and Impact.

Value Criteria F WeightF

Criteria D WeightD

1 Very Low 0,1 No effect 0,052 Low 0,3 Less influ-

ential0,1

3 Moderate 0,5 Pretty In-fluential

0,2

4 High 0,7 Influential 0,45 Very High 0,9 Very influ-

ential0,8

The weighting when multiplied to obtain FR val-

ues will result in the FR (risk level analysis) categoryrange as follows:

Table 4: Risk Category.

Risk Score Risk LevelAnalysis

Steps for

Handling(FR)

0.18 - 0.72 High Risk Reduced risk iscarried out to alower place

0,06 – 0,17 ModerateRisk

Correctionsteps areneeded in acertain period

0.01 - 0.05 Low Risk Repair stepswheneverpossible

After the calculation is done, 17 of the highestrisks are obtained as shown in table 5.

Figure 2: Risk Causes and Impact Matrix.

Figure 3: Recognition Pattern for Highest Risk.


262

Table 5: The Highest Risk That Affects OHS Performance; Subprojects: Tunnel and Dodge Channels.

Risk Rank Risk Score Activities Work Package

An explosionoccurred due tomissfire duringdrilling

10,2611

Installation of Explosives (Drilling) Stone Drilling

Closed Excavation / Tunnel

2 0,2580 Drilling Rockbolt Protection

Lack of oxygen

5 0, 2176

Making an Air Ventilation System(Suction and Blowing)

Closed Excavation / Tunnel

excavation work Excavation

Stone DrillingStone Retaining WallProtectionDolken Wood Retaining WallProtection

Being crushed orexposed to blast-ing debris

15 0,1814 Stone BlastingStone Drilling

Closed Excavaton / Tunnel

5.2 To Answer RQ2

Before developing the RK3K/safety plan document,it is necessary to know the causes and impacts of therisks that occur so that a risk response can be foundthat will be used in the development of RK3K.

5.2.1 Causes and Effects of Risk

According to experts during the discussion, in theconstruction of the Dam, in general, can be sepa-rated into 2 work, namely preparation and main work.Work that is generally included in the main work indam construction is work that requires special meth-ods in its implementation such as excavation, em-bankment, concrete placing, blasting, formwork in-stallation. While other works just use simple meth-ods.

Of all the causes it has been concluded that thereare 15 causes of risk that produce 9 different impactswhich can be seen from the table below.

In activities classified as preparation work, thecauses of risk in the project are usually caused byP1, P3, P4, P5, P6, while the activities classified asmain work are caused by causes caused by prepara-tory work and added by P2, P7, P8, P9, P10. It provesthat an error occurred in the design or inappropriateconstruction (Kausarian et al., 2018).

Then an analysis of causes and impacts is illus-trated through a matrix to find the root of the problemand the impact of each risk on OHS (OccupationalHealth and Safety) performance. The analysis can beseen in figure 2. From the matrix below it can be seenthat the same impact can be caused by more than onecause. For example, impact 1 (D1), which is injury,wound, or death can be caused by all causes.

5.2.2 Risk Response

Risk response is a handling action taken against therisks that may occur (Labombang, 2011). Based onthe analysis of the causes and effects of high risk asstated in Table 5, it was concluded that there were15 preventive measures and 13 corrective actions thatcould be taken.

Of all the causes, the impact of preventive andcorrective actions was analyzed using the recognitionpattern at the highest risk shown in table 5. The recog-nition pattern can be seen from figure below.

5.2.3 Development of the Safety Plan

From the results of discussions with experts, theRK3K/safety plan document whose the general for-mat had been submitted previously was carried out insection C.1 which has been arranged in a table format


263

Table 6: The Highest Risk That Affects OHS Performance; Subprojects: Acces and Bridge Road.

Risk Rank Risk Score Activities Work Package

Workers are hitby piles duringlifting / erecting

3 0,2290 Steel Pole Designing Structural Steel Piles

7 0,2100 Drafting of Wood PilesWood Piles14 0,1893

11 0,1987 Design of Prefabricated ConcretePiles

Pre- fabricated Concrete Piles

4 0,2195 Placing the girder on the bearing pad Erection using the doublecrane method

Falling from aheight

6 0,2113

Reinforcement Abutment / Column / PierHead (Concrete Cast Insitu)

Expansion Joint

Bearing Pad Elastomer Bearing PadTower cranecollapsed due tooverload

8 0,2022 Installation of Concrete DrainagePrecast Box Culvert

Concrete Drainage PrecastBox Culvert

Precast concretebefalls workers

9 0,2020 U-Ditch Precast Concrete DrainageInstallation

U-Ditch Precast ConcreteDrainage


Concrete Drainage PodcastBox Culvert

Workers areburied in landduring excava-tion work

12 0,1925 Mechanic Excavation Ordinary Land

Excavation

Soft Stone Excavation

Stone Drilling

Paved Pavement ExcavationExcavation of ConcretePavement

Structure ExcavationBroken SlingCrane


Concrete Drainage PrecastBox Culvert

Table 7: Effect of Risk Affecting OHS Performance Indicators (Work Accidents)

Code Effect Affected Subjects

D1 Injury, Wound, DeathLabor and CommunityD2 Raises doubts for other workers

D3 Feel uncomfortable living around the project area Society

D4 The project stopped temporarily Projects

D5 Labor and equipment are idle or unproductive Projects

D6 The results of construction are too late to use Company

D7 Nearby equipment and facilities are damaged Company

D8 Got a bad company image Company

D9 Construction failure Company


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Table 8: Causes of Risk Affecting OHS Performance Indicators (Work Accidents)

Code Cause

P1 Human Error (Workers are tired, unhealthy, or negligent)

P2 Do not carry out the correct work safety procedures for each job

P3 Using Personal Protective Equipment (PPE) that is incomplete or not used at allP4 Do not carry out the Toolbox meeting / Safety Briefing / Safety Morning Talk (SMT) before starting work

every day

P5 Lack or absence of OHS signs or safety lines

P6 Do not do House Keeping or 5R (Compact, Neat, Clean, Care, Diligent)

P7 Missing or not following Work Instruction (WI)

P8 There is no safety plan document or safety plan that does not refer to field conditions

P9 Errors in planning and doing work methods (incorrect or not on target)

P10 Work supervision or safety patrol is not carried out routinely or according to procedures

P11 Do not anticipate conditions (weather or hydrology) in the project location that affect the work

P12 The equipment used does not meet the standard specifications

P13 There is no quality control or checking the specifications of the material or tool used

P14 Material and tool checking is not carried out under applicable proceduresP15 The appointment of workers is not selected or not through the right process so that workers are less competent

in their field

Table 9: Preventive Action

Code Preventive Action RR

TP1 Carry out the Toolbox meeting / Safety Briefing / Safety Morning Talk (SMT) before starting workevery day

M

TP2 Using a complete Personal Protective Equipment (PPE) M

TP3 Give and take training or coaching work methods M

TP4 Socialization to the public regarding the control of hazards that can be caused by the project M

TP5 Conduct maximum control of hazards by conducting routine and comprehensive supervision regard-ing work safety programs

M

TP6 Arrange Job safety analysis before doing work M

TP7 Make comprehensive construction safety regulations M

TP8 Ensure that the worker is healthy before working M

TP9 Use worker that has a certificate or a specialist at his job and has experience M

TP10 Carry out Quality Assurance to ensure material specifications or tools according to standards M

TP11 Make Work Instruction (WI) for work methods that are easily understood by workers M

TP12 Plan a work safety program before the project starts M

TP13 Reviewing real conditions in the field in determining the safety plan before the project starts M

TP14 Use OHS warning signs or safety lines and barricades M

TP15 Perform workplace or housekeeping cleaning or 5R (Compact, Neat, Clean, Care, Diligent) M

from goverment regulations PU 05 / PRT / M / 2014shown in figure 4.

The results of the development shown in figure 5,carried out are by detailing the job descriptions di-vided into 2, namely work packages (level 4 WBS/Work Breakdown Structure) and activities (level 5

WBS) and in the risk control column detailed withpreventive actions and corrective actions for construc-tion work. So it can be seen an example of the de-velopment of section C.1 in the image below for thehighest risk.


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Table 10: Corrective action

Code Corrective action RR

TK1 Evacuation and further handling of victims A

TK2 Providing health insurance to workers T

TK3 Socialization to the public regarding the control of hazards that can be caused by the project A

TK4 Recovery activity A

TK5 Conduct OHS socialization to workers both in the form of safety talk, safety induction, and toolboxmeeting

A

TK6 Use experts when making a safety plan A

TK7 Increase learning lessons for specifications of types and methods of work A

TK8 Make and carry out a safety plan / safety procedure for the method of work to be carried out A

TK9 Reviewing real conditions in the field in determining the safety plan before the project starts A

TK10 Replace tools according to specifications needed and according to standards A

TK11 Change workers with more competent and experienced people V

TK12 Carry out the Toolbox meeting / Safety Briefing / Safety Morning Talk (SMT) before starting workevery day

A

TK13 Conduct training to be responsive to risk that is going to be a disaster A

Figure 4: Table C.1 Hazard Identification, Risk Assessment, Priority Scale, Safety Risk Control, Responsible Person formatfrom goverment regulations PU 05 / PRT / M / 2014.

Figure 5: The results of the development table C.1 Hazard Identification, Risk Assessment, Priority Scale, Safety Risk Control,Responsible for the Highest Risk of Tunnel Subprojects and Dodge Channels.


266

6 CONCLUSION

Based on the process carried out to develop a safetyplan, it can be concluded that 10 high risks in the ac-cess and bridge road subprojects and 5 high risks inthe tunnel and dodge subprojects on the dam projectcan be seen from table 5.

By using the highest risk, the development of asafety plan was developed from the RK3K PU 05 /PRT / M / 2014 document. The results of the devel-opment carried out are by detailing the job descrip-tions WBS (Work Breakdown Structure) divided into2, namely work packages (level 4 WBS) and activities(level 5 WBS) and in the risk control column detailedwith preventive actions and corrective actions for con-struction work.

ACKNOWLEDGEMENTS

The authors would like to thank the financial supportprovided by Universitas Indonesia through PITTAB funding scheme under grant number NKB –0803/UN2.R3.1/HKP.05.00/2019 managed by Direc-torate for Research and Public Services (DRPM) Uni-versitas Indonesia.

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west sumatera area. Indonesia. Internasional Journalon Advanced Science Engineering Information Tech-nology, Vol, 8(3):856–862.

Kausarian, H., Sumantyo, J. T. S., Putra, D. B. E., Suryadi,A., and Gevisioner. 2018. Image processing of alospalsar satellite data, small unmanned aerial vehicle(UAV), and field measurement of land deformation. In-ternational Journal of Advances in Intelligent Infor-matics, Vol, 4(2):132–141.

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Design of Web Login Security System using ElGamal Cryptography

Yudhi Arta, Hendra Pratama, Apri Siswanto, Abdul Syukur and Panji Rachmat SetiawanDepartment of Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

yudhiarta,aprisiswanto, abdulsyukur,[email protected], [email protected]

Keywords: Web Login, ElGamal, Cryptography.

Abstract: The login system is a process for accessing a computer by entering the identity of the user and the passwordto obtain permissions using the destination computer resources. In an information system security issues andmaintaining data confidentiality is one important aspect. However, these security issues often get less attentionfrom the owners and managers of information systems. If talking about security issues related to the use ofcomputers, it is difficult to separate it with the login process. Login aims to provide security services on thesystem. In this research used ElGamal cryptography algorithm to secure username and password in web login.The security level of this algorithm is based on the problem of discrete logarithms in the multiplication groupof prime modulo primes. This algorithm includes asymmetric cryptography algorithms that use two key types,namely public key and secret key. The data contained in the login is secured by using ElGamal algorithm, sothe username and password entered into the database are already in the form of ciphertext.

1 INTRODUCTION

The login system is the process of accessing a com-puter by entering the identity of the user and passwordto get access rights using the destination computer re-sources. When logging in to enter the system, the userwill be asked to enter a user identity such as user idand password in anticipation of system security. Pass-words can be changed according to needs while userid is never changed because it is a unique identity thatrefers to a particular user.

Information system on security issues and main-taining data confidentiality is one important aspect.But this security problem often gets less attentionfrom the owners and managers of information sys-tems (Arta et al., 2018). Security issues are secondor even last in the list of things that are consideredimportant(Arta, 2017; Novendra et al., 2018).

Internet users, usually using internet facilities tocarry out the process of changing information. Datasecurity is very important. The need for informationmakes website developers present a variety of ser-vices for users (Dharmawan et al., 2013). But mostof the website developers ignore system security onthe website. The most widely used attack by theseattackers is the SQL Injection attack. This study fo-cused on securing the system using the Rijndael algo-rithm to encrypt data (Minier, 2017). The Rijndael al-gorithm was chosen as a cryptographic algorithm that

can protect information well and efficiently in its im-plementation and was named the Advanced Encryp-tion Standard (Daemen and Rijmen, 1998; Daemenand Rijmen, 2013). This algorithm will be embed-ded in the system login to protect unauthorized ac-cess from the attacker (Dawood and Hammadi, 2017;Sajadieh et al., 2017). The results of using the Rijn-dael algorithm can protect the login system properlyso that the system is declared safe from the attackers(Kuo and Verbauwhede, 2001).

Computer network security is part of a system thatis very important to maintain data validity and in-tegrity and ensure availability of services for its users(Arta et al., 2016). The current network intruder de-tection system is generally able to detect various at-tacks but is unable to take further action. But on theone hand, hu-mans are very dependent on informationsystems. This has caused the statistics of network se-curity incidents to continue to increase sharply fromyear to year (Namjoshi and Narlikar, 2014; Waismanet al., 2007). This is due to the people’s lack of con-cern for network security systems. We need a sys-tem that can help network administrators to be usedas a network traffic monitor with Intrusion PreventionSystem (IPS) which is a combination of blocking ca-pabilities from Firewall (Giokas, 2016).

268Arta, Y., Pratama, H., Siswanto, A., Syukur, A. and Setiawan, P.Design of Web Login Security System using ElGamal Cryptography.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 268-273ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

2 ElGamal ENCRYPTION

The process of key formation is the process of deter-mining a number which will then be used as a keyin the process of encryption and decryption of mes-sages(Hashim, 2014). The key for encryption is gen-erated from the p value, g, y while the decryption keyconsists of the value x, p (Makkaoui et al., 2016).each value has requirements that must be met. Rarein making keys are as follows:• Primes p, with p values > 255.

• Select a random number g with the condition g <p.

• Select a random number x with the condition 1 <x < p-2.

• Calculate y = g * x mod p.The public key is y, g, p while the private key is

x. the value of y, g, and p is not save secret while thevalue of x must be kept secret because it is a privatekey to describe plaintext (Kiltz and Pietrzak, 2010;Tsiounis and Yung, 1998; Weinberger et al., 2006).


3.1 Username Encryption Process withElGamal Algorithm

In this section a comparison will be made betweenthe ElGamal login username and the standard loginon the web login system using ElGamal cryptography,the results of the comparison can be seen in table 1.

The process in table 1 above, is the result of theencryption process using the ElGamal method. Belowthis is the process of an ElGamal method at work.• If the testing system uses a username: 23081990,

Number of characters: 59, Uppercase: 0, Smallletters: 0, Numbers: 8, special character: 0, Other:15, Results: 8.81.

• If the testing system uses username: abcd1234,Number of characters: 58, Uppercase: 0, Smallletters: 4, Numbers: 8 special character: 0, Other:15, Result: 4,058.

• If the testing system uses username: AbCd1234,Number of characters: 56, Upper-case: 2, Smallletters: 2, Numbers: 4, special character: 0, Other:15, Result: 4,058.

• If the test system uses a username: Ac54$# h,Number of characters: 50, Uppercase: 1, Smallletter: 2, Numbers: 2, Special character: 2, Other:13, Result: 23,941.

• If the testing system uses a username: 6$ Ab788,Number of characters: 50, Uppercase: 1, Smallletter: 1, Number: 3, Special character: 1, Other:13, Result: 19.981.

• If the test system uses username: aaD#6754,Number of characters: 57, Uppercase: 1, Smallletter: 2, Number: 4, special character: 1, Other:15, Result: 4,995.

• If the testing system uses username: &*$# 9764,Number of characters: 59, Uppercase: 0, Smallletters: 0, Number: 4, Special character: 4, Other:15, Result: 9,313.

The process in table 2 above, is the result of theencryption process using the standart character. Be-low this is the process of standard login process test-ing

• If the test system uses a username: 23081990,Number of characters: 8, Large letters: 0, Lowercase letters: 0, Numbers: 8, character specials: 0,Other: 0 Result: 0.

• If the testing system uses username: abcd1234,Number of characters: 8, Large letters: 0, Lower-case letters: 4, Numbers: 8, Special characters: 0,Other: 0, Results: 0.13.

• If the testing system uses username: AbCd1234,Number of characters: 8, Large letters: 2, Lower-case letters: 2, Numbers: 4, Special characters: 0,Other: 0, Results: 0.13.

• If the testing system uses a username: Ac54$#h,Number of characters: 7, Large letters: 1, Lower-case: 2, numbers: 2, special character: 2, Other:0, Results: 0.5.

• If the testing system uses a username: 6$Ab788,Number of characters: 7, Large letters: 1, Lower-case: 1, Number: 3, Special characters: 1, Other:0, Result: 0.2.

• If the testing system uses username: aaD#6754,Number of characters: 8, Large letters: 1, Lower-case: 2, Number: 4, Special character: 1, Other:0, Results: 0.16.

• If the testing system uses username: &*$# 9764,Number of characters: 8 ,Large letters: 0, Lowercase letters: 0, Numbers: 4, special character: 4,Other: 0, Results: 0.31.

In table 1 and 2 above can be seen the comparisonbetween the ElGamal login username and the stan-dard login that has been done. Then the comparisonresults will be accumulated into a graph and can beseen in figure 1.

In Figure 1, the average time of the encryption anddecryption results of each username gets an ElGamal


269

Table 1: Username for ElGamal Login Testing.

ElGamalExam Username Char Encryp char(U) Char(L) Number Special(A) Other Result1 23081990 59 0 0 8 0 15 8.812 abcd1234 58 4 4 0 15 4.053 AbCd1234 56 2 2 4 0 15 4.054 Ac54$#h 50 2 1 2 2 13 23.95 6$Ab788 50 1 2 3 1 13 19.96 aaD#6754 57 1 2 4 1 15 4.997 &*$#9764 59 0 0 4 4 15 9.31

Table 2: Username for Standard Login Testing.

StandardExam Username Char Encryp char(U) Char(L) Number Special(A) Other Result1 23081990 8 0 8 0 02 abcd1234 8 4 4 0 0.133 AbCd1234 8 2 2 4 0 0.134 Ac54$#h 7 2 1 2 2 0 0.55 6$Ab788 7 1 2 3 1 0 0.26 aaD#6754 8 1 2 4 1 0 0.167 &*$#9764 8 0 0 4 4 0 0.31

Figure 1: Username Average (Second).

value: 27, 87 and standard: 0.2. Processing requiresa longer span of time than the standard username be-cause each process from ElGamal requires the inser-tion of a value before entering the username.

3.2 Password Encryption Process WithElGamal Algorithm

In this section a comparison will be made between theElGamal login password and the standard login on theweb login system using ElGamal cryptography, theresults of the comparison can be seen in table 3.

When a password is given a character using stan-dard letters, the time required does not take a longprocess of about 13 seconds. For ElGamal use usingASCII numbers, it will take quite a long time. Thecombination of standard letters and also ASCII num-bers is a safe step.

Password ElGamal Process Testing• If the testing system uses a username: kauy984,

number of characters: 51, uppercase: 3, lower-case: 1, number: 3, special characters: 0, other:13, Result: 16,235.

• If the test system uses username: abdx*&#, num-ber of characters: 53, uppercase: 2, lowercase: 2,numbers: 0, special characters: 3, other: 13, Re-sults: 53.99.

• If the testing system uses username: abcd1234,number of characters: 56, uppercase: 2, lower-case: 2, numbers: 4, character specials: 0, other:15, Results: 4,058.

• If the testing system uses a username: 65*&%k,number of characters: 53, uppercase: 0, lower-case: 1, number: 2, special characters :4, other:13, Results: 63,941.

• If the test system uses username: 6$ab788, num-ber of characters: 50, uppercase: 1, lowercase: 1,number: 3, special characters: 1, other: 13, re-sults: 19.981.

• If the test system uses username: aad#6754, num-ber of characters: 57, uppercase: 1, lowercase :2,number: 4, special characters: 1, other: 15, Re-sults: 4.995.

• If the test system uses username: &*$# 9764,number of characters: 59, uppercase: 0, lower-case: 0, number: 4, special characters: 4, other:15, Results: 9,313.


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Table 3: Password for ElGamal Login Testing.

ElGamalExam Password Char Encryp char(U) Char(L) Number Special(A) Other Result1 kAUY984 51 3 1 3 13 16.22 abDX*&# 53 2 2 0 3 15 53.93 AbCd1234 56 2 2 4 15 4.054 65*&ˆ%k 53 0 1 2 4 13 63.95 6$Ab788 50 1 2 3 1 13 19.96 aaD#6754 57 1 2 4 1 15 4.997 &*$#9764 59 0 0 4 4 15 9.31

The results from table 4 that use standard num-bers, are not much different from previous experi-ments. And for the average results of the above test is0.23 seconds.

Standart Password Process Testing• If the test system uses username: kauy984, num-

ber of characters: 7, uppercase letters: 4, lower-case letters: 0, numbers: 3, character specials: 0,other: 0, Results: 0.01.

• If the testing system uses username: abdx*&#,number of characters: 7, uppercase: 2, lowercase:2, numbers: 0, special characters: 3, other: 0, Re-sults: 0.44.

• If the test system uses username: abcd1234, num-ber of characters: 8, uppercase: 2, lowercase: 2,numbers: 4, special characters: 0, other: 0, Re-sults: 0.13.

• If the test system uses a username: 65*&*%k,number of characters: 7, uppercase: 0, lowercase:1, number: 2, special characters: 4, other: 0, re-sults: 0.4.

• If the testing system uses a username: 6$ ab788,number of characters: 8, uppercase: 1, lowercase:1, number: 3, special characters: 1, other: 0, Re-sult: 0.2.

• If the test system uses username: aad#6754, num-ber of characters: 8, uppercase: 1, lowercase: 2,number: 4, special characters: 1, other: 0, Result:0.16.

• If the test system uses username: &*$# 9764,number of characters: 8, uppercase letters: 0, low-ercase letters: 0, numbers: 4, character specials:4, other: 0, Results: 0.31.In table 2 above can be seen the comparison be-

tween the ElGamal login username and the standardlogin that has been done. Then the comparison resultswill be accumulated into a graph and can be seen infigure 2.

In Figure 2, it can be seen that the process of in-serting a value into a password takes time. This value

Figure 2: Password Average (Second).

is used for comparison when a password is to be testedif it is security, it will take a longer time than just us-ing a password that does not use ElGamal. This isa subjective assessment for a password security trial.for the average process of a password using the ElGa-mal method and ASCII numbers, it takes 24.64 sec-onds.

The following is the comparative result of calcu-lations based on ElGamal and Standard login. Toincrease the security of the username and passwordon the ElGamal encryption login, it should be addedto the length of the character, because the more thelength of characters, the more difficult the hackers in-tend to break into ElGamal encryption login system.The graph of these methods are shown in figure 3.

4 CONCLUSIONS

From the comparison test results above, it can be con-cluded that the level of security and average hourly forcomparison testing Elgamal login username: 10.73and for testing the comparison of standard login user-name: 0.20. Then for testing the comparison of Elga-mal login passwords: 24.64 and for testing the com-parison of standard login passwords: 0.23.


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Table 4: Password for Standart Login Testing.

StandardExam Password Char Encryp char(U) Char(L) Number Special(A) Other Result1 kAUY984 7 3 1 3 0 0.012 abDX*&# 7 2 2 0 3 0 0.443 AbCd1234 8 2 2 4 0 0.134 65*&ˆ%k 7 0 1 2 4 0 0.45 6$Ab788 7 1 2 3 1 0 0.26 aaD#6754 8 1 2 4 1 0 0.167 &*$#9764 8 0 0 4 4 0 0.31

Table 5: Comparison of Username Password.

USERNAME ElGamal Standard PASSWORD ElGamal Standard23081990 8.81 0 kAUY984 16.235 0.01abcd1234 4.058 0.13 abDX*&# 531.99 0.44

AbCd1234 4.058 0.13 AbCd1234 4.058 0.13Ac54$#h 63.941 0.5 65*&ˆ%k 63.941 0.46$Ab788 19.981 0.2 6$Ab788 19.981 0.2aaD#6754 4.995 0.16 aaD#6754 4.995 0.16&*$#9764 9.313 0.31 &*$#9764 9.313 0.31Average 10.73 0.20 Average 24.64 0.23

Figure 3: Graph Comparison ElGamal And Standard Login(a) Top and (b) bottom views.

ACKNOWLEDGEMENTS

We would like to express our gratitude to the Univer-sitas Islam Riau for the fund this project.

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Standard Operational Procedures Development for GovernmentBuilding’s Care and Maintenance Work of Outer Spatial and

Housekeeping Component to Improve Work Effectiveness and Efficiencyusing Risk-based Approach

Lasita Khaerani, Yusuf Latief and Rossy Armyn MachfudiyantoDepartment of Civil Engineering, Universitas Indonesia, Jakarta, Indonesia


Keywords: Standard operational procedures, care, maintenance, outer spatial, housekeeping, efficient, effective, duration

Abstract: The damage phenomenon that occurs in a building is something that is certain to happen considering that theolder the building is, the damage is something that cannot be denied. Regarding the damage, care and mainte-nance work is needed to maintain the condition of the building in order to remain feasible. Nevertheless, thereality in the field shows that the implementation of care and maintenance is often carried out in accordancewith the target because there is no clear implementation procedure. The purpose of this research is to de-velop procedures for care and maintenance work of outer spatial and housekeeping component in governmentbuilding. The risk in question is a risk that affects the duration of work activity. The objects in this studyare located in the DKI Jakarta Province, especially in the X’s Institution Government Building. The researchmethods used in this study are archival analysis, surveys, and case studies. The products produced in thisstudy are standard operating procedures for the care and maintenance work of outer spatial and housekeepingcomponent in government buildings to improve work efficiency and effectiveness.

1 INTRODUCTION

Today, the development of construction has acceler-ated rapidly and has encouraged various constructionof high-rise buildings, such as office buildings, hotels,shopping centers, hospitals, and others. Investmentin the construction sector is considered profitable andable to encourage economic growth that can be en-joyed by all levels of society. Based on informationfrom the Central Statistics Agency of DKI JakartaProvince, with an area of 661.5 km2 and a popula-tion of 5,244,690 people, developments in the con-struction sector were able to trigger economic growthbecause of the thousands of workers that constructionservices could absorb.

As a national capital city, in order to organize andsupport the performance of state governments, DKIJakarta has provided various buildings that have beenequipped with facilities and what’s in them to realizegood governance marked by the construction of gov-ernment buildings. According to Law Number 28 of2002, building is a physical form of construction workthat is integrated with its place of domicile, partiallyor wholly above and / or in land and / or water, which

functions as a place for humans to conduct their ac-tivities, whether for residential or residence, religiousactivities, business activities, social activities, culture,and special activities.

If functional buildings can still be used, risksin use can be minimized by care and maintenance.Maintenance of building is an activity to maintain thereliability of buildings and infrastructure and facilitiesso that building buildings remain functionally feasi-ble (Minister of Public Works of the Republic Indone-sia, 2008). Maintenance of building buildings aims tomaintain the buildings to reach the calculated age ofthe plan (Rosalina, 2011). Meanwhile, building main-tenance is an activity to repair and / or replace partsof buildings, components, building materials, infras-tructure and facilities so that buildings remain func-tionally feasible (Minister of Public Works of the Re-public Indonesia, 2008).

Based on Minister of Public Works RegulationNo.24 of 2008, there are several components in thebuilding, namely: architectural, structural, mechani-cal, electrical, outer space, and housekeeping. Thescope of maintenance work on the components ofouter space is the maintenance of conditions from

274Khaerani, L., Latief, Y. and Machfudiyanto, R.Standard Operational Procedures Development for Government Building’s Care and Maintenance Work of Outer Spatial and Housekeeping Component to Improve Work Effectiveness andEfficiency using Risk-based Approach.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 274-284ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

the surface of the land and / or the outer courtyardof buildings, maintenance of elements of landscapingoutside and inside the building, maintaining cleanli-ness outside buildings, gardens and the environment,as well as carrying out garden maintenance effortscorrectly by officers who are experts and competentin that field (Minister of Public Works of the Repub-lic Indonesia, 2008). In the housekeeping component,the scope of work covered are all housekeeping activ-ities such as cleaning service, landscape, pest control,and general cleaning, starting from preparatory, op-erational work, to the final work result (Minister ofPublic Works of the Republic Indonesia, 2008).

Phenomenon in the field shows that the many in-accessibility of the objectives of the care and main-tenance work of government buildings is a result oflack of efficiency and effectiveness in carrying outthese two things. According to the Indonesian Dic-tionary, one of the meanings of effective is to be use-ful. The purpose of success is to bring a result afterdoing a business. Meanwhile, some of the meaningsof the word efficient are precise and accurate, effi-cient, and effective (KBBI). This means that all ef-forts have been carried out correctly and accuratelywithout wasting time, energy, costs, and others.

Related to the previous explanation, to create aproper building maintenance work, a building mainte-nance work program is needed to achieve the plannedage of the building. However, the maintenance workprogram will not run well if it is not accompaniedby implementation procedures. Standard operationalprocedure of building’s care and maintenance work isan important matter to be prepared so that the imple-mentation of maintenance and maintenance activitiesare done according to procedures, well scheduled, andfacilitates workers in carrying out maintenance andmaintenance activities (Mohammad et al., 2014).

2 OBJECTIVE RESEARCH

The objective of study is:

• Identifying the state of existing organizations ingovernment buildings in carrying out care andmaintenance work on government buildings (RQ1).

• Identify tasks, responsibilities, and roles of re-sources for implementing government buildingcare and maintenance work (RQ 2).

• Develop business processes related to the care andmaintenance work of the outer spatial and house-keeping component of government buildings (RQ3).

• Determine the length of duration needed for careand maintenance work of the outer spatial andhousekeeping component of government build-ings (RQ 4).

• Establish input and output from each activity ofmaintenance work and care of components of theouter spatial plan and governance of governmentbuildings (RQ 5).

• Identify the risks that may occur from each careand maintenance activity of the outer spatial andhousekeeping component of government build-ings (RQ 6)

• Develop communication flow in the process ofcarrying out care and maintenance work of theouter spatial and housekeeping component of gov-ernment buildings (RQ 7).

• Develop standard operating procedures for thecare and maintenance work of the outer spa-tial and housekeeping component in governmentbuildings using risk-based approach (RQ 8).

3 LITERATURE STUDIES

3.1 SOP for Building Care andMaintenance of GovernmentBuilding

Standard operational procedure is a series of writteninstructions standardized on various processes for or-ganizing organizational activities, how and when todo, where and by whom is carried out (Minister ofAdministrative Reform and Bureaucratic Reform ofthe Republic Indonesia, 2012). Based on the Guide-lines for the Preparation of Operational Standardsin Government Administration Procedures within theSecretariat General and the Expertise Board of thePeople’s Representative Council of the Republic ofIndonesia (Representative Council of The Republic ofIndonesia, 2016), the standard operating procedure isa standardized written instruction on the implementa-tion of the tasks and functions of the General Secre-tariat and DPR RI BK.

According to the Regulation of the Minister ofAdministrative Reform and Bureaucratic Reform ofthe Republic of Indonesia No. 35 of 2012 (Ministerof Administrative Reform and Bureaucratic Reformof the Republic Indonesia, 2012), there are 2 elementsof standard operating procedures, namely:

• Identity Section This section contains logos, SOPnumbers, manufacturing dates, revision dates, ef-fective dates from the entry into force of SOPs,

Standard Operational Procedures Development for Government Building’s Care and Maintenance Work of Outer Spatial and HousekeepingComponent to Improve Work Effectiveness and Efficiency using Risk-based Approach

275

endorsement by competent officials, titles, legalbasis, linkages, warnings, implementing qualifi-cations, equipment and equipment, and recordingand data collection.

• Flowchart Flowchart is a description of thesteps in sequence of the standardized procedure.Flowchart contained in the SOP document com-munication flow is described with 5 symbols thathave different function which is illustrated in fig-ure 1, 2, 3, 4, and 5, they are:

– Capsule / Terminator Symbol

Figure 1: Capsule Symbol

Function: describes the start and completion ofactivities

– Box Symbol / Process

Figure 2: Box Symbol

Function: describes the execution process oractivity

– Rhombus Symbol / Decision

Figure 3: Rhombus Symbol

Function: describes decision making activities– Arrow Symbol / Arrow

Figure 4: Arrow Symbol

Function: describe the direction of the activityprocess

– Pentagon Symbol / Off-Page ConnectorFunction: describes the relationship betweendifferent symbol pages

3.2 Business Process

According to the Minister of Research, Technologyand Education Regulation of the Republic of Indone-

Figure 5: Arrow Symbol

sia No. 71 of 2017 (Minister of Research, Technol-ogy, and Education of the Republic Indonesia, 2017),business processes or governance is a set of structuredand interrelated work activities that produce outputaccording to user needs. In addition, (Paul, 2003) de-fines business processes as a series of activities car-ried out by a business from the initiation of input toproduce a number of output. Business process is akey element in ensuring that activities are executedin line with specified requirements (Machfudiyantoet al., 2018).

The purpose of mapping and management (busi-ness process) analysis is to see in full the whole setof processes that affect the work and achievementsof the organization in serving key external and inter-nal stakeholders (Minister of Administrative Reformand Bureaucratic Reform of the Republic Indonesia,2011).

The stages of mapping business processes accord-ing to the Regulation of the Minister of Administra-tive Reform and Bureaucratic Reform of the Republicof Indonesia No. 12 of 2011, are:

• Understanding the organization’s strategic direc-tion (vision, mission, tasks, and organizationalfunctions).

• Identifying management (business processes) tobe mapped based on needs analysis.

• Identifying the name and type of management(business process) in question.

• Determining who are the main users or users ofthe management (business process) in question.

• Describing the sequence of activities that form themanagement chain (business process) in question.

• Determining the main input of management (busi-ness process) in question.

• Determining the main management (business pro-cess) output in question.

• Specifying the owner (owner) the management(business process) in question.


276

3.3 Assignment Matrix (RAM / RACI)

RAM is a matrix that serves to show the resourcesassigned to each work package. RAM describes theresponsibilities of the project team, group, or unit ofeach component of work that exists (Institute, 2016).One example of RAM is RACI which is shown intable 1. RACI means responsible (executor), assign(person in charge), consult (advisor), and inform (in-formed).

Table 1: Example of RAM / RACI Matrix

ActivitiesResponsible Agency

Cisa Lisa Fisa Risa Tisa1 R C I I I

2 A R C I I

3 I A R C I

4 I C A R I

The sample matrix above shows the work thatmust be done in the left column and who is respon-sible for the work in the column to the right of theactivity column using RACI.

3.4 Risk Management

Risk is a potential event that can be avoided or re-duced as small as possible to minimize the impact ac-cording to planning or permissible tolerance limits tothe intended target (Asiyanto, 2009). According to(Institute, 2016), one method for analyzing risk is touse qualitative risk analysis. Qualitative analysis isa step to prioritize risk based on the possibility andimpact of risk. This study uses qualitative risk analy-sis that refers to PMBOK to make a risk-related study.The risk management process carried out in this studyis risk identification, qualitative risk analysis, and riskresponse preparation.

4 METHODOLOGY

The object of this research is the buildings inside TheHouse of Representatives of the Republic of Indone-sia (DPR RI) Complex. There are six buildings therewith Nusantara as the main building. Nusantara build-ing consists of a plenary meeting hall with 1700 seat-ing. The other five buildings are used as the office andmeetings rooms.

This research was conducted to answer the re-search objectives by using 3 research strategies,

Figure 6: Research Process Flowchart

namely: survey, archive analysis, and case study. Theflow of research conducted is illustrated in figure 6.

At the end of this study, the products are stan-dard operating procedures for the care and mainte-nance work of the outer spatial and housekeepingcomponent in government buildings using risk-basedapproach. Risks reviewed are occupational risks thataffect the duration because of the duration of the rela-tion to efficiency and effectiveness of work. With thedevelopment of standard operating procedures for thecare and maintenance work of the outer spatial andhousekeeping component, it is expected that care andmaintenance work can be carried out well.


5.1 For Answering RQ 1 and RQ 2

5.1.1 Form of Organization Structure and JobDescription There Is Institution XGovernment Building

In the first stage of data collection process, the au-thor gave questionnaires to the three experts to be ver-ified, clarified and validated. Experts validate the or-ganizational structure and the distribution of job de-scriptions by referring to the applicable regulations in


277

the Secretariat General and the The House of Repre-sentatives of the Republic of Indonesia (DPR RI) Ex-pertise Agency. Those experts are the Head of StateProperty Management Bureau of Institution X, theHead of Building and Garden Division of InstitutionX, and the Project Manager of Procedure from a na-tion owned company. These three experts are the oneswho did all the validation needed for this research.

Based on the results of processing the first stageof data collection taking into account the recommen-dations of experts, the authors made several adjust-ments to the existing form of organizational structurebecause of the inequality of responsibilities betweenone position and another. The previous organizationalstructure and the results of developing a new organi-zational structure are illustrated in figure 7 and 8:

State Property Management Bureau

Administration Division

Planning & Utilization

Administration

Reporting

Building and Installation

Building and Garden

Mechanical

Electrical

Houses Management Division

Kalibata Houses

BoD & Ulujami Hoses

Guest House Management

Guest House Maintenance

Guest House Service

Figure 7: Organizational Chart Before Development

State Property Management Bureau

Administration Division

Building and Installation

Building

Garden

Installation Division

Mechanical

Electrical

Housing & Guest House Management

Housing Maintenance

Guest House Service

Figure 8: Organizational Chart After Development

5.2 For Answering RQ 3, 4 and 5

5.2.1 Business Processes, Duration, and Inputsand Outputs Activities for Maintenanceand Maintenance of Outer SpatialComponents and Governance ofGovernment Buildings

The second stage of the data collection process is todetermine the technical procedures for the care andmaintenance work of government buildings. This

stage begins with the collection of business pro-cesses, activities, output, input, and the duration of thecare and maintenance work on government buildingsthrough literature studies and followed by validationon experts.

Based on the literature study, 12 components ofbuilding space and 26 components of building struc-ture in the building were found. After being verified,clarified, and validated by experts, we found a reduc-tion of 7 outer spatial components and the addition of4 components of housekeeping component, so that thefinal total components produced by this study were7 components of outer spatial and 30 components ofhousekeeping.

There are several activities in each component ofcare and maintenance work. The activity is then sup-plemented with input, output, and duration of imple-mentation in the form of documents. The example ofthe details of each component that includes the activ-ity, input, output, and the duration will be given at thesame time as the SOP product discussed in the nextdiscussion.

5.3 For Answering RQ 7

5.3.1 Communication Flow

The third stage of the data collection process is tomap the communication flow by defining the personin charge and executor of each activity in each busi-ness process.

After getting the organizational form, businessprocess, duration, input and output from the activitiesin the work and maintenance of the outer spatial andhousekeeping component of government buildings,the author makes communication flows that show therelationship between activities that need to be done byparties involved with the activity.

In the outer spatial component, there are sevencare communication flow charts and nine mainte-nance communication flow charts. Whereas in thehousekeeping component, there are thirty mainte-nance communication flowcharts and no care commu-nication flowcharts.

The communication flow chart is made by refer-ring to the results of data analysis in stage three whichis collected using the RAM / RACI method. TheRAM / RACI method is used to define the personin charge of each activity. The communication flowchart serves as an instrument that is useful for show-ing those responsible (responsible) for an activity ineach business process.

Figure 9 is an example of the development of acommunication flowchart in one of the care and main-


278

tenance work for the outer spatial and housekeepingcomponent that are part of the SOP.


5.4.1 Risk Identification

The fourth stage of data collection process is carriedout to identify the risks of each activity in each busi-ness process by conducting a literature study and pro-ceeding with the validation of the experts. Based onthe results of risk identification with a literature study,there were 43 risks related to the duration of work thatcould affect work efficiency and effectiveness.

After being verified, clarified, and validated by ex-perts, 24 additional risks were obtained so that the to-tal risk in the building maintenance and maintenancework became 67 risks.

5.4.2 Risk Assessment (Qualitative RiskAnalysis)

The previously identified risks are then assessed forfrequency and impact through the fifth stage of datacollection carried out with the survey method of re-spondents beginning with the pilot survey to deter-mine whether all identified risks are understood.

The stages of risk analysis are carried out by re-ferring to PMBOK 6th Edition as a guideline. Qual-itative risk analysis is carried out by multiplying theweighting results of the frequency and impact level,then categorizing the results of the values accordingto the risk criteria. The scale of frequency, impact,and risk weighting used in this study are displayed intable 2, 3, 4, and 5. They are:

Table 2: Scale Rating Frequency

Scale FrequencyLevel

Remarks

1 Rarely(rare)

Chance of occuringis small and onlyoccur under certainconditions

2 Few possibili-ties (unlikely)

Can occur in acondition

3 Maybe (possi-ble)

Can occur occasionally

4 Frequent(likely)

It may occur in manycircumstances

5 Almost certain(almost certain)

Estimated to occur inmany circumstances

Based on the results of data processing using riskqualitative analysis, 2 variables of the 67 variablestested were considered high level risk. According

Table 3: Scale Rating Impact

Scale ImpactRate

Remarks

1 Not sig-nificant(Insignifi-cant)

Does not cause financiallosses and delays

2 Small Does not cause financiallosses and cause delays ofless than 1 day

3 Moderate Cause moderate financiallosses and cause delays ofless than 1 day

4 Severe A mild-moderate financialloss and a delay of morethan 1 day

5 Disastrous A high financial loss and adelay of more than 1 day

Table 4: Weighting frequency and impact

Value Criteria F Weight F Criteria D Weight D1 Very Low 0,1 No effect 0,05

2 Low 0,3 Less influen-tial

0,1

3 Moderate 0,5 Pretty Influ-ential

0,2

4 High 0,7 Influential 0,4

5 Very High 0,9 Very influen-tial

0,8

Table 5: Risk Category

Risk Score Risk Category (FR)0,18 – 0,72 High Risk

0,06 – 0,17 Moderate Risk

0,01 – 0,05 Low Risk

to (Tan, 2011), it takes at least 10% of the variablesample to conduct a further review of a research vari-able. Therefore, the researcher took 7 risk eventsfrom 67 variables to be followed up. The seven riskevents consist of 2 high level risks and 5 medium levelrisks. Those high risk activity in the procedure forcare and maintenance and maintenance of outer spa-tial and housekeeping components of the governmentbuildings are displayed in table 6.

5.4.3 Causes and Effects of Risk

The sixth stage of data collection is carried out toidentify the causes, impacts, and risk responses tohigh-risk activities. This process is carried out usingliterature studies followed by validation on experts.As for the causes of the risk is displayed in table 7and the impact of the risk in table 8.


279

No Activities

Implementation

Input Output Duration Remarks

Head of State

Property

Commitment Officer

Head of Building and

Garden

Head of Building

Subdivision

Civil Working Group

Third

Party

Work Inspecto

r

1

Provide a schedule or

work instructions /

repairs.

Disposition

Maintenance Work

Schedule and

Instructions

1 day Done as soon as

possible.

2

Making RKS Implementatio

n of Maintenance

Works

Maintenance Work

Schedule and Instructions

RKS Concept

Maintenance Work

1 month

3

Making HPS Maintenance

Work Implementatio

n

Maintenance Work


HPS Maintenanc

e Work Concept

1 month

4

Submitting RKS for

Implementation of

Maintenance Works

RKS Concept Maintenance

Work

RKS Maintenanc

e Work 1 month

5

Submitting HPS

Maintenance Works

HPS

Maintenance Work Concept

HPS Maintenanc

e Work 1 month

6

Inform maintenance

schedule in the relevant ranks.

Maintenance

Work Schedule

Schedule Submission

Report 1 day

Done as soon as

possible.

7 Prepare work equipment.

Maintenance Work


Form checklist complete

tools

1 day

Work equipment

prepared by Building

Management is limited to standard

routine work

equipment.

8

Check Uniform and Identification Completeness.

Schedule and List of Officer

Names

Form checklist

completeness officer

1 day

9 Conduct periodic checks.

Maintenance

Work Schedule and Instructions

Form check list work 1 day

10 Check the zinc

cover listplank.

1 day

11

Clean the surface of GRC with

emery no.2.

1 day

12 Re-paint with

emulsion paint.

Form check list previous

work

Form check list work 1 day

13

Check the results of

maintenance work.

Form checklist work

Maintenance Work Report

1 day

14

Report the results of

maintenance work.

Maintenance Work Report, Activity Documentation, Report Progress 0%, 50%, and 100%

BA Submission

of Job Reports

1 day

NO

NO

YES

YES

Figure 9: GRC Maintenance List Communication Flowchart


280

Table 6: High Risk Activities

Activities Code Risk Potential RiskLevel

Submitting Technical Proposals and Mainte-nance Schedule.

X8 There are changes in conditions on theground that affect job demand.

High Risk


X7 Additional work / change in job demand Moderate

Making HPS Maintenance Work Implemen-tation

X13 The incompatibility of specifications is deter-mined by the conditions in the field

Moderate


X11 Calculation error Moderate


X12 Error determining specifications in makingHPS

Moderate

Provide schedules or maintenance work in-structions

X2 Unclear work instructions Moderate


X5 Lack of workforce expertise Moderate

Table 7: Causes of Risk for Duration

Code CauseP1 Incorrect design information

P2 Investigation of imperfect locations

P3 Bad communication

P4 Imperfect administration of contracts

P5 Uncontrolled external events

P6 Incomplete contract information

P7 Lack of coordination

P8 List of ingredients prices is not appropriate

P9 There is a new government policy

P10 Error math operations when counting

P11 typing / inputting data error

P12 Fatigue conditions when calculating RABP13 Job drawing errors as a guideline for

calculationsP14 Deliberately creating confusion for the

benefit of specific groupsP15 Poor ability to present instructions

(communication)

P16 Instructions are not well prepared

P17 Low education level

P18 Not Certified

P19 Not experienced

5.4.4 Risk Response

Based on literature studies and validation by experts,it can be concluded that there are 14 preventive ac-tions and 10 corrective actions that are shown in ta-

Table 8: Impact of Risk on Duration

Code EffectD1 Work late

D2 Change of fees

D3 Work cannot be carried outD4 There was a change after the technical doc-

ument and the file was createdD5 Late notice regarding changes in

conditions

D6 Price is not up to date

D7 There is a policy misuse

D8 Inaccurate calculations

D9 Invalid data

D10 RAB is wrongD11 There is a deviation from the calculation

made

D12 Harm certain parties

D13 Inaccurate HPS

D14 Instructions cannot be understoodD15 It is not appropriate to determine the tech-

nical proposalD16 It is not appropriate to determine the

schedule for carrying out the work

ble 9.


281

Table 9: Preventive Action

Code Preventive ActionTP 1 Check conditions in the field

TP 2 Hold a coordination meeting routinely

TP 3 Providing communication training

TP 4 Check specifications used on HPS

TP 5 Update price lists regularly

TP 6 Adjust to changesTP 7 Make gradual corrections when doing

calculations

TP 8 Stop working before getting tiredTP 9 Ensure that the image to be calculated has

been approved.

TP10

Supervise in calculations

TP11

Establish minimum competency standardsfor instructors

TP12

Checking education background

TP13

Check worker certification

TP14

Check worker experience

Table 10: Corrective action

Code Corrective actionTK 1 Review

TK 2 rework

TK 3 Hold a coordination meeting

TK 4 Aligning communication disagreements

TK 5 RecalculationTK 6 Addendum to work contract / work

instruction

TK 7 There is a calculation adjustment

TK 8 Changes

TK 9 Certification

TK 10 Training


5.5.1 Risk-based SOP Development

Based on the results of the collection of risk responsesin the previous discussion, the authors carried out

the development of communication flowcharts for thecare and maintenance work of the outer spatial andhousekeeping components which are part of the SOPby adding risk control activities.

Of the overall preventive actions and correctiveactions that have been collected, several supervisoryactions are chosen to be used as additional activities.The results of the identification of risk responses thatare used as additional activities in care and mainte-nance work are:

• Ensure that the image to be calculated has beenapproved.

• Check specifications used on HPS

• Judicial review

• Check conditions in the field

• Hold a coordination meeting

Given that all high-risk activities are classifiedas administrative activities, additional activities willalways be the same and are located at the beginningof the work process. Apart from administrativeactivities, there is no additional activity and the SOPremains the same. Figure 10 shows an example ofdeveloped SOP.

6 CONCLUSION

Based on the research that has been done, there areseveral things that can be concluded.

First, it is necessary to adjust the organizationalstructure of the Institution’s X State Property Man-agement Bureau because of work imbalances in cer-tain parts / sub-sections.

Second, adjustment of job description is requiredin the Institution’s X State Property Management Bu-reau following the adjustment of the organizationalstructure.

Third, there are 7 business processes in the outerspace component and 30 business processes in thehousekeeping component of the care and maintenancework of government buildings.

Forth, the duration of each activity in each busi-ness process varies according to the level of difficultyof each activity.

Fifth, inputs and output in each activity studied aredocuments that are needed and produced when start-ing and completing work.

Sixth, there are 67 risks that affect the durationof all activities in the care and maintenance work ofgovernment buildings.


282

No Activities

Implementation

Input Output Duration Remarks Head of State

Property Commitment

Officer

Head of Building

and Garden

Head of Building

Subdivision

Civil Working Group

Third Party

Work Inspector

1

Provide a schedule or

work instructions /

repairs.

Disposition

Maintenance Work

Schedule and

Instructions

1 day Done as soon as

possible.

2

Making RKS Implementation of Maintenance

Works

Maintenance Work

Schedule and

Instructions

RKS Concept

Maintenance Work

1 month

3

Ensure that the image to be calculated

has been approved.

4 Check

specifications used on HPS

5

Making HPS Maintenance

Work Implementation

Maintenance Work

Schedule and

Instructions

HPS Maintenance

Work Concept

1 month

6 Review

7

Submitting RKS for

Implementation of Maintenance

Works

RKS Concept

Maintenance Work

RKS Maintenance

Work 1 month

NO

YES

NO

YES

NO

YES

Figure 10: Risk Based SOP

Seventh, There are 7 communication flowchartsfor the outer spatial component and 30 communi-cation flowcharts for the housekeeping componentin the government building’s care and maintenancework.

Lastly, in developing SOP for care and mainte-nance work in government building, the authors usethe integration result of adjusted organizational struc-ture and job description in Institution’s X State Prop-erty Management Bureau to delegate the responsibil-ities of each activity in each of the business processesobtained. The SOP is presented in the form of docu-ment communication flow. Activities in each businessprocess are added with risk prevention activities to an-ticipate the risks that might occur. The risk preventionactivities are obtained from the risk identification pro-cess that has been carried out previously.

ACKNOWLEDGMENTS

The authors would like to thank the financial supportprovided by Universitas Indonesia through PITTAB funding scheme under grant number NKB –0803/UN2.R3.1/HKP.05.00/2019 managed by Direc-torate for Research and Public Services (DRPM) Uni-versitas Indonesia.

REFERENCES

Asiyanto (2009). Risk Management for Contractors. PradyaParamita, Jakarta.

Institute, P. M. (2016). Project Management Book ofKnowledge (PMBOK GUIDE) 6th Edition. PMI In-donesia Chapter, Jakarta.

Machfudiyanto, R. A., Latief, Y., Soepandji, B. S., and Pu-tri, P. A. (2018). Improving business processes to de-velop standard operation procedures on governmentbuilding maintenance work in indonesia. In MATECWeb of Conferences, volume 195, page 06006. EDPSciences.

Minister of Administrative Reform and Bureaucratic Re-form of the Republic Indonesia (2011). Regulationfrom Minister of Administrative Reform and Bureau-cratic Reform of the Republic Indonesia No.12 of2011.

Minister of Administrative Reform and Bureaucratic Re-form of the Republic Indonesia (2012). Regulationfrom Minister of Administrative Reform and Bureau-cratic Reform of the Republic Indonesia No.35 of2012.

Minister of Public Works of the Republic Indonesia (2008).Regulation from Minister of Public Works of the Re-public Indonesia No.24 of 2008.

Minister of Research, Technology, and Education of the Re-public Indonesia (2017). Regulation from Minister ofResearch, Technology and Education of The Republicof Indonesia No. 71 of 2017.


283

Mohammad, A., Resty, A., Marsudi, and Martono (2014).Maintenance Management Model for Building Archi-tectural. Semarang State Polytechnics, Semarang.

Paul, H. (2003). The Evolution of Business Process Man-agement. DCI BPM, New Orelans.

Representative Council of The Republic of Indonesia(2016). Guidelines for the Preparation of Opera-tional Standards in Government Administration Pro-cedures within the Secretariat General and the Exper-tise Board of the People’s Representative Council ofthe Republic Indonesia.

Rosalina (2011). Building Maintenance System JudgingFrom the Reliability of Buildings (Case Study: SimpleRental Flats in Cilangkap Regency). Sebelas MaretUniversity, Surakarta.

Tan, D. W. (2011). Project finance in construction: A struc-tured guide to assessment. Construction Managementand Economics, 29(10):1074–1075.


284

A Novel Correlation on MMP Prediction in CO2-LPG Injection System:A Case Study of Field X in Indonesia

Prasandi Abdul Aziz, Hendra Dwimax, Tutuka Ariadji, Steven Chandra, Wijoyo Niti Daton, RessiBonti

Petroleum Engineering Program, Institut Teknologi Bandung, Bandung, Indonesiawndaton, ezra, siptian, paa, ta, steven, [email protected]

Keywords: Minimum Miscibility Pressure, Slimtube Experiment.

Abstract: In order to increase Indonesia’s petroleum production, which mostly comes from the marginal field, an En-hanced Oil Recovery (EOR) method is needed. One EOR method that is proven to be able to increase large oilyield is mixed CO2 injection. In implementing EOR CO2 injection mixed, the Minimum Reliability Pressure(MMP) value is the key to success. One of the problems faced by oil fields in Indonesia in carrying out EOR ofmixed CO2 injection is that the reservoir pressure has dropped due to old age making it difficult to inject withMMP pressure above the reservoir pressure. The solution that can be done to overcome this is by reducing theMMP value using Liquified Petroleum Gas (LPG).This study will determine the optimal method of LPG useto reduce CO2 injection MMP values from Field X fluid in South Sumatra. Then, the MMP value in variousconditions will be determined using a slimtube simulation which will be used to make a correlation to deter-mine the MMP value. From the results of the study, in principle mixing LPG with CO2 will reduce the MMPvalue optimally. In addition, the average MMP value dropped by 29.5% with an increase in the compositionof LPG in the gas mixture of CO2 - LPG injection by 30%, the MMP value increased by 23% with a changein hexane plus molecular weight of 27.5% higher than before, and the MMP value increased by an average of13.4% with an increase in temperature of 20%.The resulting correlation is formed using parameters that havea significant influence on the determination of the MMP value. The resulting correlation has R-Squared of98.65%. The correlation is then tested with MMP values previously determined through a slimtube simulationand produces an Average Absolute Relative Error (AARE) value of 4.52%. Correlation was then re-testedagainst the correlations of other MMP determinations using 9 fluid MMP data from other literature. The resultis the proposed correlation produces an AARE value of 10.82%.

1 INTRODUCTION

Production of crude oil and condensate in Indonesiais 803,000 barrels per day in 2017 (Statistics of theMinistry of Energy and Mineral Resources). Mean-while, Indonesia’s national oil consumption currentlyreaches 1.6 million barrels per day and continues toincrease (Statistical Review of World Energy 2017BP). This means that crude oil production in Indone-sia is smaller than consumption of petroleum as an en-ergy source. In addition, Indonesia’s petroleum pro-duction has experienced a downward trend of 1.35%every year since 2012 (Statistics of the Ministry ofEnergy and Mineral Resources). Indonesia needs tomake breakthroughs in order to increase its petroleumproduction.

One such breakthrough is Enhanced Oil Recov-ery (EOR). The breakthrough is a step to increase oil

acquisition if a field has gone through the primary re-covery stage, which is the stage where the reservoirfluid can flow by itself; and the secondary recoverystage, which is the stage where the field is injectedwith gas or water to maintain pressure in the reservoirso that it does not drop dramatically (Lake, 1989).EOR is the third step or tertiary recovery.

One type of EOR method that is quite well knownis CO2 injection. CO2 injection is still rarely used infields in Indonesia. There are 2 mechanisms for CO2injection, namely: miscible injection (mixed injec-tion) and immiscible injection (injection not mixed).From the literature study conducted, it is known thatmiscible injection produces oil that is greater than im-miscible injection. This also underlies the researchfocus on the miscible CO2 injection mechanism.

In performing miscible CO2 injection, the Mini-mum Miscibility Pressure (MMP) value is very im-

Aziz, P., Dwimax, H., Ariadji, T., Chandra, S., Daton, W. and Bonti, R.A Novel Correlation on MMP Prediction in CO2-LPG Injection System: A Case Study of Field X in Indonesia.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 285-290ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

285

portant to know. MMP is the minimum pressure sothat the reservoir fluid and injection fluid can mix.Unfortunately, the value for miscible CO2 injection isquite high considering the reservoir pressure has dras-tically reduced because of the primary and secondaryproduction stages. As a result, the injected CO2 can-not mix with the oil in the reservoir and the miscibleCO2 injection mechanism can be considered a failure.

There are two methods for this problem, namely:

• Injecting another gas into the reservoir so that theintermediate component (C2-C6) of hydrocarbonsin the reservoir increases before injecting CO2, or

• Mixing the other gases with CO2 gas on the sur-face then inject the mixed gas into the reservoir.Both of these methods are carried out so that theMMP value of the reservoir fluid against CO2 candecrease and the fluid can mix at the current reser-voir pressure.

The mixed gas is generally a hydrocarbon intermedi-ate component such as propane and butane. It wasalso known that the biggest decrease in MMP was inmixing between CO2 and butane with a ratio of 40:60(Muslim dan Permadi, 2016; Permadi, 2014; Rom-merskirchen and Nijssen, 2016). In this study, the gasused as a mixture of CO2 to be injected is LPG, as-suming the main constituent is propane.

Field X in South Sumatra is one field that has beenoperating since 1987. The field includes the old fieldcategory (brownfield). The Feasibility Study (FS)conducted by the Bandung Institute of Technology(ITB) team on Field X showed that the EOR methodthat was right for the field was CO2-EC miscible sothat the value of MMP was needed. Fluid data fromField X was obtained from reservoir and fluid descrip-tion data in the Final Report of Feasibility of Field Xin 2009. This study will try to determine CO2 in-jection MMP from Field X fluid in various conditionsusing a mixture of LPG on gas injection. The ultimategoal of this study is to form a correlation that can beused to determine the value of MMP injection of pureCO2 or CO2 - LPG on Field X and compare it withother correlations that have been formed.

2 ANALYSIS ON MINIMUMMISCIBILITY PRESSURE

Minimum Miscibility Pressure (MMP) is the low-est pressure for a gas to be mixed through a multi-contact process with reservoir oil at reservoir tem-perature (Elsharkawy, ). MMP can actually be di-vided into two, namely multiple contact miscibility

pressure (MCMP) and first-contact miscibility pres-sure (FCMP). The MCMP value must be below theFCMP value (Holm, 1987; Martin and Taber, 1992).However, as explained earlier, MMP in this study usesMCMP as the definition of MMP. This is because mis-cibility for EOR can be achieved at pressures belowFCMP and above MCMP (Zhang et al., 2004). Thereare several definitions of MMP CO2 injection mathe-matically, namely:• Pressure when oil is equal to or very close to the

maximum final gain when 1.2 pore volume (PV)is injected (Yellig et al., 1980).

• Pressure which causes oil acquisition as much as80% in CO2 breakthrough and oil yield of 94%at gas to oil ratio of 40000 SCF / stb (Holm andJosendal, 1974).

• Pressure that causes oil recovery of 90% or moreat CO2 injection of 1.2 PV (Glaso, 1985).

In this study, Glaso’s definition was used to determineMMP using a slimtube simulation. Some parametersthat affect the MMP value are as follows.• Reservoir temperature. An increase in reservoir

temperature will increase the MMP value.

• Oil composition. The higher the composition ofthe intermediate component C2 - C6 and the lowerthe composition of the heavy component of oil,the lower the MMP value.

• Gas injection composition. The higher the com-position of the intermediate component C2 - C6gas injection, the lower the MMP value. (Zhanget al., 2015).These parameters will be used as the main param-

eter to perform sensitivity and correlation formation.

MMP Correlation and LPG Injection. There areseveral determinants of the MMP value of injectionof pure CO2 that has been previously formed. Thecorrelation used as a comparison in this study is thecorrelation of Cronquist, Lee, Yelling-Metcalfe, Orr-Jensen, Alston, Emera-Sarma, Yuan, Shokir, Chen,Ju, and Hao Zhang (Ju et al., 2012; Al-Hinai et al.,2014; Bayagub, 2017; Bon and Sarma, 2005).

Gas injection of Liquified Petroleum Gas (LPG)has a lower MMP value than the MMP value for CO2.The use of LPG in EOR is relatively more benefi-cial than the use of other light hydrocarbons (Ortega,2017). According to a study conducted by Holm,CO2 injection can have oil yield of up to 75% whileby using LPG, oil yield can reach 95%.

LPG injection will help develop oil volume, re-duce oil density, and reduce oil viscosity. In addition,LPG moves residual oil that is spread in the reservoir


286

(Bayat, 2015). Even so, LPG costs have an expen-sive price. With these conditions, it is necessary tomix CO2 with LPG so that the obtained oil is higherand the price is economical (Kumar and Von Gonten,1973). The LPG used in this study was propane(C3H8).

Slim Tube Injection Process. Slimtube simulationin IPM - PVTP vers software. 9.5 is used to determinethe MMP value in various field conditions of X. Thesimulation of the slimtube is used because the use ofthe slimtube in the laboratory will take a very longtime and the costs are not cheap. Slimtube modeledin this simulation has 10 cells, where each cell has asize of 2.3727 ft in the x-direction, 0.0113686 ft in they-direction, and 0.0113686 ft in the z-direction. Theporosity used for the slimtube model is taken from theaverage porosity of Field X, which is 0.16275. Thepermeability of the slimtube model is also taken fromthe average permeability of Field X, which is equalto 63.5 mD. The Field X reservoir depth becomes theslimtube depth input data, which is 6490 ft. To de-termine the MMP value, the Slimtube simulation re-quires a definition for the MMP value. As mentionedin the previous chapter, the MMP value is the pressureat which 90% or more oil has been obtained when in-jecting a gas of 1.2 pore volume into the slimtube.The results of the slimtube simulation to determineMMP under certain conditions will be displayed inthe graph of recovery vs pore volume. An exampleof the MMP determination can be seen in Figure 1.Before determining the MMP value in various con-ditions, it is necessary to validate whether the fluidmodel to be simulated on the Slimtube in the PVTPsoftware has the same MMP value as the fluid MMPwhen tested with a slimtube in the laboratory. Thefield X MMP oil value on the slimtube test from thelaboratory test was 2820 psi. In the slimtube simula-tion for this validation, the CO2 injection MMP valuewas 2870 psi. An error of 50 psi or 1.77% is con-sidered to be tolerable and the determination of MMPusing a slimtube simulation and the fluid model in thisPVTP can be started.

To do a slimtube simulation, gas injection isneeded. In this study, there are 2 methods to be tested,namely injection of LPG first into the reservoir fluidand then injecting CO2 and injection of a mixture ofCO2 and LPG into the reservoir fluid.

For the first method, the reservoir fluid will be in-jected with LPG by comparison as follows.

• 95% reservoir fluid and 5% LPG



Figure 1: Example of Slimtube Simulation.


Next, the value of MMP is determined by the secondmethod. The injection gas used is as follows.

• 100% CO2

• 70% CO2 and 30% LPG

• 60% CO2 and 40% LPG

• 50% CO2 and 50% LPG

Both methods were tested with the same weighttemperature and molecular weight components,namely 263,525 oF and 196,073 gr / mol. Further-more, one method will be selected for further studyby conducting sensitivity to temperature, weight ofmolecular weight components, and LPG composi-tion. These parameters are selected based on literaturestudies that have been done before. The sensitivity foreach parameter is as follows.

• Temperature (250, 263,525 and 300 oF)

• MW C6 + (196,073, 225 and 250 gr / mol)

• LPG composition (0%, 30%, 40%, and 50%)


The next step is to form a correlation that can deter-mine the MMP value for Field X with the constituentvariables in the form of parameters that are significantto the MMP value. The formation of this correlationuses the Design of Experiment (DOE) method as de-scribed previously. The DOE feature in MINITAB 17software with the Two-Level Factorial Design modelrequires 8 input data in the form of MMP values be-cause there are 3 parameters to be tested. Each param-eter requires input data in the form of maximum andminimum sensitivity values. Then, the MMP value

A Novel Correlation on MMP Prediction in CO2-LPG Injection System: A Case Study of Field X in Indonesia

287

for each pair of sensitivity values between parameterswas included in MINITAB 17. The input data for thisDOE can be seen in Table 7.

Table 1: DOE Input Data.

MWC6+

Co2 Temperature(f)

MMP(psi)

196.073 100 250 2795.00196.073 50 250 1336.33196.073 100 300 3025.00196.073 50 300 1788.75250 100 250 3455.00250 50 250 1920.00250 100 300 3900.00250 50 300 2122.82

The results obtained for the DOE in this study canbe seen in the Pareto Chart and Normal Plots shownin Figure 2 and Figure 3. In the Pareto Chart, it canbe seen that the three parameters have a significant ef-fect on the determination of the MMP Field X value.This can be seen from 3 the parameter bar has crossedthe minimum line which indicates the boundary of aparameter has a significant effect or not. From thePareto Chart, it can be seen that the parameter withthe most significant effect is the composition of CO2 -LPG, then followed by the molecular weight of C6 +,and finally the temperature. This shows that the effectof the composition of CO2 - LPG is the most impor-tant parameter in reducing MMP on case of Field X.In addition, Normal Plot also shows that all three pa-rameters have a significant effect on MMP values andCO2 - LPG composition parameters having the far-thest point from the normal line. This again confirmshow the composition of CO2 - LPG has the most sig-nificant effect. The three parameters are to the rightof the normal line which indicates that the higher thevalue of the parameter, the MMP value will also in-crease (positive effect). This is because in this DOEtest the composition parameters of CO2 - LPG onlyuse CO2 input as a parameter so that the increasein CO2 composition will certainly increase the MMPvalue.

Furthermore, MINITAB 17 software forms a cor-relation consisting of these parameters. The correla-tion formed is a linear correlation. The correlation isas follows.MMP = - 4075 + 11.37 x (MW C6) + 30.04 x (CO2)+ 6.65 x (T)

From the correlation, the R-Squared value is98.65%, with the Standard Error of Regression (S) of136,754. The correlation summary model is shown inTable 2. This shows that the resulting correlation isvery good and has a high match with the input data.

Furthermore, a feasibility test for the correlation

Figure 2: Normal Plot of Parameter Effects.

Figure 3: Pareto Chart of The Correlation.

that has been formed is carried out by calculating theprevious MMP value. From the results, it can be seenthat the Average Absolute Relative Error (AARE)value is 4.52% with Maximum Absolute Relative Er-ror (MARE) of 13.22%. In addition, a graph plot wascarried out between the slimtube MMP value and theMMP value calculated using correlation. The resultscan be seen in Figure 4. The R-Squared generatedin this graph is 96.47% which means that this corre-lation is considered to determine the MMP value forField X.

Figure 4: Accuracy of the New MMP Correlation.


288

Table 2: Correlation Summary.

S R-sq R-sq(adj) R-sq(pred)136.754 98.65% 97.64% 94.62%

Correlations that have been formed will then becompared with various other correlations. There are12 correlations that will be used to test the feasibil-ity of the correlations that have been formed. The 12correlations were the correlations of Cronquist, Lee,Yelling-Metcalfe, Orr-Jensen, Alston, Emera-Sarma,Yuan, Shokir, Chen, Ju, and Hao Zhang. This correla-tion will be used to calculate MMP values in variousoil conditions. There are 9 oil data with various com-positions and temperatures obtained from various lit-erature. The oil data will be used as input data for cal-culating MMP values with the correlations mentionedabove. Comparison between MMP correlation valuesand literature MMP is shown in Figure 5. In addi-tion, the AARE value of each correlation is shown inFigure 6.

Figure 5: Comparison of MMP Calculation Correlation.

Figure 6: AARE Comparison of MMP Correlations.

From the results of calculations that have beenmade, it can be seen that the correlation proposed in

this study has AARE and MARE values of 10.82%and 27.18%. Meanwhile, the correlations of Cron-quist, Lee, Yelling-Metcalfe, Orr-Jensen, Alston,Emera-Sarma, Yuan, Shokir, Chen, Ju, and HaoZhang produced an AARE score of 15.91%, 36.96%,19.58%, 32.32% respectively. , 18.87%, 20.48%,12.70%, 27.09%, 20.88%, 14.36%, 29.45%, and8.06%. This means that the correlation formed hasquite good results because other correlations have agreater AARE value, except for the correlation of HaoZhang who has AARE of 8.06%. This can occur be-cause the correlation formed in this study uses C6 +heavy components while the input data is C7 +. In ad-dition, the parameters for the formation of correlationin this study have not been checked with a broadervalue. Even so, the results of calculating the MMPvalue using the correlation formed from this study canbe said to be better than some of the existing correla-tions.

4 CONCLUSIONS

Based on the studies that have been done, the obtainedconclusion as follows.

• The method of reducing CO2 injection MMP bymixing LPG and CO2 first successfully reducesMMP significantly more than the CO2 injectionMMP reduction method by mixing LPG into FieldX oil. Thus, the mixing method of LPG and CO2is the most optimal method to reduce CO2 injec-tion MMP in Field X.

• In Field X, the composition of CO2 - LPG, C6+ molecular weight, and temperature are parame-ters that significantly influence the CO2 injectionMMP value. The average MMP value decreasedby 29.5% with an increase in the composition ofLPG in the gas mixture of CO2 - LPG injection by30%, the MMP value increased by an average of23% with a change in molecular weight of hexaneplus of 27.5% higher than before, and the MMPvalue increased by an average of 13.4% with anincrease in temperature of 20%.

• The resulting correlation to determine the valueof MMP of CO2 injection in Field X is as fol-lows. MMP = - 4075 + 11.37 x (MW C6) +30.04 x (CO2) + 6.65 x (T). The correlation has R-Squared of 98.65% and AARE between the MMTresults of the slimtube simulation and the correla-tion is 4.52%.

• The resulting correlation has AARE of 10.82%and MARE of 27.18% when tested using data

A Novel Correlation on MMP Prediction in CO2-LPG Injection System: A Case Study of Field X in Indonesia

289

from other literature. Correlations of Cron-quist, Lee, Yelling-Metcalfe, Orr-Jensen, Alston,Emera-Sarma, Yuan, Shokir, Chen, Ju, and HaoZhang produced AARE values in a sequenceof 15.91%, 36.96%, 19.58%, 32.32%, 18.87%, 20.48%, 12.70%, 27.09%, 20.88%, 14.36%,29.45%, and 8.06%. Compared to other corre-lations, the correlation formed in this study re-sulted in a fairly good MMP value because it hasa smaller AARE value, except the Hao Zhang cor-relation which has an AARE value of 8.06%.

REFERENCES

Al-Hinai, K., Al-Bemani, A., and Vakili-Nezhaad, G.(2014). Experimental and theoretical investigation ofthe co2 minimum miscibility pressure for the omanioils for co2 injection eor method. International Jour-nal of Environmental Science and Development.

Bayagub, F. (2017). Study of Miscible Flooding Design Us-ing LPG Mixture to Increase Oil Recovery. InstitutTeknologi Bandung, Bandung.

Bayat, A. (2015). Application of co2-based vapor extrac-tion process for high pressure and temperature heavyoil reservoirs. Journal of Petroleum Science and En-gineering.

Bon, J. and Sarma, H. (2005). An investigation of mini-mum miscibility pressure for co2 - rich injection gaseswith pentane-plus fraction. Kuala Lumpur: Society ofPetroleum Engineers.

Elsharkawy, A. Measuring co2 mmp: Slimtube or risingbubble method? Energy and Fuel, 10:2.

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Zhang, H., Hou, D., and Li, K. (2015). An improved co2-crude oil minimum miscibility pressure correlation.Technical report, School of Energy, Chengdu Univer-sity of Technology, Chengdu, Sichuan.

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Productivity Analysis of Frac-pack Completion in M Well with SandProblem Indication and High Permeability Formation

Herianto, Prasandi Abdul Aziz, Wijoyo Niti Daton, Steven ChandraPetroleum Engineering Program, Institut Teknologi Bandung, Jalan Ganesha No 10, Bandung, Indonesia

herianto, paa, wnd, [email protected]

Keywords: Frac-pack, Completion, Sand Control, Skin, Productivity Index.

Abstract: Sand problem is one of the obstacles happening in oil and gas wells, especially in poorly consolidated for-mation. flowing fluid will generate friction force during flow in porous media and in a longer timeframe, itcan erode the wall of formation and sand will be produced along with the hydrocarbon and become problemin the whole production system. The negative impacts of this sand start from eroding the tubing wall untilentering the surface facilities, such as separator. Due to this problem, the damaged equipment needs to befixed or maintained, which means additional cost. Frac-pack is one of completion methods which is quitepopular nowadays in oil and gas industry due to its proven effectiveness of utilization in the field. Frac-pack isa combination between hydraulic fracturing and sand control. Utilization of gravel pack only will cause addi-tional skin for wellbore, leading to decrement of well productivity index. In frac-pack, the hydraulic fracturingprocess will cover the losses and reduce the skin generated. Therefore, sand problem can be mitigated, andproduction also can be compensated. This study will observe frac-pack, starting from its history, mechanismand effectiveness to be applied in M Well. The gravel pack size will be calculated first and is used as fun-damental of proppant size selection. Then, fracturing process simulation is done using commercial softwaregenerating fracture width and fracture half-length. The result will be used to calculate final well productivityby considering skin generated. This research has proven that productivity can be enhanced by using frac-packuntil 5.23%. Therefore, frac-pack can be an effective choice of sand control completion method in M Well.

1 INTRODUCTION

Well completion is a process of preparing drilledwell to become a ready-to-produce well. In otherwords, it is a bridge between drilling and produc-tion phase. Well completion itself consists of manysub-processes, i.e. perforation and surface facility in-stallation. In designing a good well completion plan,there are many things that should be put into consid-eration. One of them is concern if the well producessand or not.

Sand production has been an obstacle in oil andgas industry. Sand production is usually caused bypoorly consolidated formation. The problem becomesa challenge for companies since it can bring harm tohydrocarbon production and the durability of equip-ment. These damages are finally leading to cost in-crement, which is avoided by company. Negative im-pacts of sand production can be: produced sand be-comes waste at surface; eroded tubing or casing wall;maintenance cost of surface facilities to remove theproduced sand.

Sand problem itself is not a new thing anymore inIndonesia. Many wells in Kalimantan Island has ex-perienced severe sand problem (Angtony et al., 2018;Abass and Nasr-El-Din, ; Bellarby, ). There havebeen some completion methods, which have beenusually used to mitigate sand problem in unconsol-idated reservoir, such as critical rate control, gravelpack, chemical consolidation and frac-pack. Theseproposed methods cause dilemma for companies dueto the impacts they give. Critical rate control is amethod of maintaining the producing rate below thelimit of erosion rate. This can be useful but still it setsa limit to hydrocarbon production.

Second, gravel pack is quite popular, but it takesexpensive cost for the installation and maintenance.Furthermore, the gravel pack can give additional skinto the reservoir. The third method is chemical con-solidation, which can also cause permeability reduc-tion, leads to decrement of hydrocarbon production(Chaudhri, 2003; Cinco-Ley and Samaniego, ).

Nowadays, in oil and gas industry, frac-packbecomes a thing for becoming chosen completion

Herianto, Aziz, P., Daton, W. and Chandra, S.Productivity Analysis of Frac-pack Completion in M Well with Sand Problem Indication and High Permeability Formation.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 291-298ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

291

method to mitigate sand control. This is not surpris-ing since frac-pack combines two processes, fractur-ing and packing. Fracturing will create more pathsfor hydrocarbon to flow and gravel packing will resistsand to be produced. Thus, well productivity logicallywill increase but still sand problem can be mitigated.This thesis will mostly talk about frac-pack and itsmodelling in M Well in Indonesia.

2 BASIC THEORY

History of Frac-packFrac-pack term is first popularized in the late of 1950by Shell in Germany to define a completion methodwhich conducts fracturing before installing gravelpack (Ellis, 1998). Another application of frac-packis conducted by Amoco in Hackberry, Louisiana, in1964, which involves fracturing method in the currentsand control completion. At that time, the process iscalled “hack fracs” (Ellis, 1998; Economides et al., ).

Not until the successful result of Tip-Screenout(TSO) in North Sea Chalk formations. PrudhoeBay and Kuparuk Field (Alaska) in 1987, frac-packmethod is focusly developed. Over the years, frac-pack is now utilized by combining TSO hydraulicfracture, which creates short and high conductivefracture, and gravel pack, which resist the proppantfrom flowing back. The fracture created is meant tobypass near-wellbore damages, which can give nega-tive impact to hydrocarbon production.

However, before frac-pack is highly recom-mended for sand problem mitigation nowadays, thismethod apparently is used to be highly debatable.This conflict is caused by concerns that frac-pack isprone to problems, such as adding the completion costand contaminating the nearby water bearing sands.This concerns can be tackled by the effectiveness offrac-pack utilization in many fields in the world, startsfrom Gulf of Mexico, America, Africa, Europe un-til Asia Pacific, as stated by R.C. Ellis (Ellis, 1998;Febriani, 2003; Hashemi and Gringarten, ). Untilnow, the number of frac-pack utilization keeps in-creasing all over the world and this shows a goodprospect of frac-pack in the future.Frac-pack MechanismFrac-pack is originally a combination between frac-turing and gravel-pack. The standard to measure asuccessful frac-pack is the ability of this method tomitigate sand problem and at the same time createfracture to cover the skin made by the sand screens.This fracture created is held open by utilizing prop-pant pumped along with the fracturing fluid.

Tip-screen out fracturing is a method used to do

fracturing in weak and high permeability reservoir.The goal is creating short and wide fracture withlength of 25 to 50 ft and width of 1 to 2 in by forcingan early screen-out. Screen-out is a condition whentreatment area cannot accept proppant anymore, caus-ing the pump pressure increase to its limit and prop-pant cannot flow farther to the tip (Houchin and Dun-lap, ; Odeh, 1980; Ott, 2003). This is occurred whenthe fluid leaks off to the formation faster than pre-dicted, caused by the high permeability of the forma-tion. Screen-out is usually undesirable because a frac-turing process with early screen-out cannot achieve itsdesigned fracture length and width. However, in frac-pack, the fracture geometry is not the main goal. Frac-turing process is conducted by following these stages:

• Spearhead stage

Also known as acid stage, this stage is meant to cleardebris which may still exist in the wellbore by usinga mixture of water and diluted acid, i.e. hydrochloricacid. The result of this stage is a clear pathway forfracturing fluid to flow into the formation.

• Pad stageIn this stage, the fracturing fluid will be pumped intothe well to frac the formation and initiate fracturingof target formation. Due to its purpose to make frac-tures only, proppant has not been mixed in the fractur-ing fluid. Proppant/slurry stage In this stage, proppant(sand) will be mixed with the fracturing fluid beforebeing pumped into wellbore. Proppant is used to keepthe fracture opened. Thus, it is meant to maintain theenhanced permeability created by the fracturing in thepad stage.

• Flush stageIn this stage, fresh water will be pumped into well-bore. It is meant to flush out any excess proppant,which may still exist in the wellbore. Tip Screen-outfracturing process in each stage can be seen in Figure1.Frac-pack Benefits

Frac-pack offers many benefits, which impactsto its popularity as sand control completion method,which are:

• Lower average skin value: skin generated fromfracturing process can reduce the skin create bythe gravel pack only, leading to a better produc-tivity.

• Support high production rate of production

• Longer life span. As proppant is filling the frac-ture to the tip, the sand will be filtered from packat the tip first. This can improve the life span offrac-pack because the sand pack around perfora-tion is not affected too much.


292

Figure 1: Tip Screen-out Process (Well Completion Design(Bellarby,2009))

• Has small failure percentage, shown in Figure 2than other sand control completion method.

Figure 2: Comparison on Failures of Sand Control Method(Ellis, 1998)

Frac-pack LimitationDespite of its effectiveness, frac-pack also has somelimitations, namely

• Inappropriate for wells with gas cap

• Inappropriate for wells with poor cement quality

• Inappropriate if there is no effective barrier be-tween aquifer and reservoir zone. However, thinshale barrier (about 1 m) is enough to ensure safeoperation

3 METHODOLOGY

Sand Pack SizingIn frac-pack method, this sand sizing is used later todetermine the size of proppant used in fracturing pro-cess. Proppant will take role to keep the fracture openand become screen for sand. In determining whichsize of proppant to use, sieve analysis is one com-mon method to use. In this thesis, sizing will bebased on Schwartz correlation (1969)(Pucknell andClifford, ; Renpu, ; Saucier, 1974), which considersthe uniformity of formation and velocity to pass thescreen. The sieve analysis result will be used to calcu-late the gravel size. For non-uniform sand condition,Schwartz suggested a correlation to determine the ef-fective gravel size.

D(40(gravel)) = 6∗D(40( f ormation)) (1)

D40(gravel) is the recommended gravel size andD40(formation) is formation grain size where 40% ofthe grain is grain from the biggest diameter. In addi-tion, uniformity coefficient term is introduced to ana-lyze the distribution of gravel size, formulated as fol-lows.

UC = Dg40/Dg90 (2)Then, a minimum and maximum size of gravel diam-eter is calculated using these formulas.

D(40(gravel)) = 0.615∗Dg40 (3)

D(40(gravel)) = 1.383∗Dg40 (4)The minimum and maximum values of gravel di-

ameter will be suited to the availability of sand packsize, shown in Figure 3.Hydraulic Fracturing Simulation

After determining the suitable proppant size, thenext step is making simulation of fracturing. Thissimulation is held in a commercial fracturing soft-ware. In this software, fracture analysis is conducted.The procedures, as shown in Figure 4, are: enter-ing the well parameters, selecting proppant, select-ing fracturing fluid, designing treatment schedule and

Productivity Analysis of Frac-pack Completion in M Well with Sand Problem Indication and High Permeability Formation

293

Figure 3: Availability of Gravel Pack Size (Reproduced from Febriani, 2003)

running the simulation. The simulation result willshow the fracture profile, from the proppant con-centration until the fracture conductivity distribution.The result will be used in the next step, which is de-termining whether frac-pack is effective to be appliedin M well or not.

Figure 4: Flowchart of fracturing simulation

Skin CalculationFrac-pack will be called effective if it can miti-

gate sand problem by applying the sand screen and in-

crease the production. This can be known by calculat-ing the skin that may be caused by frac-pack process.Based on the book written by Chaudhri (Chaudhri,2003), there are some causes that can create skin. Inthis thesis, there are only three relevant skin causes,which are: partial penetration, perforation and frac-turing.Skin Due to Partial Penetration

Partial penetration is commonly happened in gaswell. The wells are usually produced in only certainparts of pay zone, creating limited entry for the fluid.Partial penetration scheme can be seen in Figure 5.The formula to calculate skin factor due to partial pen-etration, Sp, is presented by Yeh and Reynolds (Yehand Reynolds, ), as follows.

Sp =(1−b′

b′ )ln(hwd) (5)

Where :

hwd =c′b′(1−b′)hd

exp(c1)(6)


294

Figure 5: Partial Penetration Scheme (Gas Well TestingHandbook (Chaudhri,2003))

b′ =hp

h(7)

hD =h

rw√

khkv

(8)

c1 = 0.481+1.01(b′)−0.838(b′)2 (9)

∆ZD =

[h1 h2h h1

](10)

While c’ can be estimated using the graph in Fig-ure 6.

Figure 6: C’ Determination on Yeh and Reynolds Method (Gas Well Testing Handbook (Chaudhri,2003))

Skin Due to Perforation

Skin due to perforation can be calculated usinga semi-analytical solution presented by Karakas andTariq (Karakas and Tariq, 8247). This perforationskin is sum of plane flow effect (SH), vertical skineffect (SV) and wellbore effects (Swb).Plane Flow Effects

SH = ln( rw

r′w(θ)) (11)

r′w(θ) =

aθ(rw +Lperf)

f orθ 6= 0 (12)

r′w(θ) =

aθ(rw +Lperf

4)

f orθ = 0 (13)

Vertical Skin Effect

Sv = 10ahb−1

d rbd (14)

hd =hpl p

√kvkH

(15)

rd =rp

2hp

(1+

√kvkH

)(16)

a = a1logrD +a2 (17)

b = b1rD +b2 (18)

Wellbore Effects

Swb = c1ec2rWD (19)

rW D =rw

LP + rw(20)

a1,a2,b1,b2,c1, c2 are functions of perforationphasing and can be seen in Figure 7.

Figure 7: Constants for Perforation Skin Effects Calculation(Gas Well Testing Handbook (Chaudhri,2003))

After calculating all those elements, skin due toperforation can be calculated using this formula:

SP f = SH +SV +Swb (21)

Skin Due to Fracturing Fracture performance is afunction of dimensionless fracture conductivity (CfD)as shown in Figure 8. Dimensionless fracture conduc-tivity can be calculated using this formula.

C f d =k f wkx f

(22)

This relationship is presented by Cinco-Ley andSamaniego (1981). Equivalent wellbore radius is cal-culated for the fracture by assuming that the fractureis not adjacent to ant boundaries that may cover in-terval of its reservoir. Using blue line in Figure 8,skin due to fracturing can be determined using thisrelationship Sf+ln(xf/rw). In 2005, the relationship


295

Figure 8: Fracture Performancen Under Pseudo RadialFlow (Well Completion Design (Bellarby,2009))

between skin and dimensionless fracture conductiv-ity (CfD) is generalized and validated by Meyer andJacot (Meyer and Jacot, ).Productivity Analysis

Determination on whether the productivity is in-creasing or not can be concluded by its Fold of In-crease (FOI), which is represented below:

FOI =ln[ re

rw

]−0.75+Spre

ln[ re

rw

]−0.75+Spost

(23)

4 CASE STUDY

This thesis uses data from M well, an offshore gaswell in Indonesia which has been indicated to producesand. The reservoir pore pressure is measured to be5,812 psi. This well’s formation has medium to highpermeability for about 259 mD and porosity for about19.4%. The fluid viscosity is about 0.0299 cp. Watersaturation in this well is big enough, for about 41%.This reservoir is sandstone in the interval of 10,335– 10,839 ft TVDSS. There is no gas cap indicationthat means frac-pack can be conducted in this well.In addition, the water depth is 4,255 ft and has beenobserved that the temperature in depth of 10,312 ft is182°F.

Based on DST data which conducted in M Well,the drainage radius of this well is 4000 ft. The designof M well consists of 4 casing string: conductor cas-ing, surface casing, intermediate casing and produc-tion liner with OD of 36”, 20”, 13-5/8” and 9-5/8” inorder. This well is perforated in the interval of 10,405– 10,479 ft TVDSS. The perforation scheme is: shotdensity: 4 SPF; perforation radius (rp): 0.25 inches;perforation penetration depth (L perf): 8 inches andphasing angle: 120°.

A study has been conducted to analyze the rockstrength of M reservoir and the result states that theformation is medium in strength, means that this wellneeds sand control method so that it can producefluid until depletion phase. Furthermore, the reser-voir is not well distributed so that a completion typewith larger gravel/sand interface is required to pre-vent plugging. Frac-pack is the sand control methodchosen to mitigate sand problem in this well. To de-termine the effective gravel size, sieve analysis is con-ducted with the result in Table 1.


The sieve analysis result shows that the uniformity co-efficient is 6.18. From Table 2, C value shows that thesand grain in this M formation is poorly sorted. In or-der to use Schwartz correlation, D40 value is required.From the calculation, it is obtained that D40 value is0.01793 in. The gravel design, based on Schwartzconcept, results in minimum gravel diameter (D min)of 0.01103 in and maximum gravel diameter (D min)of 0.02480 in. According to the availability of gravelsize shown in Figure 3, the gravel size chosen is 20/40US Mesh. This result will be used to choose proppantselection in Fracpro simulation.

Proppant used in the simulation is Brady 20/40 be-cause of some reasons. First, Brady 20/40 is a natural-source sand, make it easy to obtain. The sand will beshifted to the size of 20/40 US Mesh. Due to its avail-ability, this sand will cost cheaper than another typeof proppant.

Second, the screen will have a certain life span.In a time, the screen will be run out because it willbe plugged by fine sand. That makes refracturing willbe required. Using this type of proppant will makethe refracturing easier. This refracturing is conductedafter re-perforating the formation by using deep pen-etrating perforation. If resin-coated proppant or ce-ramic proppant is used, the process will be more dif-ficult because those proppants will create a harderlayer. Furthermore, Brady 20/40 is enough for thisformation since the formation is not a tight formationor basement.

Fracturing fluid used in this simulation is Dy-nafrac HT 30, provided by Weatherford. Fracturingfluid will be used to bring proppant along, thus need agel strength. Dynafrac HT 30 with viscosity of 270.9cp is suitable to provide a good gel strength. In addi-tion, this fluid is common so it will be easy to obtain.

In this case with high permeability involved, aslow fluid rate will be inappropriate. High permeabil-ity means that there will be more hole or pores in the


296

Figure 9: Fracture Profile as result from Fracpro simulation

Table 1: Sieve Analysis Result of M Well Formation

MEASUREMENT I MEASUREMENT II

NO. MESH IN % WEIGHT % CUMM.WEIGHT % WEIGHT % CUMM.

WEIGHT1 20 0.0331 9.837 9.837 12.791 12.7912 30 0.0232 2.350 12.187 2.581 15.3723 35 0.0197 1.843 14.030 1.723 17.0954 50 0.0117 7.591 21.621 7.661 24.7555 60 0.0098 3.679 25.301 3.469 28.2256 80 0.0070 9.496 34.797 6.786 35.0117 100 0.0059 5.688 40.485 7.591 42.6028 200 0.0029 32.005 72.490 26.691 69.2939 pan 0 27.510 100 30.707 100

Table 2: C value Description

C<3 well sorted, highly uniform sand3<C<5 uniform sand

5<C<10 moderate/poorly sorted sandC>10 poorly sorted highly non-uniform sand

formation, commonly called sink hole. Thus, the frac-turing fluid pumped to reservoir can enter the hole. Ifthe rate is slow, the fluid can easily flow to the macropores, leaving the proppant and then leading to earlyscreen-out. This will create a very short fracture andfail to make a good frac-pack. However, in frac-packmethod, a long fracture is unneeded because the focusis to mitigate the sand problem but here the treatmentdesigned should be used effectively. That is why, inthis case, a rate of 50 bpm is used. Meanwhile, theslurry treatment is conducted in 6 stages, whose prop-pant concentration are 2, 2, 3, 4, 5 and 6 ppg respec-tively. This is done so that the proppant will be wellspread in the fracture until the tip.

The fracture profile is shown in Figure 9. The

proppant concentration profile shows that the prop-pant has been well spread in the fracture. It is lessand less to the fracture tip. The fracture width (Wf)and half-length (Xf) created are 0.025 ft (0.3 in) and80.9 ft respectively. The dimensionless fracture con-ductivity is 0.03511.

Then, skin calculation is done based on formulain Subchapter 3. It is assumed that M formation isisotropic. The result is shown in Table 3. From theresult, the fracture skin is negative, means that frac-pack is successful because it can reduce the damagecreated by the partial penetration and perforation.

Fold of Increase is calculated to be 1.0523, meansthat frac-pack has increased the well productivity of5.23%. This is good result because the goal of frac-pack, which are mitigating sand problem and increas-ing productivity index, is achieved.


297

Table 3: Skin Calculation

Skin due to Partial Penetration Sp 27.80013Skin Due to Perforation Spf 0.120039Fracture Skin Factor Sf -1.80814Skin before frac-pack Spre 27.92017Skin after frac-pack Spost 26.11203

6 CONCLUSION

In designing frac pack completion for well M, theproppant used is Brady 20/40, where the gravel size isselected based on sieve analysis. The fluid used is Dy-nafrac HT 30, whose vendor is Weatherford, based onits suitable characteristic for this case. The designedtreatment has created fracture width of 0.3 in and frac-ture half-length of 80.9 ft. This thesis proves thatfrac-pack completion method is an effective methodto be applied in sand problem indicated well, in thiscase, M well. The productivity enhancement is about5.23%. This enhancement is happened due to fractur-ing process.

REFERENCES

Abass, H. H. and Nasr-El-Din, H. A. 2002. Sand Con-trol: Sand Characterization, Failure Mechanisms andCompletion Method. SPE, page 77686.

Angtony, W., Winarto, H., Chandra, S., Herianto, H., Nu-groho, Y. A., and Marhaendrajana, T. (2018). Applica-tion of Novel Doped Nanomaterial Resin to IncreaseSand Consolidation in A Loose Sandstone Reservoir.Proceedings Indonesian Petroleum Association, FortySecond Annual Conference and Exhibition.

Bellarby, J. 2009. Well Completion Design.Chaudhri, A. U. (2003). Gas Well Testing Handbook.Cinco-Ley, H. and Samaniego, F. 1981. Transient Pressure

Analysis for Fractured Wells. SPE, 7490.Economides, M. J. et al. 1994. Petroleum Production Sys-

tems.Ellis, R. C. (1998). An Overview of Frac-Packs: A Technical

Revolution (Evolution) Process.Febriani, S. (2003). Penanggulangan masalah produksi.

Thesis in Islamic University of Riau No. TP.06. 01,01.(01).

Hashemi, A. and Gringarten, A. C. 2005. Compari-son of Well Productivity between Vertical, Horizontaland Hydraulically Fractured Wells in Gas-CondensateReservoirs.

Houchin, L. R. and Dunlap, D. D. 1988. Formation Damageduring Gravel-Pack Completions. SPE, page 17166.

Karakas, M. and Tariq, S. (18247). 1988. Semi AnalyticalProduction Model for Perforated Completion.

Meyer, B. R. and Jacot, R. H. 2005. Pseudosteady-State Analysis of Finite-Conductivity Vertical Frac-tures. SPE, page 95941.

Odeh, A. S. (1980). An Equation for Calculating Skin Fac-tor Due to Restricted-Entry. JPT, Journal of PetroleumTechnology,(June).

Ott, W. K. (2003). World Oil: Modern Sandface CompletionPractices Handbook First Edition.

Pucknell, J. K. and Clifford, P. J. 1991. Calculation onTotal Skin Factors. SPE, page 23100.

Renpu, W. 2011. Advanced Well Completion Engineering.Saucier, R. J. (1974). Considerations in Gravel Pack De-

sign.Yeh, N. S. and Reynolds, A. C. 1989. Computation of

the Pseudo-Skin Caused by a Restricted-Entry WellCompleted in a Multilayer Reservoir.


298

Emulsion Treatment using Local Demulsifier from Palm Oil

Emre Fathan and Tomi ErfandoDepartement of Petroleum Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

[email protected],[email protected]

Keywords: Emulsion, Local Demulsifier, Palm Oil, Bottle Test

Abstract: Conventional demulsifier (chemical) are still used until now in many of oil industries which the formulas areboth expensive and harmful for the environment.In this research, the new formula of local demulsifier will betested with palm oil, lemon, glycerin, and KOH as the materials. Those materials are more friendly for theenvironment and contain hexane group and octadecenoic acid that are composition in plant that can break theemulsion. Crude oil (20.8API) is taken from wellhead of the X Field in Riau, Indonesia. Emulsion samplewill be treated with formula local demulsifier and tasted in water bath for 3 hours vulnerable with 30 minutesof observation. Bottle test method will be used with the following of 40C, 60C, and 80C as temperaturetest.The test revealed that the formula demulsifier + lemon (DKL) given the best result than conventionaldemulsifier within 120 – 180 minutes at 80C that separated 39 ml of water with 5 ml of concentration.P-valueof temperature is the only less than the significance value (α=0.05) means that the linear regression model meetthe criteria of linearity and the changes that occur are significant.

1 INTRODUCTION

The participation of water in the production process ofoil is common in upstream oil and gas activities. Thewater is formation water that has a chemical contentthat will cause problems in the series of equipmentboth under and above the surface. The occurrenceof one of them is the forming of an emulsion.These problems result in high pumping costs, pipecorrosion, and special handling of certain equipment(Abdel-Raouf, ). An emulsion is a mixture of twoimmiscible fluids, one of which is shaped dropletson the other and chemically bound or stabilizedby emulsifying agents (Soffian and Niven, 1993).Demulsifier injection is often used to overcomeemulsion problems. The process of breaking downoil-water emulsions into an oil phase and the waterphase is called the demulsification (Kokal, 2005).

However, its use is still using commercial(chemical) materials which are relatively expensive(Emuchay, Onyekonwu, Ogolo, & Ubani, 2013)and cause damage to the environment. In severalstudies, demulsifier tests with local materials havebeen carried out, for example testing with coconutoil (Emuchay et al., 2013),lime(Erfando et al., 2018),and curcas oil (Sulaiman et al., 2015). Where inall the three studies shows the potential of localdemulsifiers.The potential in the oil and gas sector

should be developed to increase local and nationalrevenues(Erfando and Herawati, 2017).

In this study, new of local demulsifier areformulated to minimize the negative impact ofcommercial demulsifier both in reduce the highcost and minimize the negative impact of usingchemical on the environment. The new localdemulsifier formula will be formulated using palmoil, gliserin, lemons and KOH compounds. Palm oilcontain hexane group and octadecenoic acid. Thosecompositions are two main plant components that canbreak the emulsion (Yaakob and Sulaimon, 2017).

For the result, those local and commercialdemulsifiers will be comparing within take abestresult of temperature, concentration of separation,and the time of separation.This study was conductedto know which formula will give the best result inseparated the water and to know the contribution ofthe parameter toward the test through analysis ofregression.

The emulsion is defined as a colloidal systemin which small grains from one of the phasepresses in other phases where they are usually notmutually mixed. An emulsion can be found in theproduction process and equipment. The type thatwe often encounter in the field is water emulsionin oil (w/o). The stability of the emulsion itselfcannot be separated from crude oil asphaltenes

Erfando, T. and Fathan, E.Emulsion Treatment using Local Demulsifier from Palm Oil.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 299-303ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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and resins (Abdel-Raouf, 2012). Emulsion in theproduction field can be classified into three types,Water-Emulsion in Oil (W/O);Oil Emulsion in Water(O/W); and Complex Emulsion (Multiple/Complex).Emulsion is an unstable system, according to (Wyldeet al., 2009), classifying the length of time anemulsion system is separated based on its stability:

• Loose emulsion: is separated in minutes;

• Medium emulsion: separate in 10 minutes ormore;

• The emulsion sight will be stable for hours or evendays and in some cases, will not be able to beovercome.

Some of the causes of the stability of theemulsion are explained in the study (Kokal, 2005).Such as agitation, the grain size, surfactant, effectof pH, the composition of brine water, viscosity,and temperature. For demulsification of emulsion,injecting the demulsifire is one of the option forseparate the emulsion to dissolve dispersed phasefrom the dispersing phase. The molecule of ademulsifier will mobilize to the interface of oil-waterand separated both natural surfactant (asphaltenesand resins) (Zhou et al., 2014). Over the yearsthere has been an over dependence on the use offoreign/commercial demulsifiers this has been foundnot to be quite effective in most cases due toincompatibility with the nature of some kinds ofcrude (Emuchay et al., 2013). For some cases itwill led to the challenge for the advanced studies tolocallyformulated demulsifier in result for improvedcost efficiency and effectiveness.

2 MATERIAL & METHOD

2.1 Material

The material we used for laboratory study of emulsionand demulsification are a water bath (MemmertWNB 14), heater and stirrer (Wisd.), digital scale(Amastech), bottle for test (duran), several breakers(Pyrex Iwaki TE-32), several graduated cylinder(Pyrex), density bottle, and stopwatch. For producinglocal demulsifier we used a commercial palmoil, potassium hydroxide (KOH), aquades, glycerin(C3H8O3), and citrus limon.

2.2 Method

Generally we used saponification, bottle test method,and statistical test. In order to produce the liquid soap

as a base of local demulsifier, we used saponificationwith following step based on (Naomi et al., 2013;Sukeksi et al., 2017; Zulkifli and Estiasih, 2014).Bottle test used to observing the result and convertingthe data into graphic. As for statistical method willbe using statistic application that allows providingwhich parameter (time of separation, temperature, orinjecting volume) most contribute for the test.

2.2.1 Production of Local Demulsifier

Local demulsifier (DKS) will be formulated withsaponification method, with the following step;a) 50ml of palm oil commercial was added to a breakerand heated with 80C for 30 minutes. b) 12.5 g ofKOH add into breaker along with 25 ml aquades andthen heated until homogenous; c) Add KOH + Aq intopalm oil and stir it with heater and stirrer in 80C, 800rpm, for 3 hours and 20 minutes; d) For the last add50 ml of aquades and stir for 5 minutes, then waitthe formula for 24 hours until the formula becomeliquid. Both formulas are the local demulsifier for thisresearch.

2.2.2 Demulsification with Bottle Test Method

The following formulas that will be tasted are: a)Local demulsifier (DKS); b) Local demulsifier +lemon (DKL); c) Commercial demulsifier (DK);andd) Base case (without adding demulsifier). Thoseformulas will be injected to a bottle of sampleemulsion (1 ml, 3 ml, and 5 ml). Each volume aretested in several temperature (40C, 60C, and 80C)for 3 hours.

Emulsion separation was recorded at various timeintervals (Hirasaki et al., 2010).The process wasmonitored for every 30 minutes in 3 hours. The stepbased on (Erfando et al., 2019; Hirasaki et al., 2010)

3 RESULT

Table 1 is the properties data for sample oil. Thedata was calculate to determine the type of oil. Thetype of oil sample is heavy oil with SG = 0.929 and20.8API. Figure 1-3 are the result of the test withbottle test method in water bath.From those figureswe found out the best, highest, and also the badseparation within the formulas.

Based on data, base case formula has the highestseparation in figures 1 (40C). Meanwhile not thecase in temperature of 60C and 80C. FormulaDKShas the highest separation value on figure 2 whenadding 5 ml concentration. Figures 2 shown that


300

commercial formula (DK) has stable separation attemperature of 60C. Meanwhile bad at temperatureof 40C (figure 1).

Table 1: Properties of Crude Oil

No Properties Value Unit1 Oil Mass 23.2 gr2 Oil

Density0.93 gr/ml

3 SpecificGravity

0.93 -

4 API 20.8 -

In figure3, formula DKL (5 ml,80C) given thestable and highest separation from 120 to 180 minuteswith temperature of 80C.The result from the bottletest method shown in figure 3, that the value of local+ lemon demulsifier (DKL) separation is 39 ml.

Based on the data above, the best resultshown in figure 3 as DKS and it takes 120 –180 minute for water separated from emulsionsample.(Hayuningwang et al., 2015) said, moreoverthe salinity and temperature here also affects theamount of separation of water, but the higher the valueof salinity the process of separating oil from watertakes longer.

Based on data, the additional of 5 ml is the bestconcentration for injecting the formulas into sample,while temperature of 80C is the ideal temperaturein this research.(Augustina and Sylvester, 2015)said,the temperature or heat broke up some of the weakemulsion thereby causing coalescence and droppingof water out of the emulsion which settle in the bottomof bottle. When the temperature is rise there is also anincrease of demulsification efficiency. The researchof (Erfando et al., 2019) also make an explanationthat the temperature is one of the parameters that canaffect the condition of emulsion significantly.

3.1 Analysis of Regression andCorrelation

Table 2: Regression Analysis Data

No Parameter P-Value R-SqR-Sq(adj)

1 Temperature 0 62.2 62.12 Injected Volume 0.362 0.4 0.13 Time 0.1 0.9 0.6

Comparison of the linear regression modelsdetermines the effect of variables X on Y (Subekti,2015). If the contribution is positive then thevalue of variable X agrees to the value of variableY.Theanalysis of regression and correlation from this

research are from statistical software, to get theinformation of regression and correlation from theparameters (time, injected volume, and temperature)versus separation.

From table 2, at the output obtained p-valueoftemperature is the onlyless than the significance value(α=0.05) means that the linear regression model meetthe criteria of linearity and the changes that occur aresignificant(Draper and Smith, 1998).

R-Sq (ad j) of temperature is 62.1%, the value isinterpreted as a percentage of contribution in the test.Both parameter injected volume and time have each0.1% and 0.6%. From those data temperature has thehighest contribute.

4 CONCLUSION

Based on laboratory test, formula DKL given thehigh result than conventional demulsifier within 120– 180 minutes at 80C that separated 39 ml of waterwith 5 ml of injected volume. The effectiveness ofemulsion breakdown using local material is betterbased on base case reference and it’s comparison witha conventional demulsifier result.The temperature hasthe biggest contributes among all the parameters seenfrom the regression analysis data.

ACKNOWLEDGMENTS

The author gratefully acknowledge financialsupport from Universitas Islam Riau and PetroleumEngineering’s laboratory for the facilities.


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Figure 1: Bottle test in temperature of 40C.




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REFERENCES

Abdel-Raouf, M. E. S. (2012). Factors affecting the stabilityof crude oil emulsions.

Augustina, O. and Sylvester, O. (2015). EmulsionTreatment in the Oil Industry: A Case Study of OredoField Crude Oil Emulsion. SPE Nigeria AnnualInternational Conference and Exhibition.

Draper, N. R. and Smith, H. (1998). Applied regressionanalysis (Vol. 326).

Emuchay, D., Onyekonwu, M. O., Ogolo, N. A., andUbani, C. (2013). Breaking of emulsions usinglocally formulated demusifiers. SPE Nigeria AnnualInternational Conference and Exhibition.

Erfando, T., Cahyani, S. R., and Rita, N. (2019). Theutilization of citrus hystrix and citrus limon as anorganic demulsifier formulation. IOP ConferenceSeries: Materials Science and Engineering,509(1):12145.

Erfando, T. and Herawati, I. (2017). Analysis of petroleumdownstream industry potential in riau province.Journal of Geoscience, Engineering, Environment,and Technology, 2(2).

Erfando, T., Rita, N., and Cahyani, S. R. (2018).Identifikasi Potensi Jeruk Purut Sebagai DemulsifierUntuk Memisahkan Air Dari Emulsi Minyak diLapangan Minyak Riau. Jurnal Kimia Mulawarman,15(2).

Hayuningwang, D., Fadli, A., and Akbar, F. (2015).Pengaruh Salinitas KCl & NaCl terhadap KestabilanEmulsi Minyak Mentah–air di Lapangan Bekasap. PT.Chevron Pacific Indonesia. Jurnal Online MahasiswaFakultas Teknik Universitas Riau, 2(1).

Hirasaki, G. J., Miller, C. A., Raney, O. G., Poindexter,M. K., Nguyen, D. T., and Hera, J. (2010). Separationof produced emulsions from surfactant enhanced oilrecovery processes. Energy & Fuels, 25(2).

Kokal, S. L. (2005). Crude oil emulsions: A state-of-the-artreview. SPE Production & Facilities.

Naomi, P., Gaol, A. M. L., and Toha, M. Y. (2013).Pembuatan sabun lunak dari minyak goreng bekasditinjau dari kinetika reaksi kimia. Jurnal TeknikKimia, 19(2).

Soffian, R. M. and Niven, T. L. (1993). Emulsion TreatmentProgram. SPE Asia Pacific Oil and Gas Conference.

Subekti, P. (2015). Perbandingan Perhitungan MatematisDan SPSS Analisis Regresi Linear Studi Kasus(Pengaruh IQ Mahasiswa Terhadap IPK). 1–21.

Sukeksi, L., Sidabutar, A. J., and Sitorus, C. (2017).Pembuatan Sabun dengan Menggunakan Kulit BuahKapuk (Ceiba Petandra) sebagai Sumber Alkali.Jurnal Teknik Kimia USU, 6(3).

Sulaiman, A. D. I., Abdulsalam, S., and Francis, A. O.(2015). Formulation of Demulsifiers from LocallySourced Raw Materials for Treatment of a TypicalNigerian Crude Oil Emulsion. (January 2015).

Wylde, J. J., Coscio, S. E., and Barbu, V. (2009). A casehistory of heavy-oil separation in northern alberta:A singular challenge of demulsifier optimization andapplication. SPE Production & Operations.

Yaakob, A. B. and Sulaimon, A. A. (2017). Performanceassessment of plant extracts as green demulsifiers.Journal of the Japan Petroleum Institute, 60(4).

Zhou, H., Dismuke, K. I., Lett, N. L., and Penny,G. S. (2014). Development of More EnvironmentallyFriendly Demulsifiers. (February), 15–17.

Zulkifli, M. and Estiasih, T. (2014). Sabun Dari DistilatAsam Lemak Minyak Sawit: Kajian Pustaka [In PressOktober 2014]. Jurnal Pangan Dan Agroindustri,2(4).


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Designing an IoT Framework for High Valued Crops Farming

Domingo Junior P. Ngipol1, Thelma D. Palaoag2

1Ifugao State University-Aguinaldo Campus, Aguinaldo, Ifugao, Philippines2University of the Cordilleras, Baguio City, Philippines

ngipoldj, [email protected]

Keywords: Internet of Things, Sustainable Agriculture, IoT Framework, High Valued Crops.

Abstract: Agriculture plays a vital role in providing employment, revenue and domestic product of farmers. In thePhilippines, agriculture has a large share of employment and likewise with the population who depends onit. The increase of agricultural product and income is necessary for the growth of the country’s economiccondition. Unfortunately, the insufficiency of technology and the use of traditional methods of farming alongwith the issues and challenges associated to crops farming greatly affects farmers which results to low yieldingof crops. The integration of smart agriculture using the Internet of Things (IoT) is an absolute solution inmodernizing the traditional methods of agriculture. This simplifies farming techniques and improves timeefficiency, water and fertilizer management, crop monitoring, soil and security management. This paperproposes an IoT framework that address the current issues and challenges associated to high valued cropsfarming in Alfonso Lista, Ifugao. It integrates two main functions including environment data sensing bya wide variety of sensors and environment factors control with some mechanics driven by smart actuators.This sensors and actuators are used for real-time monitoring, analysis and collection of information about thefarm conditions like weather, moisture, temperature, humidity, fertility of soil and level of water. Essentialdata were gather by means of observation and in-depth interview with Ifugao farmers and employees of YaoJia Xi Corporation – Alfonso Lista, Ifugao. The developed framework provides holistic foundation in thedevelopment of IoT-driven system for high valued crops farming with low cost and easy implementation.

1 INTRODUCTION

The economic development of a country mostlydepend on agricultural products as it is the mainsource of food and other raw materials. It providesemployment opportunities, income and domesticproduct to the people. Of the 42.78 million personsin the Philippine labor force in 2017, the agriculturesector absorbed 10.26 million persons, representing25.44 percent of the national employment (PSA,2018). However, the use of traditional methods offarming greatly affects farmers which results in lowyielding of crops. It is evident that the automationof manual processes of farming and the use ofautomatic machineries improved the yielding ofcrops (Gondchawar and Kawitkar, 2016). Improvingfarm productivity is essential in order to increasefarm profitability and to provide the rapidly growingdemand of food caused by rapid population growthall over the world. According to the United Nations’Food and Agriculture Organization, food productionmust increase by 50% to be able to feed the rapidly

growing population that is expected to reach 10billion by 2050. The urgent need in increasing thecrop productivity is vital as it is the foundation ofany solution for food shortage and farm profitabilityproblems (FAO., 2019). The sustainability inagriculture plays an important role in addressing thischallenges since it offers technological advancementthat increase productivity and profitability whileconserving resources, minimizing waste andenviromental impact, and promoting agroecosystemresilience (Velten et al., 2015). Hence there is a needto integrate smart farming and precision agricultureusing Internet of Things (IoT) technology in orderto achieve sustainable agriculture with increaseproduction efficiency, profitability and the quality ofagricultural products (Malavade and Akulwar, ).

High value crops refer to new and expensive foodcrops such as vegetables, fruits, flowers, houseplantsand foliage, condiments and spices. Most high valuecrops have higher production efficiency and incomecompared to usual cereal grains and export foodcrops. It is not usually a common food for local

304Ngipol, D. and Palaoag, T.Designing an IoT Framework for High Valued Crops Farming.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 304-310ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

people and are mainly grown for higher income indomestic and even abroad.

Over the past few years, IoT technology havebeen introduced in almost every area of the modernsociety. Among this areas are Smart Cities, SmartHealth Care, Smart Industry, Autonomous Vehicle,Smart Agriculture, Precision Agriculture and others(Shang et al., 2015). IoT is significantly considered inthe area of technology which gains appreciation andattention from known and reputable industries likeGoogle, Apple, Samsung and Cisco (Vermesan andFriess, 2014). The IoT is referred to as the Internetof Objects that integrates several technologies suchas computers, smart phones, internet, sensors,wireless communication technology and embeddedsystems to complete a system that is capableof data transmission without human intervention(Mohammed and Ahmed, 2017).

As an emerging paradigm, the IoT has greatpotential that can have a significant influence onthe future of the world (Stoces et al., 2016).The application of the latest IoT technologiesin agriculture practice allows traditional ways offarming to be changed fundamentally on everyaspect, paving way to a new agriculture pattern ofprecision agriculture (Zhang et al., ). Iot devicessuch as wireless sensor, connected weather stations,cameras, and smart phones are capable of gatheringhuge amount of environmental and crop performancedata which ranges from time series data fromsensors, to four-dimensional data from cameras andto human interventions and observations. This dataare analyzed to filter out invalid data and computepersonalized crop recommendations for any specificfarm (Veena et al., 2018).

IoT technologies such as IoT devices providesa better way of collecting, gathering, exchanging,and transmitting data which absolutely delivers aninnovative way in data processing and intelligentdecision-making (Sreekantha and Kavya, 2017). TheInternet of Things provides the fundamental networkinfrastructure to the physical and the digital worldsthrough which smart objects, ranging from microsensors to heavy agricultural vehicles communicateto each other (Bhuvaneswari and Porkodi, 2014). It iscapable of transforming the agricultural domain intomore efficient and productive farming and improvesthe quality of life of farm workers by reducingheavy labor and tedious tasks (Elkhodr et al., 2016).At present, the internet protocol is mainly used incommunicating and interconnecting numerous smartobjects and various kinds of embedded devices andtechnologies. The increase in the application anddistribution of smart objects and internet of things

significantly impact the human life in the futuregenerations (Rghioui, 2017).

Smart farming involves the use of the Internet ofThings (IoT) to provide solutions via the electronicmonitoring of crops, as well as related farmconditions (Mohanraj et al., 2016). Understandingand forecasting crop condition and performanceunder extensive diversity of environmental, irrigation,soil and fertilization is important to improve farmproduction efficiency (Jayaraman et al., 2016).Moreover, Iot-based smart farming allows farmers tohave better control over the process of growing cropsand making it more predictable and easy to manage(Prathibha et al., 2017).

Consequently, the absolute integration of IoTtechnologies into smart farming advanced theagriculture to a new level by which the wholeagriculture industry is modernized with increasedproductivity and profit. In a broader perspective, thescope of smart agriculture which covers IoT improvesor solves critical issues such as drought response, cropyield optimization, land and water management, andpest control (Rajakumar et al., 2018). In connectionto this, the study aims to discuss the current issues andchallenges associated to high valued crops farming inAlfonso Lista, Ifugao. It also covers the frameworkthat shall be design to address the current issues andchallenges associated to high valued crops farming inAlfonso Lista, Ifugao.

2 METHODOLOGY

This study was qualitative in nature which aimed toexplore the current issues and challenges associatedto high valued crops farming in Alfonso Lista,Ifugao and develop a framework that address eachof the issues and challenges. The primary methodof data collection was possibly made throughin-depth interviews with the Ifugao farmers, thefarm manager and farm workers of the Yao JiaXi Corporation – Alfonso Lista with their variousrelevant functions which covers the scope of thestudy. The researcher used unstructured and informalinterviews which positively allows a more flexibleand responsive discussion for both the researcherand the respondents. Moreover, related articles werealso reviewed to allow a wide-ranging knowledgeon internet of things practices and applications.A framework development process was used as aguide during the development of the frameworkwhich involves the four main phases: designphase, implementation phase, instantiation phase andmaintenance phase.


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Figure 1: Framework Development Process.

Design phase: The framework structure in thisphase is defined by the framework designer, whichutilizes the information generated in the domainknowledge analysis and requirements phase. Thisrequires an imaginative task and organized method tocreate the framework design from requirements level.

Implementation phase: In this phase, theframework builder generates the actual frameworkalong with the framework documentation.

Instantiation phase: During this phase,applications are being generated by the applicationdeveloper basing from the framework which utilizesthe artifacts created in the implementation phase.

Maintenance phase: Lastly, the maintenancephase allows a harmonious communication betweenthe framework design and especially to the wholeframework which also supports the transformation ofthe design and implementation level.

3 FINDINGS

Alfonso Lista is a third class municipality of Ifugaowith a vast land for agriculture. It has a progressingtopography with an agricultural land area of 15,546hectares, a pastureland of 17,808 hectares, a forestarea of 7,305 hectares and a residential area of 394hectares with a total land area of 41,051 hectares.It is politically subdivided into 20 barangays witha total of population of 32, 119 according to the2015 census. A large percentage of its populationdepends on farming with corn, banana, cassava,

legumes, tobacco, peanuts, gabi, and other high valuevegetables as their main produce. Marketing ofagricultural products in Alfonso Lista, Ifugao is quiteeasy because of the presence of traders within themunicipality and even from neighboring provincesand cities. Figure 2 shows the satellite view ofAlfonso Lista, Ifugao which obviously shows a largeportion for agriculture.

Figure 2: Satellite View of the Municipality of AlfonsoLista.

However, the insufficiency of technology andthe use of traditional methods of farming alongwith the issues and challenges associated to cropsfarming greatly affects the productivity of the Ifugaofarmers. Below are the current issues and challengesassociated to high valued crops farming that wereidentified during the actual visit in the farm and werestrongly signified by the majority of the respondentduring the in-depth interview.


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3.1 Current Issues and ChallengesAssociated to High Valued CropsFarming in Alfonso Lista Ifugao

Water demand and shortages: The Philippine Foodand agriculture are the largest consumers of waterwhich requires more than the use for personal needs.Figure 3 shows the total water withdrawal in 2009 thatreached up 81, 555 million cubic meter, of which 82percent was for irrigation and livestock that includes754 million cubic meter for aquaculture, 10 percentfor industry purposes and 8 percent for municipalities(FAO., 2019).

Figure 3: Philippines Water Withdrawal by Sector

On the other hand, agriculture production in theprovince of Ifugao especially in the municipalityof Alfonso Lista is highly dependent on water andincreasingly subject to water risks due to rapidpopulation growth, changing climate, increasingdemand for food and other individual needs. Asa result, water scarcity is being encountered whichadversely affect the yield of farmers since rainwateris not enough as the source for irrigation of theiragricultural crops.

Fertilizer mismanagement: Fertilizer is one ofthe fundamental substance containing the chemicalelements to improve growth and productiveness ofagricultural crops. Therefore it is important to selectthe right source, the right place, the right timing,and the right rate of application for the greatestfertilizer nutrient use efficiency. Figure 4 shows the4R principles of Nutrient Stewardship (Johnston andBruulsema, 2014).

However, all farmers in the province of Ifugao arestill using the traditional method of applying fertilizerwhich is subjected to fertilizer misuse. Ifugao farmerscommon assumption regarding fertilizer applicationis “the more, the merrier” which adversely affectsthe agricultural crop, soil and the environment dueto salinity build up or to the toxicity of the chemical

Figure 4: 4R principles of Nutrient Stewardship

elements. Moreover, application of fertilizer with thecorrect rates is not a guarantee of a bountiful harvestbut it’s the application at the right rates at the righttime since the nutrients uptake of crops is at differentrates and ratios at the different phonological growthstages.

Unawareness on soil testing: Agriculturalproductivity mainly depend on soil which serves asa medium for plant growth and a sink for heat, waterand chemicals. To achieve the soil full potential, soiltesting must be done to determine the plant nutrientneeds and for environmental assessments. However,almost all farmers in Ifugao are not aware on soiltesting which results to misuse of fertilizers and otherchemical elements which in turn causes soil qualitydegradation.

Lack of farm security: Safeguarding farm assetsfrom burglars and destructive animals is veryimportant to avoid unexpected loses. However,farmers usually overlooked which allows burglars anddestructive animals robbed and destroy any valuableand available resources in the farm.

3.2 The Proposed IoT Framework forHigh Valued Crops Farming

Figure 5 shows the IoT framework for high valuedcrops farming which aims to address the identifiedissues and challenges associated to crop farming inAlfonso Lista, Ifugao. The IoT framework is a controlmodel for irrigation, application and distribution offertilizer. It is also a control model for farm security,real-time monitoring and collection of informationabout the farm conditions like weather, moisture,temperature, fertility of soil and level of water.The framework is composed of the Embedded IoTPlatform and the three layers: the application layer,network layer and the perception layer.

Perception Layer: This layer composes the


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Table 1: Hardware requirements part 1

Category Item Name Specification Function

Power Source Solar Panel

The solar panel minimumdimension is 38 x 22centimeter with 12 voltsworking power.

Its main purpose is to rechargethe battery for continuous operation.

RechargeableBattery

The most recommended battery isa sealed lead acid battery with 12volts power and 5 amp hour.

The battery serves as the mainsource of power.

IoTSensing Devices

Soil Sensor

The soil sensor working voltage isranging from 3.3 to 5 volts with anoperating temperature of -40degrees to +60 degrees.

It is mainly used to quantity the watercontent, salinity and nutrients of soil inthe farm.

TemperatureSensor

The temperature sensor measuringrange is from 0 degrees to 50degrees with a measurement errorof +- 2 degrees. The operatingvoltage is from 3.3 to 5 volts.

It is used to collect data about temperaturefrom the farm.

Water LevelSensor

The water sensor operating voltageis ranging from 5 to 24 volts with aresponse time of 500 millisecondsand an operating temperatureranging from 0 degrees to 105degrees.

It is used to detect the water level of thewater tank.

Water Flow RateSensor.

The water flow sensor workingvoltage is ranging from 5 to 18volts with a maximum waterpressure of 2 Mega Pascal.

The water flow sensor is used to quantitythe volume of water passing through thewater tank pipe and the amount offertilizer for the crop needs.

Real Time ClockThe real time clock operatingvoltage is ranging from 2.3 to 5.5volts with a battery backup.

It is solely built for keeping time thatbasically counts hours, minute, seconds,months days and years. It is used toidentify the schedule on when to applyfertilizer.

PIR MotionSensor

The working voltage of the PIRmotion sensor is ranging from 5 to20 volts with a delay time of .3seconds to 18 seconds.

The primary purpose is to sense motionaround the farm.

Microcontroller ATMega2560microcontroller

The microcontroller operatingvoltage is 5 volts with arecommended input voltageranging from 7 to 12 volts.

It is used to process data and control everytask for the whole system.

sensors and actuators which primarily aims to acquireand collect data from the physical world which isprocessed and serves as a basis for the actuatorsto operate. The process of perception is based onthe IoT sensing devices such as the soil moisture/ salinity sensor, temperature sensor, water levelsensor, water flow sensor and the PIR motion sensor.Moreover, this layer is responsible in convertinginformation to digital signals to allow convenientnetwork transmission.

Network Layer: The network layer serves asgateway and provides data routing and addressingpaths for network communication. It allows datatransfer in the form of packets through logicalnetwork paths in an ordered format. The networklayer processes the received data from the Perception

Layer and transfer it to the Application Layerusing various network technologies like wirelessnetworks which includes WiFi, Bluetooth and 3Gnetwork. This layer is basically used as a mode ofcommunication between the application layer and theperception layer.

Application Layer: This layer composes theMobile Application and the Monitor. It constitutethe front end of the whole IoT framework whichprovides personalized based services according touser relevant needs. It allows the user to receivetext messages or notifications from the system andprovide real time data monitoring through graphicalrepresentations regarding the farm condition whichthe user can understand. Real time data from themonitor serves as a basis for user decision making or


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Table 2: Hardware requirements part 2

Actuators

Liquid CrystalDisplay (LCD).

The LCD uses Liquid CrystalMonitor (LCM) that operates with5 volts Direct Current with 80mmx 36mm x 12mm dimension.

The LCD serves as a monitor for allenvironment data that is provided by theIoT sensing devices.

Relay SwitchModule

The relay switch operates with 5volts with output maximum contactof AC110V, AC250V 10A andDC30V 10A.

It is responsible in controlling thesolenoid valve which is switch on or offwhenever the soil moisture reached thethreshold value.

Solenoid Valve

The solenoid valve operatingvoltage is 12 volts direct currentwith recommended water pressureof .02 to .08Mpa.

It operates with an electromagneticsolenoid coil which change the state of thewater valve from closed to open wheneverthe relay switch is turned on, or vice-versa.

Water PumpThe water pump operating voltageis 12 volts that is powered by 2pieces of 100 watts solar panel.

It is used to refill the water tank wheneverthe water level sensor reached thethreshold value.

GSM Shield

The GSM shield module operatingvoltage is ranging from 5 to 26volts that allows communicationusing the GSM cell phone networkwhich includes SMS, MMS, GPRSand audio.

The GSM shield module sends textmessages to users whenever the water tankis running out of water and also wheneverthere are intruders or animals around thefarm.

BuzzerIt operates with 5 volts withcontrollable sound frequencies andhas 16 ohm resistance.

The buzzer is triggered whenever there areintruders or animals around the farm.

CommunicationNetwork

3G It is the third generation of wirelesstechnology for mobile phones.

It is used as mode of communicationbetween the system and the users.

Bluetooth

Bluetooth allows to transmit datawirelessly over a short distanceusing short-range wirelesstechnology devices such as smartphones and computers.

It is used as mode of communicationbetween the system and the mobile phone.

WiFi

The minimum WiFi specificationis the 802.11 WLAN which offershigher speed transmission andlonger transmission range.

It is used to provide wireless high-speed Internet and network connections.

User Interface Mobile phone

Smart phone is the mostrecommended mobile device forthe application since the systemprovides graphical data and textmessages.

The mobile phone allows the users toreceive text messages from the system. Itis also used to monitor the farm conditionand can perform system override.

Display Monitor

The display monitor can be LCDscreen with a minimum size of98mm x 60mm x 20mm or tabletthat supports wirelesscommunication such as Bluetoothand WiFi.

The display monitor allows the user toview data in visual form.

further actions.

Embedded IoT Platform: The embedded IoTplatform composes the microcontroller and the powersource. Its primary function is to process and interpretdata from all the layers and control every task for thewhole operation of the system. The microcontrolleris powered by rechargeable battery which is beingrecharge through solar panel.

3.3 Technology Required

The technology required in this research is listed inTable 1 and Table 2.

4 CONCLUSIONS

The developed IoT framework for high valuedcrops farming in Alfonso Lista, Ifugao is a


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Figure 5: IoT Framework for High Valued Crops Farming

holistic solution for the identified current issuesand challenges associated to high valued cropsfarming. It is a control model of irrigation,fertilizer, soil monitoring and security managementwhich is composed of several sensors to provideenvironmental data and microcontroller to manageoperations on how and when the actuators shouldperform basing from environment data. The actualimplementation promotes sustainable agriculture andimproves agricultural production with affordable andeasy implementation for small scale farmers.

ACKNOWLEDGMENTS

This study was supported by the ResearchDevelopment and Extension Training ServiceUnit and funded under the Research Developmentand Special Trust Fund of the Ifugao State University.

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Consideration of the Different Pile Length Due to Soil Stress and InnerForces of the Nailed-slab Pavement System under Concentric Load

Anas Puri1, Roza Mildawati1 and Muhammad Solihin2

1Department of Civil Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Undergraduate Student Department of Civil Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

anaspuri, [email protected], [email protected]

Keywords: Inner Forces, Lateral Deflection, Stress Distribution, Longer Piles, Soft Clay, Soil Stress.

Abstract: Concentric loading on the Nailed-slab Pavement System causes stress in the soil and the inner forces instructural elements. The load stress is transferred to the soil by the structural elements tends to concentrate inthe centerline area under the system. Since load stress is concentrated in the center line area, the soil stress andinner forces can be higher in the center of the system. To reduce the soil stress and inner forces of structuralelements, the longer pile can be put in the center area of the system. This research is aimed to learn thesoil stress and inner forces behavior of the Nailed-slab Pavement System in case putting the longer pile in thecenter area of the system. The maximum double wheel load was taken 50 kN which transfer to the slab surfaceby contact pressure. Wheel load was loaded in the center of the slab. The Nailed-slab materials properties andsoft clay properties were taken from the previous researcher. The piles in the center area of the Nailed-slabwere longer 33.3% than others. Results show that the Nailed-slab by longer piles in the center area can reducethe soil stress significantly for maximum shear stress up to 28%. The inner forces were also reduced by about43% to 46% and caused the reducing in lateral deflection of pile tip about 37%. It can be concluded that theincreasing pile length in the central area of the system can reduce soil stress and inner forces of the system.

1 INTRODUCTION

The uniform pile length in bearing the verticalloadings on the Nailed-slab Pavement System wasused by the previous researchers. Such as the researchby Hardiyatmo (2011), (Puri et al., 2011a; Puri et al.,2011b; Puri et al., 2012; Puri et al., 2013; Puri et al.,2014; Puri et al., 2015; Puri and Mildawati, 2019)and (Puri et al., 2015; Puri, 2016) for Nailed-slabSystem on the soft clay. The distribution of soil stresswill be experienced a maximum settlement due to theload position. A maximum settlement on the center ofthe Nailed-slab can be occurred due to the concentricload. The soil stress and inner forces analysis can bedone by the finite element method of Plaxis software(Puri et al., 2015; Puri, 2016; Puri and Mildawati,2019; WARUWU, 2018). Inner forces analysis ofNailed-slab can be also done by the finite elementmethod of SAP2000 (Puri et al., 2015; Somantri,2013) and Abaqus (Syarif et al., 2018; Diana, 2017).This research is aimed to investigate the effect ofdifferent pile length due to the soil stress and innerforces behavior of the Nailed-slab Pavement System.

2 METHODOLOGY

This research used the soil and Nailed-slab structuraldata from Puri (2015). The soft soil geometry wasset with thickness 10 m. There was the densesand layer below the soft clay which neglected inthe analysis. The considered load 50 kN was aconcentric load on the pavement slab. The boundarycondition of the soil is shown in Figure 1. Figure 1ashows the Model 1 which used uniform pile lengthand Figure 1b for different pile length (piles in thecenter area longer 33.3% the edge piles). (Somantri,2013) analyzed full-scale Nailed-slab model by usingsoil properties from experimental project. (Puri andMildawati, 2019) simulated the effect of dimensionsof Nailed-slab by using soil and structural propertiesfrom full-scale test.

The dimension of Nailed-slab model was 6.0 mx 3.6 m and 0.15 m slab thickness. The slab issupported by 5 piles. Pile diameter was 0.30 m. Pilespacing was 1.20 m. The pile-slab connections weremonolithically. The pile length for model 1 was 1.50m and for model 2 was 1.50 m for edge piles and2.00 m for piles in the center area of the slab. The

Puri, A., Mildawati, R. and Solihin, M.Consideration of the Different Pile Length Due to Soil Stress and Inner Forces of the Nailed-slab Pavement System under Concentric Load.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 311-314ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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Table 1: Model and parameters of soil.Parameters Name/ Notation Soft clay Unit

Material model Model Mohr-Coulomb -Material behavior Type Un-drained -Saturated density γsat 16.30 kN/m3

Dry density γd 10.90 kN/m3

Young’s Modulus E 1,790.00 kPaPoisson’s ratio ν 0.45 -Un-drained cohesion cu 20.00 kPaInternal friction angle φ 1.00 oDilatancy angle ψ 0.00 oInitial void ratio e0 1.19 -Interface strength ratio R 0.80

Table 2: Model and parameters of structural elements inFEM 2D plain strain.

Parameters Name/Notation Lean concrete Structural elements UnitSlab PileMaterial Model Model Volume element Plate Plate -Material behavior Type Elastic Elastic Elastic -Normal stiffness EA - 4,554,000 738,528 kN/mFlexural rigidity EI - 8,539 5,649.74 kNm2/mEquivalent thickness d - 0.15 0.3 mWeight w - 3.60 0.9 kNm/mPoisson’s ratio v 0.2 0.15 0.20 -Unit weight γ 22 24 24 kN/m3

Young’s modulus E 17,900 25,300 19,600 MN/m2

Interfacestrength ratio R 0.80 0.80 0.80

models were analyzed by 2D finite element method(FEM). In 2D FEM plain strain analysis, the softclay was modeled by Mohr-Coulomb in un-drainedcondition. All structural elements were modeledby plate element in linear-elastic behavior. Leanconcrete was modeled by soil with the linear-elasticnon-porous material. Soil parameters and idealizationof structural elements are presented in Table 1 and 2respectively.

3 RESULTS AND DISCUSSIONS

Results are shown in Tabel 3, 4 and Figure 2.The loaded Nailed-slab caused soil and structuralmovements and stresses.

3.1 Soil Stress

Table 3 shows the results of the effects of differentpile length due to soil stresses. The soil effective shearstresses are shown in Figure 2. The soil effectiveshear stresses for Model 2 has a similar shape toModel 1. Maximum shear stress, effective stress,and maximum excess pore pressure tend to decrease(Table 3). That was beneficial for the soil. Whilethe maximum excess pore water pressure under thecentral pile tip tends to increase about 12%. Thedistribution of the effective shear stress in the soil isshown in Figure 2. Model 2 can significantly reducethe maximum effective shear stress and maximum

excess pore water pressure 37% and 32% respectively.While the maximum excess pore water pressure underthe central pile tip a little bit increase about 12% andeffective stress of soil insignificantly decrease. Model2 also has a better stress distribution because it haswider stress distribution.

Table 3: The stresses in the soil

Description Unit Model1

Model2

Maximum shear stress,τxy−max

kN/m2 -15.31 -9.69

Effective stress, σ kN/m2 65.33 64.27Max. excess pore waterpressure, U kN/m2 107,49 72,93

Max. excess pore waterpressure under the centralpile tip, U

kN/m2 -11.00 -12.31

3.2 Inner Forces of Structural

Table 4 shows the inner forces in the structuralelements. The slab has a negative bending moment inthe area of the slab center similar to other researchers(Puri et al., 2015; Puri, 2016; Diana, 2017; Puri andMildawati, 2019). Using the longer pile in the centerarea of the slab were result in the good effects. Allinner forces decreased by using the longer pile, exceptfor bending moment on the pile head was relativelyconstant. Model 2 can significantly decrease thebending moment of slab of about 46%. Otherwise,it can also decrease the bending moment and axialforce of pile 46% and 43% respectively. Decreasingthe inner forces in the structural elements is verybeneficial for this system. In the case of lateraldeformation of pile head, Model 2 can significantlyreduce it about 37%.

Table 4: The extreme inner forces in the structural elements.

Description Unit Model1

Model2

Bending moment ofslab, Ms

kNm/m -42.62 -22.78

Bending moment ofpile, Mp

kNm/m 2.94 2.95

The axial force ofpile, P kN 12.33 6.61

The shear force ofpile, H kN 15.33 8.72

Lateral deflectionof pile tip, Ux

mm -7.53 -4.73


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Figure 1: Variation of the model in the analysis.

Model 1, τxy−max = 15.31 kN/m2

Model 2, τxy−max = 9.69 kN/m2

Figure 2: Distribution of effective shear stress of soil.

4 CONCLUSIONS

The results of this study prove that although theJCI change pattern follows the changing pattern

of macroeconomic variables, but after it has beenproven by a series of statistical tests, none of themacroeconomic variables affect JCI in the short run.This might be caused by investors in Indonesia paymore attention to the fundamental factors which arethe company’s financial performance. In addition,stock indices in a country do have a tendency toincrease due to developments in a country’s StockExchange.

REFERENCES

Diana, W. (2017). Behavior of Nailed-slab System onPeat Soil. Dissertation, Universitas Gadjah Mada,Indonesia (in Indonesian).

Puri, A. (2016). Behavior of uplift resistance of singlepile row nailed-slab pavement system on soft claysub grade. In Proceeding of the 3rd Asia FutureConference (AFC).

Puri, A., Hardiyatmo, C., Suhendro, B., and Rifa’i, A.(2011a). Experimental study on deflection of slabwhich reinforced by short friction piles in soft clay. InProc. of 14 th Annual Scientific Meeting (PIT) HATTI,pages 10–11.

Puri, A., Hardiyatmo, H., Suhendro, B., and Rifa’i, A.(2011b). Contribution of wall barrier to reduce thedeflection of nailed-slab system in soft clay. In Proc.of 9th Indonesian Geotech. Conf. and 15th Annual

Consideration of the Different Pile Length Due to Soil Stress and Inner Forces of the Nailed-slab Pavement System under Concentric Load

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Scientific Meeting (KOGEI IX & PIT XV) HATTI,pages 299–306.

Puri, A., Hardiyatmo, H., Suhendro, B., and Rifa’i,A. (2013). Application of method of nailed-slabdeflection analysis on full scale model andcomparison to loading test. In Proc. the 7 th NationalConference of Civil Engineering (KoNTekS7), pagesG201–G211.

Puri, A., Hardiyatmo, H. C., Suhendro, B., and Rifa’i,A. (2012). Determining additional modulus ofsubgrade reaction based on tolerable settlement for thenailed-slab system resting on soft clay. InternationalJournal of Civil and Environmental EngineeringIJCEE-IJENS, 12(03):32–40.

Puri, A., Hardiyatmo, H. C., Suhendro, B., and Rifa’i, A.(2014). Behavior of nailed-slab system on soft claydue to repetitive loadings by conducting full scaletest. In Proc. 17thIntrntl. Symp. FSTPT, Universityof Jember, pages 739–750.

Puri, A., Hardiyatmo, H. C., Suhendro, B., and Rifa’i, A.(2015). Pull out test of single pile row nailed-slabsystem on soft clay. In Proc. The 14th InternationalConference on Quality in Research (QiR), UniversitasIndonesia, Lombok, pages 63–68.

Puri, A. and Mildawati, R. (2019). Investigasi numerikperkerasan jalan sistem pelat terpaku terhadap variasidimensi struktur. BENTANG: Jurnal Teoritis danTerapan Bidang Rekayasa Sipil, 7(1):1–7.

Somantri, A. K. (2013). KAJIAN LENDUTAN SISTEMPELAT TERPAKU PADA TANAH PASIR DENGANMENGGUNAKAN METODE BEAM on ELASTICFOUNDATIONS (BoEF) DAN METODE ELEMENHINGGA. PhD thesis, Universitas Gadjah Mada.

Syarif, F., Adi, A. D., and Saputra, A. (2018). Studikarakteristik fondasi pelat tipis dengan pengaku tiang“+” pada tanah granuler melalui uji eksperimen dananalisis pemodelan menggunakan software abaqus.JURNAL SAINTIS, 17(2):66–78.

WARUWU, A. (2018). PERILAKU PEMAMPATANTANAH GAMBUT AKIBAT BEBAN TIMBUNANYANG DIDUKUNG SISTEM PELAT TERPAKU. PhDthesis, Universitas Gadjah Mada.


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Utilization of Agricultural Waste to Be Bioethanol Sources as a Solventon Paraffin Wax Crude Oil Issues

M. K. Afdhol1, F. Hidayat1 , M. Abdurrahman1 , H. Z. Lubis2 , R. K. Wijaya1 and N. P. Sari11Department of Petroleum Engineering, Faculty of Engineering , Universitas Islam Riau, Pekanbaru, Indonesia

2Department of Chemical Engineering, Institut Teknologi Medan, Jl. Gedung Arca No.52, Medan, Sumatera Utara,Indonesia

afdhol, fikihidayat, [email protected], [email protected], [email protected],[email protected]

Keywords: Agricultural Waste, Bioethanol, Solvent, Wax Paraffin.

Abstract: Crude oil is a chemical compound of saturated paraffin wax, aromatics, napthane, asphaltic, and resins indeedthis material produce wax deposits. Deposition of paraffin has potential to harmful the production due to theexistence of blockages, whether partial or the whole of the pipeline. Various techniques have been developedto overcome this problem; one of them is the use of solvents from agriculture waste. Incidentally, the materialsare easy to obtained and economical. Based on the Central Bureau of Statistics data, the agricultural waste inIndonesia recorded 5,883,730 tons/year for corn waste, 439,657 tons/year for pineapple skin waste, and 15.8tons/year for rice husk waste. The potential of agricultural waste can be used as a source of raw materials formanufacturing solvents by using bioethanol by ways of pretreatment, hydrolysis, fermentation, and distillationprocess. In addition, the result of several past studies shows that bioethanol made from pineapple skin produce8% of ethanol; bioethanol from corncobs produce 19-22% of ethanol; and bioethanol from rice husk produce14.4227% of ethanol. Therefore, it means that agricultural waste can be used as a source of bioethanol inmanufacture of solvent and could overcome the problem of paraffin wax.

1 INTRODUCTION

The decline in production is an obstacle for the oiland gas industry. Decreasing the rate of oil productionin wells will occur over time if the well is producedcontinuously (Wang et al., 2003). Paraffin is astraight chain consisting of 20 to 40 carbon atoms,paraffin is formed at low temperatures (Taraneh et al.,2008). There are several methods for dealing withparaffin wax, including preventive methods, namelyheating methods and chemical methods, one of themost effective methods is using hydrocarbon solvents(Khaibullina et al., 2016). Where one way to reduceparaffin wax is by injection of solvent as a waxinhibitor (Al-Yaari et al., 2011).

Organic waste processing has been widely used,such as: palm shells (Yuliusman et al., ; Yuliusmanet al., 2018; Afdhol et al., 2017), tea waste, coffeegrounds (Yuliusman et al., ), and inorganic waste fromplastic waste (Yuliusman et al., ). Bioethanol can beproduced from biomass containing cellulose throughvarious enzymatic processes and fermentation (Huet al., 2018). Bioethanol production from cellulose

waste has been developed, rice husk is one of therenewable raw materials for bioethanol productiondue to availability and cheap. The production processof bioethanol from cellulose raw materials is verycomplex so that it involves the preatretment process,hydrolosis and fermentation (Nanssou et al., 2016).

Based on the Central Bureau of Statistics data, theagricultural waste in Indonesia recorded 5,883,730tons/year for corn waste, 439,657 tons/year forpineapple skin waste, and 15.8 tons/year for ricehusk waste. Rice husk contains several organiccompounds, namely, lignin, cellulose, hemicellulose,nitrogen compounds, vitamin B and organic acids andcontains inorganic compounds in the form of silica(Ebrahimi et al., 2017). For rice husk used as rawmaterial for making ethanol can be seen in figure 1below.

In table 1 there is a composition of cellulose,hemicellulose and lignin from several agriculturalmaterials, it can be seen that corn stover containsabout 30-40% cellulose and lignin content 7-18,where the lignin content can inhibit the hydrolysisprocess.

Afdhol, M., Hidayat, F., Abdurrahman, M., Lubis, H., Wijaya, R. and Sari, N.Utilization of Agricultural Waste to Be Bioethanol Sources as a Solvent on Paraffin Wax Crude Oil Issues.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 315-321ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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Figure 1: Rice husks (Cai et al., 2018).

Table 1: Composition of Cellulose, Hemicellulose, andLignin from Different Sources of Lignocellulosic

Lignocellulosic Cellulose Hemicellulose Lignin(%) (%) (%)

Miscanthus 40 18 25Coastal 25 35.7 9-18

Corn Stover 35-40 17-35 7-18Wheat Straw 30 50 15

According to (Cai et al., 2018) several stagesof the biomass process will be carried out toproduce ethanol, namely pretreatment, hydrolysis andfermentation.

• Pretreatment, Biomass pretreatment is importantbecause to get high ethanol yield. The purposeof the pretreatment is to open the ligninselulosestructure so that cellulose is separated from ligninso that it is cellulose(Afdhol et al., 2019).

• Hydrolysis, Hydrolysis is the process of breakingdown existing polysaccharides in lignocellulosebiomass, namely cellulose and hemicellulosewhich will be broken down into sugar monomers.Cellulose hydrolysis that is done perfectly willproduce glucose. Hydrolysis can be carried outchemically using acid or enzymatically. Thereare several factors that influence the hydrolysisprocess, namely the first is carbohydrate contentof raw materials, pH of hydrolysis, hidrolysystime, temperature and pressure.

• Fermentation, Fermentation is a microbial activityin food ingredients so that the desired productis produced. Common microbes involved infermentation are bacteria, yeast and mold. Thefollowing are important factors that will affect theethanol yield and efficiency, that is on microbialphysiological conditions added to the media,which depends on the optimal conditions forspecific growth of the microbes to be used and

environmental conditions during fermentation,namely pH and temperature.

Solvent is a solution that is commonly used in thepetroleum world at various uses in their respectivefields and outside the world of petroleum as well asmany used solvents. In the table below is the useof solvents as paraffin inhibitors or as an inhibitor ofparaffin formation, and the classification of solventsis also used as a reference for making solvents in theresearch that will be conducted.

In table 2 there are several specifications ofsolvents used as paraffin inhibitors with the typeof solvent parasol II, where this table is used as areference specification for the manufacture of ethanoltype solvents.

Table 2: Solvent Specifications.

Parameter InformationColor ClearOdor Aromatic

Physical State LiquidForm LiquidpH 9

Boiling Point 257 F (125C)Flash Point 61 F (16.1C)

SG 0.8528Density 0.8527

Oil production wells that are Pertamina EP RegionSumatera Field Lirik by LS-124 (JOB PLP Lirik) hasparaffin properties with a fairly high wax content.Paraffin crystals from production oil begin to form attemperatures of < 180F at 100 ppm, at temperaturesbelow 180F it will increase to > 100 ppm, so thatforming wax crystals will be faster, the presence ofparaffin causes a decrease in flow efficiency (FE) dueto damage formation so that the productivity index(PI) also decreases. By injecting solvent (Xylene) andsurfactant oil production increases from 7 BOPD to43 BOPD.

Therefore in this study a laboratory analysis wascarried out, namely making bioethanol using biomasswaste derived from rice husk, corn skin and pineappleskin which will be processed so that it becomesa solvent to be able to inhibitor the occurrence ofparaffin deposits. wet oil into wet water which is oilthat can flow easily (Priyandono et al., 2007).


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2 THE PROBLEM OFDEPOSITION OF PARAFFINWAX

Paraffin is a mixture of hydrocarbon solid crystalsformed from linear or normal chains ranging fromC20 to C30 and consists of n-alkanes, iso-alkanes andnaphtenes. Wax is a high molecule of heavy paraffinfraction from crude oil which can be separated belowfrom crude oil pouring points.

In general, there are also two types of waxcontained in petroleum. First, microcrystallinewax consists of (n-alkanes) such as C20 to C50and Secondly, amorphous waxes consist of mostlyisoparaffin and naphthalene such as C30 to C60(Abdurrahman et al., 2018).

Deposits paraffin wax can be referred to as thedeposition of carbon material, which is insolubleor dispersed by crude oil under normal conditions.Normal conditions for maintaining crude oil in itsliquid form when temperature and pressure in thereservoir area are in the range of 70− 150 C and55-103 Mpa (Ridzuan et al., 2016).

Figure 2: effect of wax deposits shown above (a) measuringdrilling tubing, (b) intersection of the flow pipe, and (c) onthe inside of the pipe.

Paraffin settles can also be caused by the lossof volatile light in a crude oil, where the volatilefraction in the crude oil acts as a solvent for wax.When the fluid of this mixture begins to cool, theneach component of the wax will separate (becomenot dissolved) until finally the wax component whichhas a high molecular weight will solidify. The eventwhere the first wax crystals are formed at a certaintemperature is called the onset of wax crystallizationor better known as the cloud point or Wax AppearanceTemperature (WAT).

Up to 85% of world oil is affected by paraffin waxwhich settles and solidifies in the wellbore, in tubing,perforations, pump circuits, and rods, and along theflowlines and pipe line transfer systems (Figures 2a,2b, and 2c).

3 PARAFFIN WAX CONTROLTECHNIQUES

Deposition of paraffin wax causes equipment failure,upstream and downstream flow congestion, and lossof production, transportation capacity, and storage.Because paraffin deposits are waxed, thousandsof wells are closed, many pipelines are clogged,transport vessels are transported out of service, tanksare locked, and refinery equipment is closed at certaintimes globally, all resulting in loss of income.

In other conditions technically removingdeposition of paraffin wax in the review includes:Fused Chemical Reaction, Techniques, HeatApplications, Chemical Additives, Magnetic FluidConditioning (MFC) and Microbial Products(Abdurrahman et al., 2018).

3.1 Fused Chemical Reaction

For this method, various chemical substances areused to control waxy oil, such as diesel fuel, xylene,toluene, and naphthalene. These substances are usedas solvent to dissolve wax deposit in reservoir andincrease the well productivity and reservoir condition.There are two ways to inject solvent, continuousinjection and soaking injection. Continuous injectionis a method using a special injection pump, which setup on the wellhead. The chemical is injected intothe wellbore through the annulus. For the soakingmethod, a technique utilizing a small pump truckdropped the chemical into the wellbore through theannulus at a particular time (Abdurrahman et al.,2018).

3.2 Techniques

The practice of pigging is a way in which waxremoval is commonly accomplished in the field. Withthis method, deposited wax is techniques removedby launching a pipeline pig along the line to scrapewax from the walls as it is forced along by the oilpressure. This, however, poses the risk of forminga wax plug downstream from the pig as the scrapedwax accumulates and is compressed ahead of the pig.In such an event the pipeline could be lost.

The use of bypass pigs tries to address thisproblem. When the differential pressure across such apig becomes too high, because of the accumulation ofsolid wax and debris ahead of it, the bypass pig allowsliquid to flow through it and disperse the accumulatedsolid ahead. However, there is always the danger thatif pigging has to be temporarily suspended due toMechanical failure, or that if the pigging frequency

Utilization of Agricultural Waste to Be Bioethanol Sources as a Solvent on Paraffin Wax Crude Oil Issues

317

for a pipeline is not correctly optimized, that theresult will be a stuck pig and sizable production losses(Aiyejina et al., 2011).

3.3 Hot Water Method

Hot water is one of method used for maintaining thereservoir temperature. Furthermore, hot water whichinjected into the wellbore slow down the depositionwax process. It can be applied during completionand production. During completion, hot water iscirculated into the annulus using coiled tubing. Then,tubing string is heated to maintain the temperatureabove the pour point. In terms of production, hotwater is being used along with water injection tomaintain the pressure and temperature. The hotwater collected at the manifold for certain purposes.This technique can also be combined with chemicalmethod in order to prevent the appearance of wax inthe wellbore (Abdurrahman et al., 2018).

3.4 Biological Treatment

Biological wax removal methods have also beenstudied in recent years by researchers such as whodeveloped systems of paraffin-degrading bacterialconsortiums with nutrient supplements and growthenhancers for controlling paraffin deposition in thetubular and well bore region and in surface flowlines. Their results showed that their systems werehighly effective, eliminating the need for repeatedscrapings of wax over a period of several months.These methods are especially important because, ifsuccessfully implemented, they have the benefit ofproviding continuous control of wax deposition inpipelines through constant biodegradation, rather thanjust providing a very temporary fix (Aiyejina et al.,2011).

3.5 Microbial Method

The subject of this method is to decrease thecloud point or appearance of wax as apparentmolecular weight of crude oil. This method used themicroorganisms that alter the composition of crudeoil through bio-degradation. Crude oil in contact withthe microorganism (such as Pseudomonas aeruginosa,Bacillus subtillis, and Bacillus licheniformis) may bedegraded directly or break the long chain into shortchain.


Bioethanol making there are several important aspectsthat must be considered such as sample size, acidconcentration, reducing sugar content, stirring speed ,temperature and fermentation time this can affect theethanol content that will be produced.

So in this chapter we will also compare the effectof parameters that affect the results of ethanol fromthe raw materials of rice husks and corn cobs. Thefollowing is a detailed explanation of each of theparameters from each raw material.

4.1 Corn Cobs

During the hydrolysis process, hemicellulose acidis converted to cellulose. The results of the acidhydrolysis process showed that the smaller the sizeof the corn cobs particles (the bigger the mesh), thebetter the hydrolysis of the acid. This is shownin Figure 3, the hemicellulose level decreased withthe smaller size of the corn cobs particles and thecellulose content increased with the smaller particlesize.

Figure 3: The relationship between material content andparticle size during the process acid hydrolysis for 24 hours(Soeprijanto and Prasetyaningrum, 2008).

The effect of particle size on enzyme/acidhydrolysis on glucose conversion is shown in Figure4. The results showed that the smaller the size ofthe corn cob particles, the greater the conversion ofglucose obtained, because the small-sized particlesresulted in having a large contact area between corncob particles and enzymes/acid so that the processof hydrolysis of enzymes/acid to cellulose to glucosebecame larger and causing cellulose conversion toincrease glucose. The increase in conversion toglucose is also followed by an increase in the doseincrease of the enzyme/acid added. With the additionof the highest dose of enzyme 50 ml and variousparticle sizes (25, 50, 100 mesh), the conversion of


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cellulose to glucose increased by 43. 19%, 45.69%and 51.01%. So that the highest conversion that canbe achieved is 51.01% using the size of 100 mesh corncobs and 50 ml enzyme doses.

Figure 4: The relationship between glucose conversion andparticle size (Soeprijanto and Prasetyaningrum, 2008)

in the hydrolysis process, protons H+ fromHCL compounds will convert fiber groups from rawmaterials into free radical groups. the free radicalgroup will then be related to the OH− of H2SO4and produce glucose. when the need for H + fromHCL is sufficient to form radical groups from the rawmaterial, the glucose produced is maximal.

As well as the longer the fermentation time, thehigher the ethanol produced. this is because thelonger the fermentation time, the more glucose isreduced to alcohol, especially ethanol, but of coursethere is a maximum limit of microbial activity. It canbe seen from the result of the graph in figure 5 below(Fachry et al., 2013).

Figure 5: Effect of HCL molarity on ethanol levels atvarious fermentation times (Fachry et al., 2013)

4.2 Rice Husk

Rice husk has a lot of cellulose content which isaround 30% but the lignin content in rice huskis also large, which is around 15% where ligninbinds strongly to carbohydrates, so it can inhibit thehydrolysis of cellulose by enzymes. To obtain ethanolfrom rice husk, the pretreatment stage is needed. Thepretreatment stage is done to break the lignin bonds,so that cellulose can be hydrolyzed by enzymes thatcan produce glucose (Inggrid et al., 2011). One ofthe pretreatments that can be done is by using alkaliperoxide, so that the pretreatment process also adds tocosts in the ethanol production process.

At this stage, determining the effect of stirringspeed and determining the effect of H2O2concentration and temperature. Experiments onthe effect of stirring speed using 0% H2O2 and 2.5%at a temperature of 35C with variations in stirringspeed 0, 100, 150, 200, and 300 rpm. Experimentsto determine the effect of H2O2 and temperatureconcentrations were carried out with variations inH2O2 concentrations of 0%, 2.5%, 5%, 7.5%, and10% and temperature variations of 25C, 35C, and45C.

Experiment on determining the effect of stirring.Stirring uses a paddle because it has the largestcross-sectional area, so that with a small stirring speedcan provide a great stirring effect.

When H2O2 2.5% 150 rpm cellulose levels shouldincrease because the levels of lignin drop. Because,on a 100% basis when lignin levels decrease (thereis lost lignin), the cellulose level rises (even thoughthe amount is fixed). However, in the experiment,the cellulose content dropped because when thelignin bond was tried to be broken, there wassome cellulose which was damaged. the effectof variations in stirring, H2O2 concentration, andtemperature is easier to see when analyzing glucoselevels because the changes are greater than changesin lignin and cellulose. Moreover, in the manufactureof bioethanol, which has an important role is the levelof glucose.

Based on observation of figure 6 and ANOVAstatistical test, stirring has an effect on the level oflignin. At a speed of 150 rpm the level of lignin islowest because there is no dead zone (at 0 and 100rpm) and vortex (at 300 rpm), so that radical OHcontact with rice husk is good. Good contact resultsin more broken lignin bonds.

ANOVA statistical test results it can be ascertainedthat the temperature and H2O2 concentration havean effect on the glucose level produced, thehigher the concentration of H2O2, the higher the


319

glucose produced, but decreases at a 10% H2O2concentration. Meanwhile, changes in operatingtemperature from 25C to 45C do not have a largeeffect on cellulose levels.

Understanding wax aging mechanisms is also veryimportant to fully understanding the process of theformation of wax deposits in pipelines. Furthermore,understanding these mechanisms and predicting theCCN of particular crude oils would be helpful indetermining what chemical inhibitors would be mosteffective for preventing wax build-up in pipelinescarrying those oils.

The continuing research into methods ofinhibiting wax deposition and removing deposits hasthe potential of making the maintenance of crude oilpipelines significantly easier, as it becomes easierto optimize pigging frequency, to determine theminimum pressure required to restart gelled lines,or even to avoid the need for constant wax removalprocedures by finding a way to costeffectivelyimplement a promising method of control such as theuse of polar crude oil fractions or biological removalmeasures.

Initial testing of oil containing paraffin wax is veryimportant to determine the wax content contained inoil and the temperature at which wax begins to form.then testing was carried out to test the oil containingparaffin wax after adding a solvent to it, so these twotests were conducted to see the effectiveness of thesolvent to overcome the problem of paraffin wax.

As for the tests carried out to identify the contentof paraffin wax in oil, which is cloud point testing(ASTM D5771), cold point testing (ASTM D6371)(Products & Products, n.d.) and pour point testing(ASTM D97) (Methods & Oil, n.d.), this parametercan be used as a reference whether the solvent mixedwith oil containing paraffin wax can be handledproperly or not. and also other supporting testssuch as density (ASTM D1298) (Standard, n.d.),specific gravity (ASTM D1250) (Guide, 2004) and0API (ASTM D287) and viscosity (ASTM D445)(Viscometers et al., 2009). where all these parametersare the reference to the success of the solvent indealing with paraffin wax.

5 CONCLUSIONS

This work shows how the process of makingbioethanol from agricultural waste with optimalconditions such as particle size, enzyme / acidconcentration, reducing sugar content, stirring speed,temperature and fermentation time and also in thiswork provides another alternative in overcoming

the problem of oil containing paraffin wax usingbioethanol which produced from agricultural wasteso that it can prevent environmental damage andprovide a more efficient cost alternative in dealingwith paraffin wax deposits.

ACKNOWLEDGEMENTS

A Great Thanks To Universitas Islam Riau andPetronas Technology University for funding withnumber 469/KONTRAK/LPPM-UIR-9-2018 ForSupport In Writing This Paper.

REFERENCES

Abdurrahman, M., Ferizal, F., Husna, U., and Pangaribuan,L. (2018). Possibility of wax control techniques inindonesian oil fields. In AIP conference proceedings,volume 1941, page 020001. AIP Publishing.

Afdhol, M. K., Haris, F., Amiliana, R. A., Hanafi, A.,Ramadhan, I. T., et al. (2017). Production ofactivated carbon from coffee grounds using chemicaland physical activation method. Advanced ScienceLetters, 23(6):5751–5755.

Afdhol, M. K., Lubis, H. Z., Siregar, C. P., et al. (2019).Bioethanol production from tea waste as a basicingredient in renewable energy sources. Journal ofEarth Energy Engineering, 8(1):21–26.

Aiyejina, A., Chakrabarti, D. P., Pilgrim, A., and Sastry,M. (2011). Wax formation in oil pipelines: A criticalreview. International journal of multiphase flow,37(7):671–694.

Al-Yaari, M. et al. (2011). Paraffin wax deposition:Mitigation and removal techniques. In SPESaudi Arabia section Young Professionals TechnicalSymposium. Society of Petroleum Engineers.

Cai, W., Liu, R., He, Y., Chai, M., and Cai, J. (2018).Bio-oil production from fast pyrolysis of rice husk ina commercial-scale plant with a downdraft circulatingfluidized bed reactor. Fuel processing technology,171:308–317.

Ebrahimi, M., Caparanga, A. R., Ordono, E. E., Villaflores,O. B., and Pouriman, M. (2017). Effect of ammoniumcarbonate pretreatment on the enzymatic digestibility,structural characteristics of rice husk and bioethanolproduction via simultaneous saccharification andfermentation process with saccharomyces cerevisiaehansen 2055. Industrial crops and products,101:84–91.

Fachry, A. R., Astuti, P., and Puspitasari, T. G. (2013).Pembuatan bietanol dari limbah tongkol jagungdengan variasi konsentrasi asam klorida dan waktufermentasi. Jurnal Teknik Kimia, 19(1).

Guide, S. (2004). Standard Guide for Use of the PetroleumMeasurement Tables 1, 4, 1–7.


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Inggrid, M., Yonathan, C., and Djojosubroto, H. (2011).Pretreatment sekam padi dengan alkali peroksidadalam pembuatan bioetanol. In Prosiding SeminarNasional Te ni Kimia “Ke uangan”. Yogya arta.

Khaibullina, K. et al. (2016). Technology to removeasphaltene, resin and paraffin deposits in wellsusing organic solvents. In SPE Annual TechnicalConference and Exhibition. Society of PetroleumEngineers.

Nanssou, P. A. K., Nono, Y. J., and Kapseu, C.(2016). Pretreatment of cassava stems andpeelings by thermohydrolysis to enhance hydrolysisyield of cellulose in bioethanol production process.Renewable Energy, 97:252–265.

Priyandono, H., Amperianto, A., and Andrico, D.(2007). Upaya Peningkatan Produksi Minyak DiSumur Produksi Paraffinik Unuk Bisnis EP Lirik -Riau Menggunakan Inovasi Solvents dan Surfactants.Proceedings Simposium Nasional IATMI.

Ridzuan, N., Adam, F., and Yaacob, Z. (2016). Evaluationof the inhibitor selection on wax deposition formalaysian crude oil. Petroleum Science andTechnology, 34(4):366–371.

Soeprijanto, T. R. and Prasetyaningrum, I. (2008).Biokonversi selulose dari limbah tongkol jagungmenjadi glukosa menggunakan jamur aspergilusniger. Jurnal Purifikasi: Jurnal Teknologi danManajemen, 9(2):105–114.

Taraneh, J. B., Rahmatollah, G., Hassan, A., and Alireza,D. (2008). Effect of wax inhibitors on pour point andrheological properties of iranian waxy crude oil. Fuelprocessing technology, 89(10):973–977.

Viscometers, C. K., Density, R., Density, R., Density,R., Standards, V. O., Viscometer, C., and Oils, B.(2009). Standard Test Method for Kinematic Viscosityof Transparent and Opaque Liquids ( and Calculationof Dynamic Viscosity ) 1, 1–10.

Wang, K.-S., Wu, C.-H., Creek, J. L., Shuler, P. J., andTang, Y. (2003). Evaluation of effects of selected waxinhibitors on paraffin deposition. Petroleum scienceand technology, 21(3-4):369–379.

Yuliusman, A., K., M., and Sanal, A. (2018). Carbonmonoxide and methane adsorption of crude oilrefinery using activated carbon from palm shellsas biosorbent. IOP Conference Series: MaterialsScience and Engineering, 316(1).

Yuliusman, A., K., M., Sanal, A., and Nasruddin. (2018).CFD Modelling of Adsorption Behaviour in AGN Tankwith Polyethylene Terephthalate Plastic Waste BasedActivated Carbon. IOP Conference Series: MaterialsScience and Engineering, 316(1).


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The Effect of Regeneration Time of Biomass Activated Carbon using LowTemperature to Reduce Filtration Loss in Water-based Drilling Fluid

Mursyidah1, Nur Hadziqoh1, Arif Rahmadani1, Idham Khalid1 and Hasnah Binti Mohd Zaid2

1Faculty of Engineering, Universitas Islam Riau, Pekanbaru, Indonesia2Fundamental & Applied Sciences Department, Universiti Teknologi Petronas, 32610 Seri Iskandar, Perak Darul Ridzuan,

Malaysiamursyidahumar,[email protected], [email protected], [email protected],

[email protected]

Keywords: Activated Carbon, Oil Palm Shell, Filtration Loss, Regeneration of Activated Carbon

Abstract: Activated Carbon (AC) is a material that has porous structure and high surface area. If Activated Carbon haslong been opened to the air and interacts to the air, The surface of activated carbon can bind molecules from theliquid or gas phases by van der waals force. It can affect decreasing the ability of activated carbon to reducefiltration loss in water-based drilling fluid. The research has been carried out to increase the effectivenessof AC as an additive in drilling process by thermal regeneration of activated carbon using low temperature.This research using several samples that have various regeneration time by heated at 200C. The regenerationtimes are for 0 minute (AC non- regeneration process), 30 minutes, 60 minutes, 90 minutes, and 120 minutes.Scanning Electron Microscope (SEM) shows the surface morphology and porous size of the sample. Theresults show that filtration loss decrease with addition time respectively 15 ml, 13.7 ml, 13.1 ml, 12.6 ml, and12.1 ml. Regeneration process of activated carbon is one of the ways to reuse damaged activated carbon thatcan control filtration loss until 12.1 ml.

1 INTRODUCTION

The Drilling fluid also called drilling mud is one ofimportant process in the petroleum industry. Some ofthe petroleum industry faces challenges while drillingprocessing. One of the challenges is how to con-trol filtration loss in drilling operations. The wayto reduce filtration loss during the drilling process atwater-based mud can be added additive material intodrier mud to produce appropriate mud cake and cancontrol fluid loss (Paydar and Ahmadi, 2017). Somematerials used as additives to control filtration loss arebentonite, calcium carbonate, boehmite, nano metaloxide, nano zinc oxide, nano silica, carbon nanostruc-ture (El-Diasty and Ragab, ).

Activated Carbon (AC) is an amorphous solid thathas high surface area and porous structure (Sivakumaret al., 2012). It is widely used to adsorb the moleculesfrom liquid and gas phase. AC is used in many ap-plication due to unique porous characteristic such aswater filter (Siong et al., 2013), nuclear (Foo andHameed, 2012), pharmaceutical (ALKHATIB, 2016),agriculture (Nolan et al., 2015), gas and oil indus-try (Mahto, 2013). The adsorptive properties of the

AC is needed to adsorb the adsorbate of the water-based drilling fluid. The surface area of AC is excess1000 m2/g that result have powerful adsorptive prop-erties (Tadda et al., 2016). The smaller size of ACincreased the surface area. The quality of AC depen-dent on the raw materials and the activation process.AC is produced by various sources of carbonaceousmaterial such as coconut shell, sawdust, agriculturalactivities waste (McLean, 2003).

The adsorptive properties of the activated carboncan decrease when activated carbon has been longopened in the air and interacts with the air. Thesurface of activated carbon which is porous struc-ture adsorb organic component and any impurities.It is because of London dispersion force betweenmolecules. London dispersion force is a type of Vander waals force that can bind activated carbon withmolecules from liquid or gas phases. The Van derwaals force is a weak electrostatic force between un-charged molecules. The force have short range andsensitive in interaction between the carbon surfaceand the adsorbate molecules. The adsorption capacityof activated carbon is finite. If the porous surface ofactivated carbon adsorb any impurities from the air,

322Hadziqoh, N., Mursyidah, Rahmadani, A., Khalid, I. and Binti Mohd Zaid, H.The Effect of Regeneration Time of Biomass Activated Carbon using Low Temperature to Reduce Filtration Loss in Water-based Drilling Fluid.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 322-325ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

it can affect activated carbon loses its adsorption effi-ciency.

Regeneration also called reactivation is a processto clean the pores of activated carbon from organiccomponent or any impurities by reheated process. Re-generation process of activated carbon selectively canremove adsorbed organics from the pores of activatedcarbon (McLaughlin, 2005).

Some methods of regeneration of activated carbonare wet oxidation, supercritical fluid, classical solventregeneration low-temperature regeneration using mi-crowave (Calıskan et al., 2012), but on an industrialscale only thermal regeneration is used (Sabio et al.,2004).

Thermal regeneration is a method to destroy theadsorbed component from surface of activated carbonusing thermal process. It is desirable to restore the ad-sorptive capacity of the carbon and return the carbonto the formerly structure.

The objective of this research is to investigate theeffect of thermal regeneration of biomass activatedcarbon using low temperature to control filtration lossin the water-based drilling fluid.

2 EXPERIMENTAL

2.1 Materials

The raw material of Activated carbon in this researchis the oil palm shell from PT. Tunas Baru Lampung,Kecamatan Beringin, Kabupaten Pelalawan, Riau.Physical method used to produce activated carbon .There are Three general processes to produce acti-vated carbon. That are dehydration of water, car-bonization, and activation of the carbon.

2.1.1 Dehydration Process

Oil palm shell was prepared and has been cleaned. Inthis process, oil palm shell was dried in an oven at100 C for 1 hour.

2.1.2 Carbonization Process

Carbonization is a process of combustion of organicmaterial in the oil palm shell. This phase decomposescellulose into carbon by heated in an oven at 300 Cfor 1 hour. The objection of carbonization is to disap-pear volatile compounds in the noncarbon elements,hydrogen, and oxygen form. After that, the carbonmashed to size 6 300 mesh.

2.1.3 Activation Process

Activation is a process of breaking the carbon chainfrom the compound organic by heated in a furnace at1000 C for 1 hour.

2.2 Thermal Regeneration of ActivatedCarbon

The low temperature of the thermal regeneration withvarious time was carried out. The temperature used inregeneration is 200 C. Various time of regenerationare 0 minutes (non-regeneration process), 30 minutes,60 minutes, 90 minutes, and 120 minutes. In the ther-mal regeneration process, the sample was heated bythe oven for each time.


The focus study is to analyse the effect of regenera-tion time of activated carbon in controlling filtrationloss. Volume filtrate test was carried out using a filterpress set low-pressure low temperature (LPLT) for 30minutes. The test result shows at table 1.Table 1: Volume filtrate of the water-based drilling fluidwith various time of the regeneration.

No Sample Regeneration Timeof AC (Minute)

VolumeFiltrate

(ml)1 Sample 1 0 152 Sample 2 30 13.73 Sample 3 60 13.14 Sample 4 90 12.65 Sample 5 120 12.1

Sample 1 is a non-regeneration of activated car-bon. As can be seen the highest filtration loss isin non-regeneration activated carbon. The effectof regeneration process is reducing filtration loss indrilling-fluid. Generally, fluid loss decreases respec-tively with increasing regeneration time. Besed on ta-ble 1, the best time for regeneration process is 120minutes that can control filtration loss until 12.1 ml.In this condition, adsorbed contaminants or impuritiesremoved from porous of activated carbon.

The Grafik shows that cake thickness decrease re-spectively with addition regeneration time. The high-est cake thickness is in non-regeneration activated car-bon. This proves that regeneration of activated carboncan decrease cake thickness in drilling fluid.

The adsorption properties of activated carbon de-pend on its porous structure and pore size distribution

The Effect of Regeneration Time of Biomass Activated Carbon using Low Temperature to Reduce Filtration Loss in Water-based DrillingFluid

323

Figure 1: Grafik the effect of regeneration time to filtrationloss

Figure 2: Grafik of the effect of regeneration time to cakethickness

Figure 3: SEM image of AC with 0 minute regenerationtime

Figure 4: SEM image of AC with regeneration time 120minute

(Guo and Du, 2012). Figure 3 and figure 4 showsthe SEM image of activated carbon non-regenerationand activated carbon with regeneration for 120 min-utes. The result showed that the average of pore sizeis 0.67 µm non regeneration activated carbon and 0.53

µm with regeneration process for 120 minutes. Theactivated carbon adsorption is better with more devel-oped small pore size with large surface area than largepore size with small surface area.

4 CONCLUSION

Activated carbon is an additive material that can con-trol filtration loss in drilling fluid. However, acti-vated carbon should be regenerated when activatedcarbon is exhausted by impurities in the air. In thisresearch, the exhaust activated carbon (activated car-bon has been polluted by air) has been restored tothe formerly adsorption capacity by thermal regen-eration. The non-regeneration activated carbon hasmore filtration loss than activated carbon with regen-eration process. Filtration loss and cake thickness re-duce significantly with increasing regeneration timeof activated carbon. Activated carbon with regenera-tion time 120 minutes is the best material to decreasefiltration loss that can reduce filtration loss until 12.1ml.

ACKNOWLEDGEMENTS

The authors thank International Collaboratives Re-search Funding (ICRF) Universitas Islam Riau andUniversiti Teknologi Petronas for financial supportoffered through the project No. 437/Kontrak/LPPM-UIR-9-2018.

REFERENCES

ALKHATIB, A. (2016). The appropriate use of acti-vated charcoal in pharmaceutical and toxicologicalapproaches. Biomedical Journal of Scientific & Tech-nical Research, 5(2).

Calıskan, E., Bermudez, J., Parra, J., Menendez, J., Mahra-manlıoglu, M., and Ania, C. (2012). Low temperatureregeneration of activated carbons using microwaves:Revising conventional wisdom. Journal of environ-mental management, 102:134–140.

El-Diasty, A. and Ragab, A. Applications of nanotech-nology in the oil & gas industry: Latest trendsworldwide & future challenges in egypt. 2013.

Foo, K. and Hameed, B. (2012). Potential of activated car-bon adsorption processes for the remediation of nu-clear effluents: a recent literature. Desalination andWater Treatment, 41(1-3):72–78.

Guo, Y. and Du, E. (2012). The effects of thermal regenera-tion conditions and inorganic compounds on the char-acteristics of activated carbon used in power plant. En-ergy Procedia, 17:444–449.


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Mahto, V. (2013). Effect of activated charcoal on the rheo-logical and filtration properties of water based drillingfluids. International Journal of Chemical & Petro-chemical Technology (IJCPT), 3(4):27–32.

McLaughlin, H. (2005). Understanding activated carbon re-activation and low-temperature regeneration technol-ogy. International sugar journal, 107(1274):112–114.

McLean, S. (2003). Recent issues in assisted reproductionin the united kingdom. Clinical Risk, 9(1):18–22.

Nolan, N. E., Kulmatiski, A., Beard, K. H., and Norton,J. M. (2015). Activated carbon decreases invasiveplant growth by mediating plant–microbe interactions.AoB Plants, 7.

Paydar, P. and Ahmadi, M. (2017). Characteristics of water-based drilling mud containing gilsonite with boehmitenanoparticles. Bulletin de laSociete Royale des Sci-ences de Liege, 86:248–258.

Sabio, E., Gonzalez, J., Gonzalez-Garcia, C., Ramiro, A.,and Ganan, J. (2004). Thermal regeneration of acti-vated carbon saturated with p-nitrophenol. Carbon,42(11):2285–2293.

Siong, Y., Idris, J., and Atabaki, M. M. (2013). Performanceof activated carbon in water filters. Water Resources,pages 1–19.

Sivakumar, B., Kannan, C., Karthikeyan, S., et al. (2012).Preparation and characterization of activated car-bon prepared from balsamodendron caudatum woodwaste through various activation processes. Chem,5(3):321–327.

Tadda, M., Ahsan, A., Shitu, A., ElSergany, M., Arunku-mar, T., Jose, B., Razzaque, M., and Daud, N. (2016).A review on activated carbon: Process, applicationand prospects. Journal of Advanced Civil Engineer-ing Practice and Research, 2(1):7–13.

The Effect of Regeneration Time of Biomass Activated Carbon using Low Temperature to Reduce Filtration Loss in Water-based DrillingFluid

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Improving the Accuracy of Features Weighted k-Nearest Neighbor usingDistance Weight

K. U. Syaliman1,2, Ause Labellapansa2, Ana Yulianti21Informatics Engineering, Politeknik Caltex Riau, Pekanbaru, Indonesia2Informatics Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

[email protected], ause.labella, [email protected]

Keywords: Accuracy, Distance Weight, FWk-NN, K-NN, Vote Majority

Abstract: FWk-NN is an improvement of k-NN, where FWk-NN gives weight to each data feature thereby reducing theinfluence of features that are less relevant to the target. Feature weighting is proven to be able to improvethe accuracy of k-NN. However, the FWK-NN still uses the majority vote system for class determinationto new data. Whereby the majority vote system is considered to have several weaknesses, it ignores thesimilarity between data and the possibility of a double majority class. To overcome the issue of vote majorityat FWk-NN, the research will change the voting majority by using distance weight. This study uses a datasetobtained from the UCI repository and a water quality data set. The data used from the UCI repository are iris,ionosphere, hayes-Roth, and glass. Based on the tests carried out using UCI repository dataset it is proven thatFWk-NN using distance weight has averaged an increase about2%, with the highest increase of accuracy of4.23% in the glass dataset. In water quality data, FWk-NN using distance weight can achieve an accuracy of92.58% or has increased 2% from FWk-NN. From all the data tested, it is proven that the distance weight isable to increase the accuracy of the FWk-NN with an average increase about 1.9%.

1 INTRODUCTION

k-Nearest Neighbor or commonly known as kNN isone of the popular classification methods for dealingwith problems in the field of mining data, includingtext categorization, pattern recognition, classification,etc (Bhatia and Vandana, 2010; Jabbar et al., 2013;Rui-Jia and Xing, 2014; Sanchez et al., 2016; Zhenget al., 2017). This is because kNN has advantagesincluding simple methods, quite interesting, easy toimplement, intuitive, can be exploited in variousdomains, and is quite efficient (Wang et al., 2007;Garca-Pedrajas and Ortiz-Boyer, 2009; Ougiaroglouand Evangelidis, 2012; Feng et al., 2016; Pan et al.,2017; Sanchez et al., 2016; Song et al., 2017).

kNN still has weaknesses that make the resultsof accuracy remain relatively low, even more sowhen compared with other classification algorithms.(Danades et al., 2016; Tamatjita and Mahasta, 2016).The low accuracy value of kNN is caused by severalfactors. One of them is because each featurehas the same effect on determining the similaritybetween data. The solution is to give weight toeach data feature or commonly called Feature Weightk-NN (Kuhkan, 2016; Duneja and Puyalnithi, 2017;

Nababan et al., 2018).FWk-NN is proven to improve the accuracy of

the kNN method. It can be seen in the researchconducted by Duneja (2017) and Nababan, et al(2018) which gives weights for each data featureusing the Gain Ratio. In determining the class fornew data, FWk-NN still adopts the votes system,where the majority vote system ignores the similaritybetween data, and another problem is the possibleemergence of a double majority class(Gou and Xiong,2011; Yan et al., 2015; Syaliman et al., 2017).

The solution to the majority vote system problemhas been done by Mitani et al. (2006) . In thisresearch, it was proposed to make a method changein class determination for new data, initially used thevoting majority to be exchanged using local mean,so the class for new data is no longer based onthe majority class, but is determined based on thesimilarity of the local mean vector.The results of thisresearch proved that the local mean was able to reducemisclassification caused by the vote majority system.

Another solution to overcome the weaknessesin the vote majority system is to use the methodproposed by Batista & Silva (2009). In this researchit is recommended to use a distance weight while to

326Syaliman, K., Labellapansa, A. and Yulianti, A.Improving the Accuracy of Features Weighted k-Nearest Neighbor using Distance Weight.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 326-330ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

determine the new data class is based on the weightof the distance between the data, it has proved thatit is able to overcome the problem in the majorityvote system which ignored the similarity betweendata (Gou and Xiong, 2011; Syaliman et al., 2017).

Based on previous studies, the authors see that theaccuracy of the FWk-NN method can be improved,where to improve the accuracy of FWk-NN, in thisresearch the author will replace the vote majoritysystem with a distance weight system. It is expectedthat using distance weight is able to increase theresults of the classification.

2 FEATURE WEIGHTED K-NN(FWK-NN)

FWk-NN is a method developed to overcomeproblems in kNN that are sensitive to distancefunctions because of the sensitivity inherent inirrelevant features. FWk-NN is based on featureweighting (Chen and Hao, 2017).The details of theFWk-NN algorithm are as follows :

Step 1: Compute the weight of each feature using theGain Ratio. (Duneja and Puyalnithi, 2017;Nababan et al., 2018).

Step 2: Determine the value of k, k is the number ofnearest neighbor (Syaliman and A., 2015).

Step 3: Compute distance using equations :

D(x− y) =

√√√√ f

∑i=1

f wi× (xi− yi)2 (1)

where D(x− y) is the euclidean distance from x andy, f is the number of features, f w is the weight of thefeatures.

Step 4: Sort the distance between data from thesmallest to the largest (ascending) depend onthe number of k.

Step 5: Compute the number of each class based onthe nearest neighbor k.

Step 6: Make the majority class a new data class.

FWk-NN gives each feature a different weight,where features that have a greater influence on theclass will be given a feature weight greater than theweight of other features. Thus the less relevant weightcan be reduced by its influence (Kuhkan, 2016).

3 DISTANCE WEIGHTED K-NN(DWK-NN)

DWk-NN is also one of the improvements ofk-NN.Improve to the DWk-NN were carried outto overcome the problem of the vote majoritysystem from k-NN (Lidya et al., 2015).In k-NN,each nearest neighbor has the same influence inclass determination for new data, this is consideredirrational when viewed based on the similaritybetween data (Pan et al., 2016). The details of theFWk-NN algorithm are as follows:Step 1: Determine the value of k

Step 2: Compute distance using equations :

D(x− y) = (f

∑i=1

(xi− yi)r)

1r

(2)

D(x− y) is the distance between x and y, f is thenumber of features, r is lambda value (a positiveinteger). r = 1 is known as Manhattan / City Blockdistance, r = 2 is known as Euclidean distance and ifr = infinity is known as Chebyshev distance (Merigoand Casanovas, 2008; Labellapansa et al., 2016;Koteswara Rao, 2012).Step 3: Sort the distance between data from the

smallest to the largest (ascending) depend onthe number of k

Step 4: Compute the weight of the distance betweendata using equation (Batista and Silva, 2009):

dw =1

d(x,y)(3)

Step 5: Compute the average weights each dataclass based on closest k neighbors using theequation (4).

sum wc =kNN

∑i=1

wi,(c = cNNi ) (4)

Step 6: Select the class with the highest averageweight value, then make it as a class for newdata.

The workflow of DWk-NN is quite similar tok-NN. In K-NN class determination is based onmajority vote while in DWk-NN uses the highestnumber of average distance weight values betweendata.

4 PROPOSE METHOD

To further described the changes made to FWk-NNusing the distance weight will explain step by step inthis sub-chapter. The stages are in figure 1.

Improving the Accuracy of Features Weighted k-Nearest Neighbor using Distance Weight

327

Figure 1: Proposed Method

From figure 1, the modified Feature WeightK-Nearest Neighbor (FWk-NN) and Distance Weighthave several stages,which are :

Step 1: Compute influence of features by using GainRatio

Step 2: Compute the weight based on the gain ratiousing equation (5)

f wi =(Gi−Min(G))

Max(G)−Min(G)×1 (5)

where f wi is features weight-i, Gi is Gain Ratio-i,Min(G) is the minimum gain ratio, and Max(G) isthe maximum gain ratio.

Step 3: Determine the value of k

Step 4: Compute distance using equations (1).

Step 5: Sort the distance between data from thesmallest to the largest (ascending) based onthe number of k

Step 6: Compute the weight of the distance betweendata sorted by equation(3).

Step 7: Calculate the average weight for eachclass based on the nearest neighbor usingequation(4).

Step 8: Select the class with the highest averageweight value, then make it as a class for newdata.

Step 1 to 5 is the contribution from FWk-NN,while step 6 to step 8 are the steps of the distanceweight to determine the class for new data.


This research uses several datasets from the UCIMachine Learning repository, such as ionosphere,Haberman, hayes, glass, and iris. In addition, theproposed method is also tested using real data froma water quality status of Indonesia (Danades et al.,2016). The detail of the data can be seen in table 1.

Table 1: Detail of Data

Data Features Class Total DataIonosphere 34 2 351

Iris 4 3 150Hayes 4 3 160Glass 10 6 214

Water Quality Status 8 4 120

In this study used 10-fold cross-validation, and thevalue of k is only worth 1 to 10. The average accuracyof each data can be seen in figure 2.

Figure 2: Accuracy from Dataset

Based on figure 2,the proposed method orFWk-NN using distance weight has higher accuracythan FWk-NN, where the highest improved ofaccuracy obtained in Glass dataset is worth 4.23%,and the lowest improved of accuracy obtained in theiris dataset of 0.4%. From all dataset, the accuracyincrease is 2%.

Based on the testing by using the dataset from UCIwas knowing, the proposed method is better than theoriginal FWk-NN. To know with certainty whetherthe proposed method is better to make predictions inthe real data from water quality status in Indonesia, it


328

will be compared with original FWk-NN. Details ofthe test results can be seen in table 2.

Table 2: Comparison of Accuracy

kAccuracy

Best MethodFWk-NN(1) ProposedMethod(2)

1 94.20% 96.67% (2)2 92.50% 96.67% (2)3 95.00% 95.83% (2)4 90.00% 93.33% (2)5 92.50% 93.33% (2)6 87.50% 90.83% (2)7 90.80% 89.17% (1)8 88.30% 90.00% (2)9 89.20% 90.00% (2)

10 85.80% 90.00% (2)Avg 90.58% 92.58%

Based on table 2, the proposed method givesthe best prediction results in determining of Data.Although when the value of k is 7, the accuracy of theproposed method is decreased by 1.63%, overall theproposed method was able to improve the accuracyworth 2%, whereby the highest difference of accuracyis 4.20% when k is 10.

6 CONCLUSIONS

Referring result and discussion in the previouschapter can be concluded that distance weights canimprove the accuracy of FWk-NN. Based on the test,the highest accuracy is obtained at about 4.23% inthe glass data.Distance weights also have proven tobe successful in improving accuracy on water qualitystatus data. The highest accuracy occurs when k isten by 4.2% with the average increase is 2%.In alltests that have been carried out, it has proven that thedistance weights applied to FWk-NN provide betteraccuracy results than the majority vote system withthe average accuracy of all data used is 1.9%.

ACKNOWLEDGMENTS

High appreciation should be given to PoliteknikCaltex Riau and Universitas Islam Riau (UIR)especially Department of Informatics for their supporton the dissemination of this research work as well asthe facilities provided.

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Chen, Y. and Hao, Y. (2017). A Feature Weighted SupportVector Machine and K-Nearest Neighbor Algorithmfor Stock Market Indices Prediction. Expert SystemsWith Applications : 1-29.

Danades, A., Pratama, D., Anggraini, D., and Anggraini,D. (2016). Comparison of Accuracy Level K-NearestNeighbor Algorithm and Support Vector MachineAlgorithm in Classification Water Quality Status.International Conference on System Engineering andTechnology.

Duneja, A. and Puyalnithi, T. (2017). EnhancingClassification Accuracy of K-Nearest NeighborsAlgorithm Using Ga in Ratio. International ResearchJournal of Engineering and Technology (IRJET).

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Garca-Pedrajas, N. and Ortiz-Boyer, D. (2009). BoostingK-Nearest Neighbor Classifier By Means OfInput Space Projection. Expert System WithApplication37(7):.

Gou, J. and Xiong, T. (2011). A Novel Weighted Voting forK-Nearest Neighbor Rule. Journal of Computer6(5):833-840.

Jabbar, M. A., Deekshatulu, B., and Chandra, P.(2013). Classification of Heart Disease Using K-Nearest Neighbor and Genetic Algorithm. ProcediaTechnology, 10:85–94.

Koteswara Rao, M. (2012). Face Recognition UsingDifferent Local Features with Different DistanceTechniques. International Journal of ComputerScience, Engineering and Information Technology,2(1):67–74.

Kuhkan, M. (2016). A method to improve the accuracy of k- nearest neighbor algorithm. Internatonal Journal ofComputer Engineering and Information Technology.

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Nababan, A. A., Sitompul, O. S., and Tulus (2018).Attribute Weighting Based K-Nearest Neighbor UsingGain Ratio. Journal of Physics: Conference Series,1007(1).

Ougiaroglou, S. and Evangelidis, G. (2012). Fastand Accuratek-Nearest Neighbor Classification usingPrototype Selection by Clustering. PanhellenicConference on Informatics.

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Predicting of Oil Water Contact Level using Material Balance Modelingof a Multi-tank Reservoir

Muslim Abdurrahman1, Bop Duana Afrireksa2 Hyundon Shin2, Adi Novriansyah1,3

1Petroleum Engineering Department, Universitas Islam Riau, Pekanbaru, Indonesia2Department of Energy Resources Engineering, Inha University, Incheon, South Korea

3Department of Energy and Mineral Resources Engineering, Sejong University, Seoul, South [email protected], [email protected], [email protected], [email protected]

Keywords: Oil Water Contact, Material Balance, Tank Model, Sand Production, Prediction, Reservoir Modeling.

Abstract: Nowadays, the increase in water production becomes a problem in the oil and gas industry. Besides being aproblem, it also becomes extra energy to produce oil and gas. OWC is one of the keys for water productiondetermination for each layer. If the perforation at production well is at OWC or below OWC, the productionwill be 100% water. In general, the log is used to determine OWC. Besides with log, tank modeling fromthe material balance equation is also used to determine OWC. WH field located 15 km from Bangko Field inRiau. This primary field has high water production with 97% water cut. Before tank modeling starts, eachlayer needs to be analyzed based on its reserves, production cumulative and remaining reserves to determinethe productive layer, which can be developed in the future. Prediction can be done when history matching andcalibration process for both historical data and simulated data by software. Prediction ends in August 2021,which is the end of development contract in WH field. From the results, it can be determined that from C sand,the OOWC and COWC are at 2922 ft and 2883 ft with the cumulative oil production is 6.78 MMSTB. FromE sand also can be determined the OOWC at 2368 ft and COWC at 2325 ft with the cumulative oil productionis 14.57 MMSTB. From K sand, the OOWC is at 2002 ft and COWC at 1911 ft with the cumulative oilproduction is 13.5 MMSTB. L sand the OOWC is at 2243 ft and COWC at 2191 ft with the cumulative oilproduction is 29.17 MMSTB. From the analysis, K sand has the most significant OWC movement, which is91 ft and it is also validated with the current log data. This sand needs more care to maintain water production.

1 INTRODUCTION

Water production is one of the common problems ofthe past few years (Hudiman and Permadi, 2016).Water production is also one of the dilemmas in oiland gas industries, on the other side water is knownas an energy source in reservoir flow (Daneshy, 2006).Production well at the beginning of development hasa bigger oil production than water does. As time goesby, oil production will decrease because of severalthings, there are formation damage, pump mechanicalfailure, etc. This also caused by the increase in wa-ter production (increasing of water cut), where watermovement is faster than oil. With this water produc-tion, it can decrease production efficiency and profitfor the oil and gas company.

The method that has been used to maintain wa-ter production is by doing workover jobs, one of thejobs is by closing the zone, which is not productiveor it has 100% water cut which called water shut off

(Noordin, 2009). Water shut off method can be doneby using a mechanical method (packer), cementing(squeeze), or using chemical mixtures. These meth-ods can be used in order to maintain water productionso it will increase oil production with low expendi-tures (Stashin, 1989).

Oil water contact is the key to determine waterproduction when the production reaches 100% watercut, OWC must be at or above the perforation. Log-ging is the common method to determine OWC po-sition either the original one (OOWC) or even cur-rent position of OWC (COWC). Besides that, thereare several methods to determine OWC position, thereare RFT, DST, and other good tests. The followingmethods including logging data are costly and havesome limitations especially in certain reservoir issue(Ghahri et al., 2013). Material balance is a low-costapproach for determining OOWC or even COWC po-sitions (Nwaokorie and Ukakuku, 2012). By materialbalance also we can study the movement of OWC it-

Abdurrahman, M., Afrireksa, B., Shin, H. and Novriansyah, A.Predicting of Oil Water Contact Level using Material Balance Modeling of a Multi-tank Reservoir.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 331-336ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

331

self.Material balance is one of several methods used

estimating reserves for oil and gas reservoir and thusallows for making the critical decisions concerningdevelopment plans and strategies regarding the reser-voir. It is also the simplest way to express the conser-vation of mass in a reservoir. The material balance iszero-dimensional, meaning that it is based on a tankmodel and does not take into account the geometry ofthe reservoir, the drainage areas, the position, and ori-entation of the wells. The other uses of this conceptare to determine the size of an aquifer, encroachmentangle of the aquifer, estimate the depth of fluid con-tact, etc (Dake, 1983).

The material balance equation mathematically de-fines the different producing mechanisms which ef-fectively relates the reservoir fluid and rock expansionto the substance of fluid withdrawal. Several methodshave been developed and published applying the ma-terial balance equation to the various types of reser-voirs and solving the equation to obtain the initial oilin place (N) and the ratio of the initial gas to oil (m)in the reservoir (Havlena and Odeh, 1963). For wa-ter drive reservoir diagnostic plot, Campbell plot isused to determine the energy of the aquifer and theOOIP itself by using F/Eowf vs Np plot (Campbelland Campbell, 1978).

The general material balance equation for an oilreservoir is expressed as:

F = NEt +We (1)Where the underground withdrawal F equals to the

production of oil, water, and gas corrected to reservoircondition:

F = Np(Bo −Bg ∗Rs)+Bg ∗ (Gp −Gi)

+(Wp −Wi)∗Bw(2)

And the original oil in place is N stock tank barrelsand E is the unit per unit expansion of oil (and its dis-solved gas), connate water, pore volume compaction,and the gas cap:

E = (Bo −Boi)+(Rsi −Rs)∗Bg +m

∗Boi

(Bg

Bgi−1

)

+(1+m)∗Boi

∗(

SWc ∗Cw +C f

1−Swc

)

∗ (Pi −P)

(3)

WH field is a primary field, which located in RiauProvince. This field discovered in July 1972 with the

OOIP is 184.457 MMSTB. In February 2017, the av-erage water cut of this field reached 97%. High watercut becomes a dilemma in this field.

The purpose of this paper is making the tankmodel of each most productive layer from WH fieldby using IPM – MBAL software and predict the OWCmovement until August 2021, which is the end of thecontract for the WH field development. The predic-tion is used to determine the sand, which has a sig-nificant movement of OWC. The log data is neededto validate the OWC movement for each productivesand.

2 GEOLOGY AND RESERVOIRCONDITION

WH is located at Central Sumatera Basin, Indone-sia, at Bangko Area in Riau Province. This for-mation consist of Brown Shale Formation at Pe-matang Valley as the source rock. The lithofacies ofBrown Shale Formation is carbonaceous and algal-amorphous (Katz and Mertani, 1989). Where algal-amorphous is oil prone at the upper and middle partof Brown Shale Formation (Aman, Kamba, and Ran-gau). Carbonaceous is the gas and light condensateprone, which located at Kiri, Aman, Kamba, and Ran-gau. The transition facies between algal-amorphousand carbonaceous is also located at Aman, Kamba,and Rangau. Pematang group (fine and medium sand-stone from Upper Red Formation) and Sihapas Groupcome as reservoir rock after the primary migration tothe hinge margin basin caused by the Pematang to-pography, which is asymmetric. The result is, reser-voir rocks along steep fault scarp margin and hingemargin, which formed Telisa, Duri, Bekasap, Bangko,Pematang, and Petani formation with a total of thick-ness reached 3300 ft.

Figure 1: WH Field Map


332

WH field reservoir properties from the log data,core, single well-tracer, and volumetric data are asfollows:

Table 1: WH Field Reservoir Properties

Formation GOR, SCF/STB 26.4Oil Gravity, API 34.5Gas Gravity, sp. Gravity 0.8Water Salinity, ppm 20000Connate Water Saturation, % 21Porosity, % 25

3 METHODOLOGY

In this section, the methodology, which applied inthis paper will be discussed in order to build the sandpredictive material balance equation models by usingIPM – MBAL software.

Figure 2: General IPM - MBAL Workflow

3.1 Data Gathering

Proper data acquisition has to be carried out in or-der to build a good material balance equation modelor MBAL model. Most of these data are acquiredat the early phase of field development. Either us-ing well tests (RFT, MDT, Swab, PBU, etc) or coretest (RCAL or SCAL) data acquired are, Pressure,Production data, PVT, Rock properties, OOIP fromthe volumetric calculation, and PV fraction vs depth.Porosity, permeability, and water connate saturatedalso are obtained from existing well logs and coredata. Original oil in place (OOIP) obtained by calcu-lating the rock properties (porosity, water connate sat-uration, formation volume factor) and net pay thick-ness and area from well-logs to get the OOIP math-ematically. Effort should be made in order to under-stand the uncertainties related to the reservoir param-eters, which used to calculate OOIP. In cases when theMBAL initialize volumes are different from the vol-umetric calculated volumes, basically due to the highuncertainty of the MBAL data which is used in thesimulation.

3.2 Sand Selection

Sand selection is needed to filter which sand is suit-able to model and develop in the future. The screen-ing criteria of this section initial volumetric OOIP,production cumulative, and remaining reserves. Inthis case, when the remaining reserves are too low fora layer, it will not profit to develop. C, E, K, and Lare the selected sand based on these screening crite-ria, which are suitable to model and develop.

3.3 Material Balance Model

The understanding of building a material balancemodel for each productive layer is needed to make asand predictive model in material balance. It requiresbasic and fundamental knowledge related to the reser-voir structure, type, and the aquifer effect to the reser-voir itself. Several analytical models of the aquiferwere tested in a bid to model the geometry of thereservoir. Carter Stacy, Van Everdingen, Van Everdin-gen modified, Hurst-Van Everdingen modified, etcare the available aquifer models at the software. Af-ter aquifer model selection (in this case, Hurst-VanEverdingen modified model was selected), the modelalready established to connect the reservoir volume.The predicted OOIP which generated by the softwarecan be compared with the volumetric OOIP. In thiscase, the generated OOIP is matched to the volumetricOOIP for all layers (see Fig 2 for initialization modelplots).

3.4 History Matching

With the aquifer model being the key of uncertainty,encroachment angle, ReD, aquifer permeability, andinner/outer ratio were regressed upon the reservoirpressure history matching process and productiondata assuming reservoir volume reproduced to stocktank condition. The regression needs to be done re-peatedly until the deviation is lower than 5. It needsto be done in order to validate the model due to theaquifer model uncertainties.

3.5 Simulation

At this part, reservoir pressure over time is simu-lated from the production history data. This simulatedreservoir pressure is compared to the measured reser-voir pressure at the field from the input data to seethe MBAL model could replicate the actual or currentreservoir pressure which is given by the same reser-voir energy and properties (see Fig 3 to Fig 6). Sim-

Predicting of Oil Water Contact Level using Material Balance Modeling of a Multi-tank Reservoir

333

ulated OWC from the MBAL were calibrated withlogged OWC for modeled sands (Fig 7).

Figure 3: IPM – MBAL Initialization Output

Figure 4: Pressure and Cumulative Production HistoryMatch from K Sand

Figure 5: Pressure and Cumulative Production HistoryMatch from L Sand

Figure 6: Pressure and Cumulative Production HistoryMatch from E Sand

3.6 Calibration

Material balance model calibration is needed to matchthe end of history matching point with the prediction

Figure 7: Pressure and Cumulative Production HistoryMatch from C Sand

starting point in order to make prediction more vali-dated. In this section, pseudo-prediction will be gen-erated by using the prediction tool. Since the goal is topredict using tank model, a well prediction model wasnot used in this case. For the constraint, history pro-duction rate and time will be used to generate pseudo-prediction to calibrate the model. Once both pointsmatched, prediction can be generated next.

3.7 Prediction

After the model already matched and validated, thenext thing is the prediction of the field performance.Prediction generated until the end of contract of thisfield development (August 2021). The models werefurther calibrated by running pseudo-prediction forexisting sands. Results were compared with the out-come from another method in determining the heightof OWC as shown in Fig 8.

Figure 8: OWC Prediction

4 RESULT

Various results were discussed during the study whichinvolved saturation reservoir with concurrently oilproduction from the oil rim. Well logs will be adoptedto verify results from MBAL models. Table 3 shownmaterial balance results the OWC from MBAL hascompared well with the log data. For the productionforecast, it predicted using no well prediction which


334

assumpted the sand production rate is decline natu-rally due to the pressure loss at the reservoir. Pre-diction rate will be generated by software as longthe reservoir pressure and aquifer is enough to pro-vide energies. From the result, K sand has significantmovement of OWC, the contact moves from 2002 ftat 1973 to 1911 ft at 2012. This 91 ft movementin 48 years from prediction makes this sand needsmore concern due to the water production mainte-nance. The other sand has a certain movement lessthan 55 ft in 48 years.

Table 2: Predicted OOWC vs Log OOWC

SandMBALOOWC(ft)

LogOOWC(ft)

Error (%)

C 2922 2925 0.103E 2368 2366 0.085K 2002 2002 0.000L 2243 2246 0.134

Table 3: Predicted COWC vs Log COWC

SandMBALCOWC in2021 (ft)

MBALCOWC in2014(ft)

Log COWCin 2014 (ft)

C 2922 2925 0.103E 2368 2366 0.085K 2002 2002 0.000L 2243 2246 0.134

5 CONCLUSION ANDRECOMMENDATION

• Sand predictive Material Balance Models havebeen proved to be a quick alternative tool to de-termine OWC movement as reservoir simulationin the sand analysis.

• Good surveillance acquisition data is needed toprovide input data. The accuracy of each dataneeds to be concerned as pre-requisite to makevalidate models.

• Sand K has the most significant move of OWCdue to water production maintenance. It reached91 ft in 48 years of prediction. The other sandshave certain movement below 55 ft.

• Lift tables are needed and also validated to makewell predictive models.

REFERENCES

Petroleum Experts IPM-MBAL Manual.Campbell, R. A. and Campbell, J. M. (1978). Mineral prop-

erty economics. Petroleum Property Evaluation, 3.Dake, L. P. (1983). Fundamentals of reservoir engineering.

Elsevier.Daneshy, A. A. (2006). Selection and execution criteria for

water-control treatment. In SPE Symposium and Ex-hibition on Formation Damage Control, Los Angeles.

Ghahri, P., Berthereau, G., Milner, S., Orta, M. E., Sikan-dar, A. S., et al. (2013). Estimated fluid contact usingmaterial balance technique and volumetric calculationimproves reservoir management plan. In SPE OffshoreEurope Oil and Gas Conference and Exhibition. Soci-ety of Petroleum Engineers.

Havlena, D. and Odeh, A. S. (1963). The material balanceas an equation of a straight line. Journal of PetroleumTechnology, pages 896–900.

Hudiman, A. and Permadi, B. Y. (2016). Analisa penentuanlaju air produksi yang optimum untuk memperlambatwater coning di lapisan tipis. JTMGB, 10(1):17–22.

Katz, B. J. and Mertani, B. (1989). Central sumatra — ageochemical paradox. In Proc 18th Indon Pet AssocAnn Con, volume 1, pages 403–425, Jakarta.

Noordin, F. M., e. a. (2009). Case study: Water shut offmechanism in small, remote platform-process & chal-lenge. In SPE European Formation Damage Confer-ence, pages 27–29, Netherlands.

Nwaokorie, C. and Ukakuku, I. (2012). Well predictive ma-terial balance evaluation: A quick tool for reservoirperformance analysis. In SPE Nigerian Annual Inter-national Conference and Exhibition, Abuja.

Stashin, K. (1989). An analytical approach to determiningoil/water contact rise at utikuma field. In 40th AnnualTechnical Meeting of The Petroleum Society, Banff.Petro Society of CIM.

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APPENDIXAPI : American Petroleum InstituteBo : Current oil volume factorBoi : Initial oil volume factorBg : Current gas volume factorBw : Current water volume factorCf : Formation compressibilityCOWC : Current Oil Water ContactCw : Water compressibilityDST : Drill Stem TestEt : Total expansion of fluidF : FahrenheitFT : FeetGi : Cumulative gas injectionGp : Cumulative gas productionIOIP : Initial Oil in PlaceIPM : Integrated Production ModelingM : Gas oil RatioMBAL : Material Balance Modeling

SoftwareMSTB : Thousand Stock Tank BarrelMMSTB : Million Stock Tank BarrelN : Initial Oil in PlaceOOIP : Original Oil in PlaceOOWC : Original Oil Water ContactOWC : Oil Water ContactPBU : Pressure Build-Up Testppm : Part per MillionPSIG : Pound Square Inch GaugePV : Pore VolumePVT : Pressure Volume TemperatureRCAL : Routine Core AnalysisRFT : Repeat Formation TestRs : Current solution gas oil ratioRsi : Initial solution gas oil ratioSCAL : Special Core AnalysisSCF : Standard Cubic FeetSTB : Stock Tank BarrelSwc : Connate water saturationWe : Water influxWi : Cumulative water injectionWp : Cumulative water production


336

Chip Formation and Shear Plane Angle Analysis on Carbon SteelDrilling using Solid Carbide Tools

Rieza Zulrian AldioDepartment of Mechanical Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

[email protected]

Keywords: Carbide Drill Bit, Chip Formation, Drilling, Shear Plane Angle

Abstract: The analysis of the chip formation and shear plane angle from the drilling process are conducted as a mean todetermine the best drill bit used. Both aspects that influenced by the drill bit will define the machinability andquality of the machining process. The aim of this experiment is to determine which is the best drill bit to use.There are nine types of drill bit used in this experiment. All of the drills used are made of the solid carbide.The chips are obtained from the drilling conducted by HPMT Industries Sdn Bhd. There are several types ofchips from the experiment, such as continuous, discontinuous and segmented chip. It is found that the chip’sthickness and the helix angle of the drill bit affect the value of the shear plane angle created. Since all drillbits are made of the same material, the helix angle of the drill bit become the main factor of choosing the bestdrill bit because of the relationship between it influenced the shear plane angle value.

1 INTRODUCTION

One of the workpiece that is frequently and generallyused in the machining process is steel. There are sev-eral types of steel used in the machining process suchas stainless steel, carbon steel and others. Each typeof steel has a different nature. Stainless steel is themost common type of steel used in the manufactur-ing industry. For example, corrosion resistant prop-erties of stainless steel is due to a chromium contentof 10-12 percent of the total weight of stainless steel(Kalpakjian and Schmid, 2006). Then there is alsocarbon steel which is also often used in industry be-cause of its low cost and ease of manufacture (Smithand Hashemi, 2006).

One of the type of machining process which is of-ten used for steel is drilling process. Drilling pro-cess is the process by which drill bit will result in ahole in the workpiece through direct contact betweenthe tool and the workpiece surface. Drilling processis one of the most important machining processes inthe automotive and aircraft industries. (El-Sonbatyet al., 2004) states that the industries required morethan 100,000 holes for small aircraft engines, mostlyused as a fastener. There are several forms of chipsthat could resulted from the drilling process (Shar-man et al., 2008). For example, the long continuouschips are bad shape because chips will stick to thesurface of the tool and affect the performance of the

tool while performing the drilling process (Feng et al.,2005). Long chips also make the chip evacuation be-come more difficult and cause the drill to require morepower, which would increase the risk of broken drill(Batzer et al., 1998). For this reason, the form andevacuation process of the chips have important roles.

Chips will have direct contact with the flutes onthe twist drill during the drilling process. The geome-try of the tool used will have an impact on the processof moving chips (Abrao et al., 2008). Because of that,the shape that commonly found has curls form, whichis according to the flute’s shape. (Bakkal et al., 2005)in experiments on the chip’s morphology of drillingmetal glass found that there are six forms of chipssuch as powder, short ribbon, long ribbon, long spi-ral, long twisted ribbon and fan shape.

Movement of the chips on the flutes will causebending moments which can lead to chip fracture.(Sakaurai et al., 1998) states that the chip will bebroken when the friction torque between the holewall and chip’s surface is beyond the chip’s torque.The size of the chip will have impact on the sur-face roughness, which will produce rougher surface(Batzer et al., 1998). The performance of a tool canbe determined by the shape of the resulting chips.

Therefore, apart from the chip removal process,the shape and length of chips resulted from thedrilling process should be reviewed in order to accom-plish better performance of the drilling process. In

Zulrian Aldio, R.Chip Formation and Shear Plane Angle Analysis on Carbon Steel Drilling using Solid Carbide Tools.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 337-341ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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addition to differences in material and machining pa-rameters on the tool used, the difference in the shapeor geometry of the tool will affect the shape of the re-sulted chips (Wan and Tang, 2011). Geometric dif-ferences such as rake angle or helix angle and thepoint angle will affect the shape, size and length ofthe chips. Point angle, helix angle and size of fluteson the tool will affect the movement of chips (Fenget al., 2005).

So in this experiment will be analyzed on the frag-ments resulting from each type of device used. Eachtool has a different geometry and analysis on the re-lationship between the different tool geometry andshape of the pieces will also be done. Then the re-lationship between the rake angle of the tool with theresulting shear plane angle will also be reviewed.

Figure 1 shows the geometry of the typical drillbit used in machining.

Figure 1: Drill Bit Geometry

2 EQUIPMENT

The workpiece used is carbon steel S45C. CNC ma-chine is used for the drilling process. The diameter ofall cutting tool used is 8 mm. All of them are not us-ing coolant. There 9 drill bits, each has different helixangle value. Figure 2 shows the holes produced fromthe drilling process. From the process, there are 600holes produced by using each cutting tools. Then fig-ure 3 show the CNC Drilling Machine Makino S-33that used in the drilling process.

3 METHODOLOGY

Every drill bit will drill 600 holes with same machin-ing parameters, shown in table 1. Then the chipsare taken randomly between the drilling process.the chip’s thickness measured using vernier calliper.Thus, using the thickness ratio and helix angle value,the shear plane angle value can be found. Theseformulas are used for the calculation.

Figure 2: Carbon Steel S45C

Figure 3: Makino S-33 CNC Machine

Figure 4: Drill Bits Used In The Drilling Process

r =totr

(1)

tanΦ =r cosα

1− r sinα(2)


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Table 1: Machining Parameters Used

Cutting speed Feed rate Depth of cut140 m/min 0.16 mm/rev 42 mm


4.1 Chip Formation

From the chips sample, there are several forms of chipresulted from each type of cutting tools. Long heli-cal continuous chip is always resulted in the drillingprocess. There are also discontinuous and segmentedchip resulted. But there are only two cutting tools re-sulting segmented chips. Beside the shape, the lengthand thickness of the chips are also measured. Thelength of the chips are between 3 to 6 cm. Figure 5below shows the sample of the chips.

Figure 5: Type of Chips Resulted From The Drilling Pro-cess

There are several types shapes of the chips re-sulted. With continuous being the dominant one,while some discontinuous and segmented are also re-covered. There are no real significant difference in theshape due to the similarity value of the rake angle.

For the thickness value however, the differencesbetween all the chips resulted from each cutting toolsare quite similar. This is due to the similarity of thefeed rate used in the drilling process. Table 2 show thevalue from the maximum length and thickness mea-surement of the resulted chips.

Chips from cutting tool C8 has the least maximumlength of all the chips. As for he longest is from

the cutting tool WT. Cutting tool ZC produce longestchips at 4.5 mm, and this cutting tool is the cuttingtool that produce the most many long continuous he-lical chips. Long continuous chips also resulted fromthe use of all the cutting tools. But only ZC produce itas the most dominant chip’s form. For the segmentedchips, there are two cutting tools produced it, they areHT and MT. Using MT, there is also produced longcontinous string chips. As for the cause of this oc-curence, is likely due to the high cutting speed andinfluenced by the wear condition of the cutting tools.

From table 2, it can also show the value of the chipthickness. The small difference might happened dueto the similar use of machining parameter,, especiallyfeed rate that affect the chip thickness. There is nochange in the parameter, which is making unclear tocompare the chip thickness resulted from each cuttingtools. Thus, the similarities between the values areobtained.

4.2 Surface Integrity of the Chip

Observation of the surface of the resulting chips werealso conducted. The both of the chip surface was ob-served using an optical microscope. Of all the pieces,it is found that many chips with good machined sur-face (outside) or good quality. However, there is alsothe outer surface of chips having a surface shape isnot good, as there is friction and cracked. The condi-tion of the chip surface in contact with the workpiecehas a resemblance to each other. There are traces ofthe strain acting on the surface of the chip, which oc-curred during the drilling process. The traces are re-sulted by the cutting tools.

From observation, it can be seen that the shapeof the surface of the chips of each tool has a shapesimilar or even identical. Due to the dominant circu-lar chip, it is difficult to observe the inner part of thechip. To do the observation of this part, the discontin-uous chip type is observed so the inner surface can beobserved. From the figure below, it is shown that thechips surface from HPMT DRNiTiCo has poor condi-tion than the others. It can occured due to the cuttingtools became dull (due to the wear).

4.3 Shear Plane Angle Analysis

Feed rate is used as the replacement for the to.Thereis a relationship between shear plane angle and rakeangle. Because rake angle will define the sharpnessof the cutting tool. Rake angle will affect the shearplane angle resulted. For drilling process, the rakeangle is replace by the helix angle. Because helix an-gle (on flute) is the part that directy cut or touch with

Chip Formation and Shear Plane Angle Analysis on Carbon Steel Drilling using Solid Carbide Tools

339

Table 2: Chip’s Length And Thickness Measurement

No Drill Bit Max Length (cm)Thickness (mm)

1 2 3 Average

1 ZC 4.5 0.23 0.25 0.25 0.24

2 HT 4 0.29 0.24 0.23 0.25

3 SU 4.2 0.21 0.24 0.25 0.23

4 MT 4.4 0.26 0.2 0.21 0.22

5 WT 6 0.27 0.31 0.29 0.29

6 HPMT DR45 3.8 0.24 0.26 0.23 0.24

7 HPMT DRNiTiCo 3.5 0.31 0.29 0.25 0.28

8 C4 4.5 0.24 0.27 0.26 0.26

9 C8 3 0.21 0.22 0.25 0.23

Figure 6: Chips of Drill Bit C8

Figure 7: Chips of MT

the workpiece’s surface and resulting the chip. Thechip also flow through this part. So in this case, helixangle is related to the shear plane angle.Table 3 showsthe rake angle and shear plane value.

From the table 3, it is known that the least thick-ness will cause the shear plane angle to increase. That

Figure 8: Chips of HPMT DRNiTiCo

shows the relationship between thickness and shearplane angle. Beside that, rake angle also influence theshear plane angle. It is seen that the smaller rake an-gle tend to produce smaller shear plane angle, exceptfor C4 and C8. The value of the shear angle also willdecreased if the rake angle is too large, such as WTshow. This means that the rake angle value should beoptimized to get the optimum value of the shear planeangle.

The chip thickness has more clear relationshipwith the shear angle. The smaller thickness will re-sulting the bigger shear plane angle. As figure 6,7 and8 shows that the optimum value of the shear plane isaround rake angle with 30.

5 CONCLUSION

From the measurement and observation of the chip,it is concluded that there are several type of chip


340

Table 3: Shear Plane Angle Value of Every Drill Bit

No Drill Type Chip Thickness (tc)(mm) Cutting Ratio Helix / Rake Angle Shear Plane Angle

1 ZCC 0.24 0.67 30.21 41.14

2 Hitachi (HT) 0.25 0.64 28.67 39.02

3 Sumitomo (SU) 0.23 0.7 30.16 43.03

4 Mitsubishi (MT) 0.22 0.73 30.69 45.02

5 Walter Titex (WT) 0.29 0.55 33.17 33.37

6 HPMT DR459670800 0.24 0.67 30.22 41.14

7 HPMT DRNiTiCoD08800 0.28 0.57 30.16 34.63

8 Coromant 460 (C4) 0.26 0.62 26.24 37.46

9 Coromant 860 (C8) 0.23 0.7 26.41 42.32

resulted such as continuous, discontinuous and seg-mented chip. Continuous is the most dominant chipof all, since it appeared on each tool. The segmentedonly appeared on HT and MT, and could occured dueto the tool wear and randomness of the chip collectedfrom the drilling process.

Shear plane angle is calculated and shows that ithas strong and clear relationship with chip thicknessvalue. As for the rake angle, it shows that the opti-mum value of rake angle must be specified if wantto increase the shear plane angle. Meaning also toreduce the chip thickness to accomodate better chipevacuation during drilling process.

ACKNOWLEDGEMENTS

The author would like to give an acknowledgment toHPMT Industries Sdn. Bhd. members, especiallyResearch and Development Department for their co-operation in data. The author also thanks UniversitiKebangsaan Malaysia as the organisation that providetheir facilities for the research’s purpose.

REFERENCES

Abrao, A. M., Rubio, C., C., J., Faria, P. E., and Davim,J. P. (2008). The effect of cutting tool geometry onthrust force and delamination when drilling glass fibrereinforced plastic composite. Materials and Design.29:508 513.

Bakkal, M., Shih, A. J., McSpadden, S. B., Liu, C. T., andScattergood, R. O. (2005). Light emission, chip mor-phology, and burr formation in drilling the bulk metal-lic glass. International Journal of Machine Tools andManufacture 45 741 152.

Batzer, S. A., Haan, D. M., Rao, P. D., Olson, W. W., andSutherland, J. W. (1998). Chip morphology and holesurface texture in the drilling of cast Aluminum alloys.Journal of Materials Processing Technology 79.

El-Sonbaty, I., Khashaba, U. A., and Machaly, T. (2004).Factors affecting the machinability of GFR/epoxycomposites. Compos Struct ;63(34):329 38.

Feng, K., Ni, J., and Stephenson, D. A. (2005). Continu-ous chip formation in drilling. International Journalof Machine Tools & Manufacture 45.

Kalpakjian, S. and Schmid, S. R. (2006). ManufacturingEngineering and Technology. Upper Saddle River:Pearson Prentice Hall.

Sakaurai, K., Adachi, K., and Hanasaki, S. (1998). Break-ing mechanism of chips in inter- mittently deceleratedfeed drilling of aluminum alloys. Japan Institute ofLight Metals 48 (4) 195 198.

Sharman, A. R. C., Amarasinghe, A., and Ridgway, K.(2008). Tool life and surface integrity aspects whendrilling and hole making in Inconel 718. Journal ofmaterials processing technology. 200:424 432.

Smith and Hashemi (2006). Foundations of Materials Sci-ence and Engineering.

Wan, Z. and Tang, Y. (2011). Characteristics of uncurledand reversely curled chip during orthogonal cutting.International Journal of Machine Tools and Manufac-ture, 51(10-11):831–835.

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A Solution to Increase Natuna D Alpha’s Resource Utilization byCryogenic Distillation: Conceptual Design & Sensitivity Study

Wijoyo Niti Daton, Ezra Revolin, Siptian Nugrahawan, Prasandi Abdul Aziz, Tutuka Ariadji, StevenChandra and J. A. Nainggolan

Petroleum Engineering Program, Institut Teknologi Bandung, Jalan Ganesha No 10 Bandung, Indonesiawndaton, ezra, siptian, paa, ta, steven, [email protected]

Keywords: Cryogenic Distillation, CO2 Separation, CO2 Transportation.

Abstract: Natural gas extracted from its respective reservoir needs to be processed to meet the specifications of salesgas. CO2 is one of the components that needs to be separated from natural gas. The CO2 concentration ofnatural gas varies from a content of less than 20 mole % to more than 80 mole%. There is a problem whenthe content of CO2 is very high so it is necessary to modify the CO2 level reduction by modifying the equip-ment or changing the operating conditions to meet the desired CO2 purity. In this study, field conditions andcharacteristics reviewed is East Natuna Gas Field which has a gas composition of 71% CO2 and 29% methanewith modified pressure based on the capability and capacity of available equipment. From the conditions andcharacteristics of the field, the CO2 method of separation from natural gas using cryogenic distillation waschosen.This research presents analysis and sensitivity of technical parameters that influence the method ofCO2 separation from natural gas using cryogenic distillation. The sensitivity is done by changing parametersof pressure and very high feed gas flow rate into the column. In addition, the calculation of the diameter andheight of the distillation column using the calculation of the formula and the results of the simulation usingcommercial process flow software. This study applies a CO2 separation process with cryogenic distillationand the desired product specification of CH 4 is 99%. The design of the equipment was simulated using twodistillation columns with operating pressure at the first distillation column of 45 bar and the temperature of19.19 oF, and for the second distillation column the operating pressure was reduced to 35 bar. The results arefor the 8000 MMSCFD flow rate case obtained the first number of columns as many as 16 with the size of7.4 meters diameter and 17.66 meters high, while the number of second column of 4 with the size of 8 metersdiameter and 22.38 meters high. The results presented are still less suitable with the conditions in the EastNatuna Gas Field because offshore constrains so need to be studied further for design and other methods inapplication in the field.

1 INTRODUCTION

Natural gas is one of most the important energysources in the world. Today humans use natural gasto meet energy needs, where the use of gas is esti-mated to increase by 1.5% each year (IEA, 2017).Global gas demand for natural gas increased from3635 bcm in 2016 to more than 5300 bcm in 2040(IEA, 2017) Indonesia is one of the archipelagic coun-tries that has large gas reserves spread across sev-eral regions, one of which is the East Natuna Block.Natuna Timur block is one of the gas fields that has anabundant source of gas reserves, which makes Natunathe largest undeveloped gas reserve in Southeast Asia(Fenter et al., 1996). However, the abundant potentialof gas reserves also has a very high CO2 gas content

so that CO2 separation technology is needed so thatthe gas produced can be utilized properly. Impuri-ties such as CO2, H2S, and other acid gases need tobe removed from natural gas because in the presenceof water, this content can make pipes and other toolscorroded(Rufford et al., 2012).

At present, various methods of acquisition andtechnology have been implemented to increase nat-ural gas production. The existing technology is ad-justed to the field conditions and characteristics. Onechallenge that is often faced is the presence of acidgas contained in it. Sources of acid gas are naturalgas resources that contain most of CO2 and/ or H2S(Burgers et al., 2011). The separation process can bedesigned to overcome differences in molecular prop-erties or thermodynamic properties and the .

342Daton, W., Revolin, E., Nugrahawan, S., Aziz, P., Ariadji, T., Chandra, S. and Nainggolan, J.A Solution to Increase Natuna D Alpha’s Resource Utilization by Cryogenic Distillation: Conceptual Design & Sensitivity Study.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 342-348ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

displacement of components in the mixture (Ruf-ford et al., 2012). Therefore several methods of sepa-ration of acid gas have been developed, or commonlycalled sweetening gas processes for H2S separation,such as absorption, adsorption, membrane and cryo-genic methods, each of which is used for differentproperties and conditions of fluid and field. In thisstudy, the selection of CO2 separation method withreference characteristics from the East Natuna GasField was carried out and a process simulation wascarried out to obtain the results of the high CO2 con-tent separation by observing the effect of pressure andthe feed rate from CO2 gas was very high.

Natuna Gas Field is located in Indonesian watersprecisely in the Natuna Sea. This field is 140 milesnortheast of the Natuna Islands and 218 miles north-west of the island of Borneo. The water depth of thisfield is around 475 feet. The amount of gas volumein the reservoir is estimated at 222 TSCF with thecomposition of the gas contained among others 71%CO2, 28% methane and heavy diffraction hydrocar-bons, 0.5% H2S, and 0.5% N2 (Fenter et al., 1996).The Natuna Gas Location Map is shown in Figure 1.

Figure 1: Location of Natuna Field (Fenter et al, 1996).

Natuna gas reservoir is interpreted in the form ofcarbonate domes which are isolated and contained inthe Miocene Reef Formation (Fenter et al., 1996). Ifthe formation is a carbonate formation, calcite disso-lution will form CO2. The high CO2 content in theNatuna gas reservoir is estimated to be the result ofthe calcite dissolution process (Suarsana et al., 2010).This reservoir has a pressure of 5717 psig and a tem-perature of 340 F which is measured by measuringthe well at the central depth. The estimated gas yieldfrom this field is 75% with recoverable hydrocarbongas of 46 TSCF (Fenter et al., 1996).

Natuna Field Reservoir contains more CO2 thanhydrocarbons. CO2 dominates the aging of the reser-voir phase and controls the production method. Be-cause this reservoir fluid contains more hydrocar-bon components, this reservoir is considered a non-hydrocarbon reservoir (Suarsana et al., 2010).

2 OVERVIEW OF NATURALGAS-CO2 SEPARATIONPROCESS

During the requirement of separating CO2 from nat-ural gas, not all available methods can be applied inevery field. Considerations of methods available onseparating high levels of CO2 is important so that theselection of the right method will give good results.In addition, differences also depend on the thermody-namic and transport properties (interphase), in whichcase the properties considered include vapor pressure,boiling point, solubility, adsorption capacity, and dif-fusivity (Rufford et al., 2012). Based on the natureof the components to be separated, the main opera-tion in the gas separation and purification mechanismfollows the mechanism: (1) phase formation by heattransfer and / or shaft work into or from the mixture,(2) absorption on liquid sorbents or solids, (3) adsorp-tion on solids, (4) permeation through a membrane,and (5) changes in chemical compounds into othercompounds (Kohl and Nielsen, 1997)(Seader et al.,1998). The direct chemical change in CO2 which iscurrently under study is an example of dry reformingprocess, namely CO2 reacts with CH 4 to form syn-gas (mixture of H2 and CO2) which can later be usedto produce liquid fuel through a Fischer-Tropsch re-action (Rufford et al., 2012) Then the selection forselecting an acid gas treating process can be viewedfrom the gas partial pressure, based on referencesfrom Aden (Nexant, 2011) and shown in Figure 2.

Figure 2: CO2 Removal Chart Based on Partial Pressure(Aden, 2009).

Based on the results of Revolin’s (2016) research,the selection of the CO2 method can be done withthe help of the separation process selection diagramshown in Figure 10. In addition, in this thesis a selec-tion of CO2 separation methods was carried out withreferences from (Rufford et al., 2012) based on sev-

A Solution to Increase Natuna D Alpha’s Resource Utilization by Cryogenic Distillation: Conceptual Design & Sensitivity Study

343

eral influential parameters in Table 1. In this study, thefactors that were considered to be the most influentialin the process of selecting CO2 separation methodsfrom natural gas include:

• The presence or absence of H 2S gas content

• Concentration of feed gas CO2

• Feed gas flow rate

• The purity of CH4 and CO2 products

From the Natuna Field case, there are severalcharacteristics that are owned as consideration of thechoice of methods including:

• The H2S content is small

• The concentration of the gas content is 29%methane and 71% CO2

• Flow rate is very high (more than 1 BSCF, de-pending on the duration of the contract)

• The desired purity of the product is at least 95%methane, in this case it is targeted to be 99%.

From the parameters of CO2 inlet concentrationabove 50%, then based on a summary of the techno-logical characteristics in Table 1 that may be used aremembrane technology, absorption with amine, andcryogenic distillation. Then the selection process isalso carried out with the help of a selection diagramin Figure 3 with the results of technology suitable foruse, namely cryogenic absorption and distillation. Inthis study, membrane technology and absorption werenot chosen because there were several considerationsbased on (Rufford et al., 2012). Membrane technol-ogy requires pretreatment processes to remove heavyliquids or hydrocarbons because it can cause damageto membranes and blockages. Membrane quality de-pends on permeability and selectivity that cannot beobtained simultaneously. In addition, membranes aresensitive to feed conditions and hydrocarbon loss isalso higher than other technologies. In the absorptionmethod another unit is needed to regenerate solventsin the process of CO2 gas separation. In this methodit is also often formed loading, foaming, and channel-ing so that mass transfer is not good. Then, the ab-sorption method requires a large amount of solventsto separate the volume of high CO2 gas, which makesenergy consumption also higher especially for regen-erating solvents. Conformity between the character-istics of the cases and categories in this study resultedin the selection of cryogenic distillation.

In this study the simulation of CO2 separation us-ing the cryogenic distillation method was carried outusing the Aspen Hysys V10 software. Simulationof CO2 separation was carried out by applying refer-ence to the cryogenic distillation process by Pellegrini

Figure 3: CO2 Separation Guideline (Liu et al., 2015).

(Pellegrini et al., 2015) with simplification of one dis-tillation column and reference from Revolin (2016) asa simulation baseline with several assumptions usedin the process including simplified feed gas compo-nents in the form of binary mixture namely CO2 andmethane, and the vapor and liquid phases are consid-ered ideal. The scheme of the distillation process canbe seen in Figure 4.

Figure 4: Cryogenic CO2 Separation (Pellegrini et al.,2015).

In this CO2 separation simulation the most im-portant component observed is the distillation col-umn. The distillation design process consists of de-signing processes and mechanical design. Simulationwith shortcut distillation is used in the design pro-cess to find out the mass balance and the variablesneeded. Then, some parameters generated from thissimulation that are needed for mechanical design in-clude pressure and temperature on the top product (inthe condenser) and the bottom product (in reboiler)needed, the minimum and actual stage number, theposition of the feed gas stage, and reflux ratio early. Inthis stage data on composition, pressure, temperature,and feed gas flow rate are needed, as well as the speci-fications of the condenser output and reboiler needed.The feed gas flow rate obtained also makes the flowrate data for each component in the feed known.

In mechanical design, rigorous methods are used(with the distillation column) for more detailed anddetailed simulations to determine and determine theprofile of pressure and temperature in each stage, con-


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denser and reboiler condition profiles, and the com-position of CO2 and methane from separation. It isnecessary to know the variables needed in the distilla-tion column, including the composition and flow rateof the feed gas, the pressure and temperature of thefeed gas, the position of the feed gas stage, the num-ber of stages and the pressure profile, and the spec-ifications of the desired product or product. Someof the assumptions used in the distillation columninclude each plate in the column having an equilib-rium with constant pressure reduction with a rule ofthumb of 0.2 psi per plate. The pressure and tem-perature of the feed gas entering the distillation col-umn need to be adjusted to match the column op-erating conditions. The high CO2 content is cooledto a certain temperature and pressure on the distilla-tion column so that the CO2 concentration decreasesto the desired level, which increases the concentra-tion of methane. Pressure and temperature specifi-cations are important factors that influence gas sep-aration(Suarsana et al., 2010). The column operatingconditions are assumed to be in ideal conditions or inthe sense that the amount of feed gas to the distillationcolumn is equal to the number that exits the column.Then the separation simulation is carried out usingtwo stages of design with several sensitivity studiesthat refer to a predetermined base case condition.

From the base case that has been determined, pres-sure sensitivity and the rate of gas feed production arecarried out into the distillation column. After a simu-lation and sensitivity study, the reflux ratio results andthe number of stages needed to obtain the desired cri-teria for the methane and CO2 content are obtained.Variations in the condition of the feed gas are carriedout with the condition of the condenser and the re-boiler being fixed.

3 CASE STUDY

Before the sensitivity study, a base case was sim-ulated with a composition of 71% CO2 and 29% CH4, feed gas flow rate of 8 BSCFD, pressure of 652.7psia, and temperature of 19.19 oF (at the dew pointpoint) with the result specifications in the CH 4 con-denser with purity of≥ 95% and the result of reboilerCH 4 ≤ 0.001%. From the variable reference shortcutdistillation method obtained, the minimum number ofstages required is 9,643 with rounded up to 10 stages,the actual number of stages is 17, and the feed gasflow is optimal in the second stage. Then the resultsof the condenser namely CH 4 composition has a flowrate of 2,442 BSCFD and from the reboiler obtaineda flow rate of 5,558 BSCFD. The shortcut distillation

operation scheme in the base case can be seen in Fig-ure 5.

Figure 5: Cryogenic CO2 Separation (Pellegrini, 2014).

The results of the number of stages and reflux ra-tios obtained from the shortcut distillation simulationare entered into the distillation column for rigorousdistillation simulation and the results for this basecase condition are reflux ratios of 12.08. Comparisonof reflux ratio calculations with the shortcut distilla-tion method and rigorous distillation gives differentvalues. This is due to the rigorous distillation simula-tion, the calculation is done in more detail and detailthat considers many variables and results until the de-sign of column sizes. The results obtained are in theform of a static plant simulation and even dynamicif added to the addition of controls (Biyanto, 2007).While the distillation shortcut is still a rough calcula-tion or not done in detail. The CO2 separation schemeuses rigorous distillation in the base case distillationcolumn attached to Figure 6.

Figure 6: Cryogenic CO2 Separation (Pellegrini, 2014).


345

Then a sensitivity study is carried out by review-ing the variable pressure and feed gas flow rate. Thetemperature conditions of the feed gas, gas specifica-tions produced, and variations in flow rates are madethe same in each case. The feed gas flow rate andthe flow rate of the separation results for each rate areshown in Table 1.

Table 1: Gas Flow Rate on Distillation Column.

Flow Rate (MMSCFD)

Feed Gas Condenser (Top) Reboiler (Bottom)

8000 2442 55581000 305.2 694.82000 610.4 1389.63000 915.6 2084.44000 1221 27795000 1526 34746000 1831 41697000 2136 4864

From Table 2, the flow rate of CH 4 generatedfrom the condenser is smaller than the flow rate ofCO2 generated from the reboiler because the fractionof the CO2 component in the feed gas is greater thanCH 4. And also in this study, the calculation in thesimulation uses the assumption of a 100% efficiencylevel in the separation process so that the total flow ofthe feed gas entering is equal to the amount that comesout. The following are the operating conditions of thedistillation tower for each case shown in Table 2.

Table 2: Gas Condition in Distillation Column.

Case Operating ConditionFeed Gas Condenser Reboiler

Base P = 652.7 psiT =19.19 F

Pcond = 652.3 psiTcond = -109.5 F

Preb = 656.1 psiTreb = 50.67 F

Case 1 P = 507.6 psiT =19.19 F

Pcond = 507.2 psiTcond =-120.9 F


Case 2 P = 362.6 psiT =19.19 F



Case 3 P = 217.6 psiT =19.19 F

Pcond = 217.4 psiTcond =-140 F

Preb = 219.4 psiTreb = -17.5 F

Case 4 P = 72.52 psiT =19.19 F


Preb = 73.92 psiTreb = -69.13 psi

In terms of operating conditions, the pressure onthe condenser needs to be made smaller than the re-boiler pressure. This is so that the steam formed canrise to the top of the column, according to the prin-ciple of fluid flow that the gas will flow from highpressure to low pressure.

From the sensitivity results obtained that thegreater the pressure of the feed gas into the distilla-tion column, with the same flow rate and tempera-ture of the feed gas, the more reflux ratio is needed.This is because with high pressure the more steam

formed. Even though the reflux system is condens-ing steam, so if the steam is high then the reflux ra-tio is also high. This applies also with the increasingpressure of the feed gas, the greater the number ofstages needed. The principle of the stage is to sep-arate the components in the gas feed, if the pressureis high then the interaction of the gas component isalso higher, then more stages will be needed for theseparation process. In this study the magnitude of thefeed gas flow rate does not directly affect the magni-tude of the relux ratio and the number of stages. Foreach case carried out, the value of reflux ratio and thenumber of stages are the same, but the magnitude ofthe feed gas flow rate affects the diameter of the dis-tillation column more and the energy needed, in thiscase the condenser duty and reboiler duty. The greaterthe feed gas flow rate, the greater the dimension (di-ameter and height) of the distillation column and theenergy needed. This is because a large flow rate re-quires a large capacity.

After the sensitivity to the influential parametersit was found that in distillation using distillation isstrongly influenced by pressure and rate feed gas flow.The smaller the condenser duty feed gas pressure andthe reboiler duty is also greater, but it needs to be ad-justed again with the existing capacity. In the lowtemperature process carried out on the separation ofthe natural gas flow with high CO2 concentration thecooling cycle is required in the process. In this condi-tion, electrical energy needs are one of the importantfactors because they are needed in the cooling cycle.Therefore it would be better to choose the lowest pres-sure energy conditions, especially in this study thecondenser and reboiler. From the results of the sensi-tivity obtained the selection of pressure is taken at thegreatest value. In this study the pressure was in therange of 5-45 bars. In this study cryogenic distillationwas not carried out by a higher pressure review be-cause of the limitation of temperature determinationof 19.20 F and the feed gas vapor fraction 1 whichcould be achieved with higher pressure when the tem-perature was also raised. Therefore it was chosen, thefeed gas pressure was 45 bar in this study.

The design of the CO2 separation process in thisstudy used the method in the Pellegrini (Pellegriniet al., 2015) patent with separation using two distil-lation columns. The feed gas pressure entering in thefirst column is 45 bar and in the second column 35bar. The purity results obtained in this study were99% CH 4 at the end of the second column. From thefirst column to the second column a heater and valveare given to reduce pressure. Then the output of CO2in the second column is pumped back to the first col-umn for re-separation. The design of this process can


346

be seen in Figure 7.

Figure 7: Overall Design of Cryogenic Process.

To validate the results of the calculation of the dis-tillation column, a reference is needed for compari-son. In this study a reference to the size of the dis-tillation column from the RCC Regenerator Columnwas used, Balongan refinery with a diameter of about9 meters and a height of more than 20 meters. Thenthe feed gas rate is determined by the length of theagreed contract. In this study the reference of feedgas flow rate uses a reference from Nainggolan (2016)with a flow rate of 8 BSCFD. From these references,determining the size of the distillation column can bedone.

The variation in flow rate from 1-8 BSCFD pro-duces a diameter of more than 11 meters. Whereasthe flow rate of 100-800 MMSCFD has the largest di-ameter at the rate of 800 MMSCFD with a value of10 meters. For the rate of 8 BSCFD, a diameter of52.5 meters is produced, in the field this condition isnot possible so there is a need for a scenario to di-vide the flow rate in the column in parallel, more thanone in each column. In the first column the maximumrate that can be accommodated is 500 MMSCFD witha diameter of 7.4 meters, while for the second col-umn the maximum rate that can be accommodated is610.4 MMSCFD from the results of the first columnwith a diameter of 8 meters. The scenario is basedon the smallest condenser duty and reboiler duty to-tal requirements is selected so that the first scenariowith column 1 (7.4 meters in diameter and 17.66 me-ters in height) is obtained and 16 pieces are neededcolumn 2 (with a diameter of 8 meters and a heightof 22.38 meters) requires 4 pieces. From these resultsfor the next process, it is necessary to consider the ap-plication of the distillation column in the field, withthe limitation of the location of the Natuna Gas Fieldwhich is offshore resulting in the availability of landand installation of the distillation column equipmentthat needs to be reviewed.

Based on the designs presented above, it can be

proposed to be two main distribution/processing hub,namely the platform based unit processing and on-shore facility, connected with underwater pipeline. Itis worth noting that applying platform based process-ing facility requires massive capital due to the sizeof the processing facility, while using onshore facil-ity would require very large pipe with high corrosionpotential. Further study should be done to assess theeconomic and technical feasibility of these projects.

4 CONCLUSIONS

The choice of CO2 separation technology from natu-ral gas is based on several factors that are highly de-pendent on the conditions and characteristics of thegas field being reviewed.

Under pressure and gas flow rates based on thecase of the Natuna Gas Field, the cryogenic distilla-tion process is chosen in the separation of CO2 con-tent at high flow rates, and is considered capable ofobtaining specifications of CO2 content of less thanor equal to 1%.

In designing CO2 separation using cryogenic dis-tillation at a very high flow rate, a flow rate distri-bution scenario in parallel with different columns isneeded to meet these needs due to limited locationavailability.

With the content of 71% CO2 and 29% methane,the results of separation using two-column cryogenicdistillation obtained by the case of 8000 MMSCFDflow rate obtained the number of the first column asmuch as 16 with a diameter of 7.4 meters and heightof 17.66 meters, while the number of second columnswas 4 in diameter 8 meters high and 22.38 meters.

REFERENCES

Biyanto, T. R. (2007). Cascade control using soft sensor foraldehide column energy saving. IPTEK The Journalfor Technology and Science, 18(4).

Burgers, W., Northrop, P., Kheshgi, H., and Valencia, J.(2011). Worldwide development potential for sourgas. Energy Procedia, 4:2178–2184.

Fenter, D., Hadiatno, D., et al. (1996). Reservoir simulationmodeling of natuna gas field for reservoir evaluationand development planning. In SPE Asia Pacific Oiland Gas Conference. Society of Petroleum Engineers.

IEA (2017). WEO 2017.Kohl, A. L. and Nielsen, R. (1997). Gas purification. Else-

vier.Liu, X., Jin, D., Wei, S., Wang, Z., An, C. G., and W.

(2015). Strategies to enhance CO2 capture and sepa-


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ration based on engineering absorbent materials. Jour-nal of Materials Chemistry A. 3, 3.:12118–12132.

Nexant, Inc., S. F. C. (2011). Survey and Down-Selectionof Acid Gas Removal Systems for the Thermo-chemical Conversion of Biomass to Ethanol with aDetailed Analysis of an MDEA System. Techni-cal report, National Renewable Energy Laboratory(NREL), Golden, CO (United States).

Pellegrini, L. A., Oldrich, M., Lange, S., and Picutti, B.(2015). A New Cryogenic Technology for Natural GasSweetening. Presented at SOGAT 2015, Abu Dhabi.

Rufford, T. E., Smart, S., Watson, G. C., Graham, B.,Boxall, J., Da Costa, J. D., and May, E. (2012).The removal of co2 and n2 from natural gas: A re-view of conventional and emerging process technolo-gies. Journal of Petroleum Science and Engineering,94:123–154.

Seader, J. D., Henley, E. J., and Roper, D. K. (1998). Sepa-ration process principles.

Suarsana, I. P. et al. (2010). Producing high co2 gas contentreservoirs in pertamina indonesia using multi stagecryogenic process. In SPE Asia Pacific Oil and GasConference and Exhibition. Society of Petroleum En-gineers.


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Design of Volcanic Educational-based Natural Tourism at Giriloyo,Wukirsari Village, Imogiri District, Bantul Regency,

Yogyakarta-Indonesia

Sri Mulyaningsih1, Nur Widi Astanto Agus Tri Heriyadi2, Desi Kiswiranti3 dan Muchlis4 .1,2,3Geological Engineering of FTM-IST AKPRIND Yogyakarta,Jl. Kalisahak No. 28 Yogyakarta

Corespondence: 082136293027, [email protected]

Keywords: design, nature, tourism, ancient, and volcano

Abstract: Previous study determined Giriloyo was Tertiary ancient volcano. Dyke, lava, and andesitic breccia which comprise this region strongly support the geological conditions, but the central facies of the ancient volcano had already associated with so many cracks, so that need further geotecnical handlings. Design technic for the geotecnical engineering is required to support it. This study aims to develop a geotechnical planning design in the context of a potential landslide management. On the other hand, Giriloyo has a potential volcanic educational-based tourism, supported with beautiful landscapes. The geotechnical planning design was packaged in the form of educational-based natural tourism development. Research related to the purpose has been carried out supported with geotechnical mapping to describe the carrying capacity. The results found southwest-northeast normal faults (N290-320oE), north-south shear faults (0-15oE), and oblique normal faults (northwest-southeast). All of them have potentially move to generate landslides. In anticipate the active rock movements, sloping terraces into 25-30o to obtain safety factors of at least 1.5-1.8 have been designed. Thus, the technical design to reduce the potential mass movements is addressed to obtain the natural cruising tourism. The terraces are designed to expose 5 ancient volcanic stratums, i e. Central Facies Stratum, Dyke Stratum, Lava with Hydrovolcanic Stratum, Lava with Collumnar Joints Stratum, and Agglomerates with Autoclastic Breccia Stratum. Each of these stratums is connected with a multilevel educational pathway to reduce burden on the land.

1 INTRODUCTION

An ancient volcano was identified at Giriloyo, Wukirsari Village, Imogiri District, Bantul Regency, Yogyakarta Special Region (Figure 1). There was a long periode of superimposed volcanism, building Kebo-Butak Formation and Nglanggeran Formation, during Early to late Middle Miocene (Mulyaningsih et al., 2019). The exposed volcanic rocks were deformed generating active cracks that potentially to move. A big landslide was noted in 17 March 2019, remaining very wide sloping plane of 47o (Figure 2). The slope was progressing to erode time by time, not only by running water but also by the active fault.

Figure 1: Situation map of study area.

Mulyaningsih, S.Design of Volcanic Educational-based Natural Tourism at Giriloyo, Wukirsari Village, Imogiri District, Bantul Regency, Yogyakarta-Indonesia.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 349-356ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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Dykes, lava, tuff, and andesitic breccia compose Nglanggeran Formation, that covering older volcanic rocks of Kebo-Butak Formation, exposed at Watulumbung, near the landslide. While Kebo-Butak Formation consists of black color of layered tuff, palagonite tuff and lapillistone. About 40-60cm of calcareous sedimentarry rocks of claystone and sandstone intersected the Kebo-Butak Formation and the Nglanggeran Formation, having ages of N5-6 (Early Miocene). So that the Kebo-Butak Formation must be older than Early Miocene.

Actually, those volcanic rocks should strongly support the geological conditions, but a high density

of deformations and weathering, so it become fragile. It needs further geotechnical treatments. Design technic after the geotechnical study in early step is necesarry to assist the geotechnical engineering.

This study aimed to design the geotecnical engineering, related to the mass movements management. By the presence of the interesting volcanic rocks of the central facies ancient volcano, design of the geotechnical engineering should be composed curously and arty. Those purpose to obtain Giriloyo ancient volcano to be community-based geotourism.

Figure 2: Landslaide happened on 17 March 2019 at the meter of 720th (a) and the potential landslides along the track of Giriloyo (b,c).

2 METHOD

The study was started by geotechnical mapping with surface and subsurface investigation. Those mapping described lithology distributions, faults (deformation)

and the potential creeps, slumps and falls. Surface mapping carried out by tracking, measuring and compiling the geological data. Subsurface mapping used microseismic soundings. This research used H/V method, also called Nakamura technique. The device was seismometer Lennartz Electronic with brand LE-


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3Dlite, to describe the HVSR spectrum ratio (~microzonation), following the formula is:

Site response analysis is important in seismic hazard assessment such in earthquake prone zones (Bray and Rodriguez-Marek, 2004) and mass movements. Tohwata (2008) argued that microzonation can predict the response and behaviour of soil and rocks by the external energy around the soils/rocks.

Fifteen spots have sounded using H/V method. The microseismic device identifed vibration decays along the identified surface fault planes. This method was intended to identify the distribution of the faults below the surface. Along with the broadband seismometer measuring in the real time, the vibration were recorded using the main sources of hits sounding into the medium. The ground movements were verified as a function of time in local site.

Analysis and synthesis of research data is based on all data that is compiled using the library data collection system, then synthesized using overlie system. Calculation and simulation of slopes is carried out manually and computed using ESRI and / MapInfo Arc-GIS software.

3 RESULTS

3.1 Secondary Data

Secondarry study found stratigraphy of study area from the bottom to the top were Kebo-Butak, Semilir, Nglanggeran, Sambipitu, Oyo and Wonosari Formations (Elliezer et al., 2019; Rahardjo et al., 1995; and Surono et al., 1992). The third earlier mention were volcanic constituents. Kebo-Butak Formation and Nglanggeran Formation were exposed at study area (Mulyaningsih et al., 2019).

3.2 Field Data Record

Surface field mapping described Kebo-Butak Formation consists of black tuff intersects with brecciated and compacted basalt lava in about 60m thickness. Above them are less calcareous sedimen-tarry rocks consist of laminated tuffaceous claystone and sandstone in about 60cm. Creammy color of coarse tuff and lapillistone lie on the sedimentarry rocks. That volcanic rocks are coarsening upward and

replaced with intersectings of thick layers of breccia, lava and lapillistone in pyroxene-rich basalt composition. The thickness of the volcanic sequence is ~200m. Above them are agglomerate, andesitic lava and dike (Figure 3), which is interpreted as Nglanggeran Formation, as a product of constructive phase volcanism occured within central facies. The last volcanic rocks are exposed in the top of the track, i.e. in the meter of 1000th at Watulumbung (1927th).

These volcanic rocks strongly supported the geological conditions, but the inflation and deflation during the volcanism located at the central facies had already associated with the deformations. Mapping recognized geological structures, consist right normal slip faults. There are south-west-northeast normal faults (N290-320oE), north-south shear faults (0-15oE), and oblique normal faults (northwest-southeast) (Figure 4a-b). All of them have potentially move to generate landslides.

3.3 Subsurface Mapping

The soil vulnerability index (Table 1, Figure 5) displays soil and rocks stability; the greater the vulnerability value the smaller the soil/rocks structure. The high vibration decays of the lections of micrometer are found at S04-S07 with 33.2-45.55kgs in the elevation of 134-186m asl (Table 1, Figure 5). Those corners are described having small values of the soil vulnerability index, so that interpreted as unstable conditions (movable). Low vibration decays are found at S012-S015; that zone are interpreted having higher vulnerability index, so that calculated as more stable blocks.

Table 1: The mass vulnerability index recorded during microseismic measurements.

Sta-tion

Coordinate (m) Eleva-tion (m)

Vulnerability Index (kgs) South East

S01. 434823 9124498 50 32.45 S02. 434778 9124451 104 23.68 S03. 434783 9124362 146 18.42 S04. 434786 9124312 145 45.55 S05. 435126 9124308 186 38.75 S06. 435044 9124366 137 37.56 S07. 434995 9124430 134 33.12 S08. 434922 9124450 115 27.49 S09. 434845 9124597 105 16.54 S010. 434881 9124518 94 17.77 S011. 434759 9124693 103 21.45 S012. 434920 9124600 157 19.87 S013. 435055 9124516 211 17.55 S014. 435238 9124359 244 15.45 S015. 435255 9124336 262 12.73

Design of Volcanic Educational-based Natural Tourism at Giriloyo, Wukirsari Village, Imogiri District, Bantul Regency,Yogyakarta-Indonesia

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Figure 3: The volcanic rocks exposed at study area; a. Agglomerate; b. Dike; c. Altered rocks with sulphid minerals, d. Volcanic neck; and e. Lava with collumnar joints. Those are used to deposited very close to the crater or within the crater.


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Figure 4a: The geological structure measured and computed at study area; the right normal slip faults.

Figure 4b: The distrubuted normal and right slip faults interpreted based on surface mapping and subsurface mapping using dipole-dipole resistivity method and microseismic method.


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Figure 5. Map of vulnerability index at study area interpreted from microseismic soundings.

3.4 Geomorphological Analyses

Geomorphology of study area are characterized by gently to undulating topography sloping to 5-10o (at Giriloyo), undulating to steeply at Cengkehan to Nogosari (sloping between 10-30o), roughy elevated hills near upper Nogosari, Watulumbung and Grenjeng (~30-60o) and very steeply scarpments with ~60-70o on upper cliffes (Figure 6). The scarpments are impending to fall (Figure 2). Creeps are recognized along Grenjeng and lower Bukit Makbul (Figure 2).

Figure 6: Digital Elevation Model (DEM) at study area.

4 DISCUSSION

Both surface and subsurface mappings recorded active faults that potential moving at study area. According to the data, whenever and at any time, such in water saturated condition (in rainny sesion), it will

immediately collapse. Sloping will reduce the rate of mass movement. Design for the hazard mitigation is necesarry following the potential landslide/ rock falls. It’s following the internal shear angle (ɸ), the density of soil/rocks (γ), cohesion (c) and water contents (ω). Terraces will be also able to minimize the impact caused by the mass movements. Technically, designing terrace are following Figure 7.

The problems are how to manage the slope stability, at once the kinds of strategic management in protecting the geoheritage related to the Giriloyo-Cengkehan’s ancient volcano phenomenon. Safe storage with good aesthetics can be done through the terracing. Making artistic terraces will not only reduce the rate of mass movements but also add to the aesthetics of the study area. Slope management can be improved through risk analysis and systematic assessment of slope stability.

Terrace morphometry has been analyzed based on size, width (horizontal/horizontal interval (HI)) and distance of each edges (vertical distance/vertical interval (VI)). The terrace interval (HI) was assumed according to the ease of anthropogen activities. The size of terrace (VI) was calculated using the equation of FAO (1986, in Blanco, 2008) as follows.

∗

∗= where as VI = vertical distance (m), Wb =

terrace width (m), hereinafter referred to as HI (m); S = slope (%) and U = HI and VI ratio (using 0.75 for manually built terraces (Blanco, 2008). So that it was calculated that slopes of ≤20o is advisable a distance to be 15m; while slopes of ~30o should be more than 10m distance. Bennett's criteria to calculate distances between terraces are the more advisable being closely related with experimental results in the area. Each terrace consists of 5m for landfill, 5m bamboo parks with landfilling to the top, the last 5m is keep to be the original slopes. The overall slope has changed to ~20o in the teak garden, and ~35o around the 1.5-5m and obtain safety factor of 1.5-1.8 for the sloping terraces.

Bamboo park is chosen to be an effective soil conservation at study area. Bamboo groves can maintain land and groundwater stability. The dense bamboo root system, which spreads in all directions, is able to strengthen the stability of the land, and rain water is easier to infiltrate into bamboo-covered soil. Bamboo stems have advanced natural capillary, which absorbs and stores water. Bamboo is able to release 35% oxygen and is a very useful plant in terms of reforestation of unproductive or degraded land. Planting bamboo at study area as land conservation is designed take place in the tarrace planes (Figure 7.a), while the hillslopes are designed as a retaining walls (Figure 7.b).


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Figure 7: Design for the terracing (grounding) the slopes in reducing mass movements

Figure 8: Design of the volcanic educational-based tourism at study area; as a conservation plan to manage landslide and other potential mass-movements.


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5 CONCLUSIONS

Study area has potential mass-movements, such as landslides. It threats to the civilization below the slopes. But study area also potential with special interest of ancient volcanological tourism. Land conservaton and developing heritages (land, culture and geology) is designed following the natural resources and their potential movements. Terracings are chosen to be developed at study area. Those are designed by sloping landscape into 20-35o, to obtain slope stability under safety factor of 1.5-1.8.

ACKNOWLEDGEMENTS

Our greetings attend to the Ministry of Research and High Education (RISTEKDIKTI) which was funding the research by the first and second years of Penelitian Terapan Unggulan Perguruan Tinggi (PTUPT Scema) on 2018-2019. Special gratitudes tend to the goverment of Bantul Regency, the head and staff of Wukirsari, the Giriloyo and Cengkehan communities, POKDARWIS, as well as FORCIB ARYABHATA, who have provided the research facilities, accompanied the research and gave a variety of very warm supports. A big appreciation is supervised to LPPM IST AKPRIND Yogyakarta for the opportunities to reach the PTUPT grant.

REFERENCES

Arce, J.L., Walker, J. and Keppie, J.D., (2014). Petrology of two contrasting Mexican volcanoes, the Chiapanecan (El Chichón) and Central American (Tacaná) volcanic belts: the result of rift-versus subduction-related volcanism. International Geology Review, 56(4), pp.501-524.

Bray, J.D. and Rodriguez-Marek, A., 2004. Characterization of forward-directivity ground motions in the near-fault region. Soil dynamics and earthquake engineering, 24(11), pp.815-828.

Budayana, I.G.N.M, (2017). Geologi dan Identifikasi Fasies Gunung Api Berdasarkan Stratigrafi Batuan di Daerah Mangunan dan Sekitarnya, Kecamatan Dlingo, Kabupaten Bantul Daerah Istimewa Yogyakarta, Laporan Sripsi Tipe-1, 2017; tidak dipublikasikan.

Edwards, R.N., 1997. On the resource evaluation of marine gas hydrate deposits using sea-floor transient electric dipole-dipole methods. Geophysics, 62(1), pp.63-74.

Eliezer, I., Winarno, T. and Ali, R.K., 2019. Petrogenesis Lava Bantal Nampurejo di Dusun Kalinampu Dan Sekitarnya, Desa Jarum, Kecamatan Bayat, Kabupaten

Klaten, Provinsi Jawa Tengah. Jurnal Geosains dan Teknologi, 2(1), pp.33-41.

Hadian, M.S.D., Yuliwati, A.K. and Pribadi, K.N., (2016). Increasing community environmental awareness through geodiversity conservation activities at Ciletuh, Sukabumi, West Java. Journal of Environmental Management & Tourism, 7(2), p.14.

Hermawan, H. and Brahmanto, E., (2017). Geowisata: Perencanaan Pariwisata Berbasis Konservasi.

Hermawan, H., (2018). Geowisata Sebagai Model Pemanfaatan Kekayaan Geologi Yang Berwawasan Lingkungan. Jurnal online (STP AMPTA Yogyakarta, diakses tanggal 23 April 2018).

Hermawan, H. and Ghani, Y.A., (2018). Geowisata: Solusi Pemanfaatan Kekayaan Geologi Yang Berwawasan Lingkungan. Jurnal Sains Terapan Pariwisata, 3(3), pp.391-408.Mulyaningsih, S., Blessia, S., Tania, D. and Heriyadi, N.W.A.A.T., 2019. Studi Fasies Gunung Api Purba Gunung Ireng, Desa Pengkok, Kecamatan Patuk, Kabupaten Gunungkidul-DIY. Jurnal Teknomineral, 1(1), pp.15-23.

Mulyaningsih, S., Suhartono, dan Mindayani, E., (2019b). Kajian Potensi Pengembangan Jalur Jelajah Alam Geologi gunung Api Purba Giriloyo-Imogiri, Jurnal Riset Daerah, in press.

Pamuk, E., Özdağ, Ö.C., Özyalın, Ş. and Akgün, M., 2017. Soil characterization of Tınaztepe region (İzmir/Turkey) using surface wave methods and Nakamura (HVSR) technique. Earthquake Engineering and Engineering Vibration, 16(2), pp.447-458.

Permadi, R., Rachwibowo, P. and Hidajat, W.K., (2014). Potensi Situs-Situs Warisan Geologi di Area Kars Gunung Sewu sebagai Pendukung dan Peluang Pengembangan Geopark di Indonesia untuk Aset Geowisata Kreatif. Geological Engineering E-Journal, 6(2), pp.586-601.

Picozzi, M., Parolai, S. and Albarello, D., 2005. Statistical analysis of noise horizontal-to-vertical spectral ratios (HVSR). Bulletin of the Seismological Society of America, 95(5), pp.1779-1786.

Shapiro, N.M., Campillo, M., Stehly, L. and Ritzwoller, M.H., 2005. High-resolution surface-wave tomography from ambient seismic noise. Science, 307(5715), pp.1615-1618.

Sheng, D., Fredlund, D.G. and Gens, A., 2008. A new modelling approach for unsaturated soils using independent stress variables. Canadian Geotechnical Journal, 45(4), pp.511-534.

Smyth, H.R., Hall, R. and Nichols, G.J., (2008). Cenozoic volcanic arc history of East Java, Indonesia: the stratigraphic record of eruptions on an active continental margin. Special Papers-Geological Society of America, 436, p.199.

Surono, B.T. and Sudirno, I., (1992). Peta Geologi Lembar Surakarta-Giritontro. Jawa.(1408-3), Skala 1: 100000

Towhata, I., 2008. Geotechnical earthquake engineering. Springer Science & Business Media.


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Four Types of Moral Holistic Values for Revolutionizing the Big DataAnalytics in IoT-based Applications

Norma AliasDepartment of Mathematical Science, Universiti Teknologi Malaysia, Malaysia

Center for Sustainable Nanomaterial, Ibnu Sina Institute, Universiti Teknologi Malaysia, [email protected]

Keywords: IoT, Applications, Data Analytics.

Abstract: The high data speed generated by sensor devices has led to an awareness of the potential impact of big dataanalytics (BDA) and the Internet of Things (IoT). This paper highlights 4 types of moral holistic values forBDA analyzer, system developer, data provider and user in integrating the BDA and IoT applications. Beingethical is about confronting ethical issues. Wisdom, glory morality, courage, and justice are important holisticvalues for handling data sharing, data collaboration and data analytics. Four moral holistic values will reducethe gap between IoT, human and practice to improve the performance and revolutionize the performance ofBDA and IoT-based applications.

1 INTRODUCTION

The potential impact of BDA and the challenges of theIoT-based has been explored by the high speed datagenerated based on sensor devices. Huge memory al-location, high-speed processor and network commu-nication has led to the challenges presented by bigdata size, such as gigabytes, terabytes, and petabytes,that are generated by IoT-based device. The analysisof the IoT data set is basically obtained from the inte-grated technologies. For example, the combined IoT-based system for smart city development and urbanplanning using big data analytics has been suggestedby Rathore et al. (Rathore et al., 2016) Hence, themoral holistic values approach is needed for investi-gating various performances and analysis indicatorsthat are associated with prediction, visualization anddecision making.

M. Ge et al. (Ge et al., 2018) stated that the con-cern of big data collection, data processing, data an-alytics, data security, and the holistic value for thedata provider or data analyzer have become impor-tant. This is because the management of big data re-quires a continuously expanding network. The func-tion of the data provider and data analysis can beclassified according to their focus on the develop-ment of a complete IoT system consisting of var-ious types of sensor deployment, smart home sen-sors, vehicular networking, weather and water sen-sors, smart parking sensors, and surveillance objects

(Rathore et al., 2016). The tasks of data providers in-clude customizing IoT hardware and software, com-bining multiple processing tasks, handling data man-agement, conducting data analysis, managing projectsand data collections, transforming database structuresand maintaining cloud-HPC Platform (Lanza et al.,2016). These functions must be conducted in sucha way as to lead to integrity, trustworthiness, justice,courage, and excellence. Based on the requirementof human-to-human or human-to-computer interac-tion, this paper highlights four types of moral holis-tic values for BDA analyzer, system developer, dataprovider and user in integrating the BDA and IoT ap-plications, (Al-Turjman and Alturjman, 2018). Wis-dom, glory morality, courage, and justice are impor-tant holistic values for handling data sharing, data col-laboration and data analytics.

2 MORAL HOLISTIC VALUES

Quran describes that it is within the nature of thesoul to commit crime (Saged et al., 2018). Accord-ing to the Lord as Musa A. S stories, which have beenpassed down by Allah S.W.T in the Quran, fear re-sides within the soul. In addition, the soul is hometo animate the defiant feeling to face malicious acts(Dawud, 2002; Miskawayh, 1977; Bakar, 2010) con-cluded, based on the agreement of scholars, that the

Alias, N.Four Types of Moral Holistic Values for Revolutionizing the Big Data Analytics in IoT-based Applications.In Proceedings of the Second International Conference on Science, Engineering and Technology (ICoSET 2019), pages 357-362ISBN: 978-989-758-463-3Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

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cardinal virtues existing in humans can be dividedinto four categories. If a man contributes his excel-lence, glory, courage, and justice to others and peoplecan benefit from it, then he will be recognized andpraised as as wise, noble, courageous and fair (Misk-awayh, 1977). Being ethical is about confronting ethi-cal issues based on the holistic value of wisdom, glorymorality, courage, and justice. The first moral holisticvalue of this paper is wisdom.

2.1 Wisdom (al-hikmah)

Revolutionizing the big data analytics in the aspectof Islamic civilization involves the process of purifi-cation of the soul. This process is determined bythe rational sense of mind. Furthermore, to disci-pline emotional strength and rational sense of mindforces the emotions to behave and push it towardgoodness. Meanwhile, the power of lust can be disci-plined by the power of emotion. This process involvesthe change of the rational sense of mind (Miskawayh,1977). If the process of soul purification is successful,then the rational sense of mind will enhance the wis-dom (al-hikmah). The emotional strength will trig-ger courage (shaja cat) and the power of lust will re-veal the glory of morality (ciffat). Ultimately, justice( cadl) can be achieved when the three holistic valuesforce the form of the cooperation privilege (fadhilat)(Miskawayh, 1977). Thus, these four cardinal virtueswill drive the revolution of big data analytics.

According to (Miskawayh, 1977), there are sixtypes of wisdom that can be identified in individu-als; wisdom, retention, rationality, clarity of mind,quickness, soundness of understanding and capacityfor learning easily. The society that emphasizes theimportance of education and knowledge will be ableto produce a better human civilization. Intellect is avery useful gift for humans in the quest for scienceand wisdom. The expression of ideas will encouragethe production of a new creation. The reality is thatthe evolution of these creations occurs beyond the ju-risdiction and control of humans. On the contrary,it is an inspiration that is the gift of Allah the MostKnowledgeable (al-’Alim). Although it seems to benaturally born, in fact it is the result of God’s gift, fol-lowing the correct and valid rules of thought (Yang,2012).

Abu Bakar al-Razi (1987; 73) argues that humanshave never been created for physical pleasure, but arecreated to seek knowledge and to practice justice. Fora prosperous life, (Dawud, 2002) emphasized that ev-ery individual must familiarize himself with good-ness, obedience to the practices of religion and dis-tance themselves from evil and sin. People who live

in suffering are those who gird themselves with eviland immorality and are separated from kindness andobedience to God. Ibn Hazm (Dawud, 2002) men-tions that if knowledge is spread among people whodo not deserve it, it will ruin them. He mentions theparable of prescribing perfume to the person who hasa headache, as it will cause the person to get evensicker. Miskawayh (Miskawayh, 1977) divides wis-dom into two groups, wisdom from a theoretical andwisdom from a practical point of view. Wisdom froma theoretical point means the ability to deliver theright thought, while in the practical point, wisdom isthe sense of ability to produce a good situation thatpromotes the right action. Individuals with discretionwill ensure that each activity or product is produced inaccordance with the measuring stick and symbolizesthe wisdom of the mind. Besides intelligence, Misk-awayh also included some other elements includingretention, rational, clear mind, speed and firmness ofunderstanding, and ability to learn easily.

Data policy of the fourth industrial revolution(4iR) is highlighting the relationship between risk andbenefit. Islam encourages risk-sharing in our dailylife, be it in the transaction or not. When a risk isshared among two or more parties involved in dailyactivities, the burden of the risk faced by each party isreduced. The intelligent policymaker recognizes theimpact of culture, morals, and socialization of the 4iRpractitioners to reduce the risk globally. Accordingto Chen. J. (Liu et al., 2015), the intelligent systemdeveloper provides a proper infrastructure for usersto gather and to share data wisely. The success ofbig data-driven and updating data bank property willbe appreciated by the researchers. Intelligent algo-rithm and data training for machine, deep and extremelearning are the artificial infrastructures to stimulatedata-driven. The wisdom for data processing, iden-tifying, classifying and categorizing the huge datasetcan be performed by behaving and pushing it towardgoodness. Hence, the emotion to act has to be therational sense of mind force.

For example, using the big data for predicting,measuring the performance indicator for disseminat-ing analysis, enhancing intelligent data training forlarge-scale data analysis, and establishing the excel-lence library for data bank development. Therefore,to enhance the discovery of knowledge, wisdom is animportant factor in assisting human intellectual abil-ity, handling the artificial intelligence process (Aliaset al., 2018) and analyzing the performance of BDAand IoT.


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2.2 Glory Morality (al- ciffah)

Humans become ’human’ because of the advantagesof his existing rational soul (al-nafs al-natiqah). Theglory morality has a strong rational soul (Miskawayh,1977). The existence of glory morality distinguisheshumans from animals and angels. If the movementof the pious soul (al-nafs al-bahimiyyah) is normalbehavior, then he is responsible for the rational soulwithout rejecting what is given to him and he is notimmersed in lust. Furthermore, the moral holisticvalue of glory morality (fadilat al- ciffah) will be fol-lowed by the privilege value of benefactors (fadilatal-sakha’), (Miskawayh, 1977). Miskawayh dividesglory into twelve types namely; modesty, sedateness,self control, liberality, integrity, sobriety, benignity,self-discipline, good disposition, mildness, staidnessand piety. In the formation of spiritual values andpower within an educator, mujahadah is the most im-portant jihad.

Big data morality refers to the glory behavior toimprove society, to understand the problem and tosolve with a true interpretation. The examples ofimmoral behavior are accessing personal data or us-ing public data without permission. Lack of glorymorality can be seen in the process of analysing dataand producing enabled data source. For example, theparochially altruistic acts determining ethical pathsthrough a datafying world and understanding factualvia a trusted data base. Referring to big data ana-lytics process, we can understand the effects of de-cisions morally. We can determine the right outcome.If the outcomes are good, then the actions, intentionsand moral decisions will be right. If the outcome ispoor, then the actions, intentions, and decisions willbe wrong. Thus, the invention of network commu-nication of IoT device should have a glory morality,integrity, privacy, and autonomy.

2.3 Courage (al-shajacah)

The power of anger comes from jealousy and envy(quwwah ghadabiyyah). If he can control his emo-tion, then he has the potential to develop the courage(shaja cah) with confidence. In addition, this personwill have the courage to fight and justify the truth. Theinfluence of anger can make him arrogant. In con-trast, the absence of temper can make him becometimid. Individuals who have the bravery, yet don’tcontribute it to other people, will be known as proudindividuals. The normality of emotional soul (al-nafsal-ghadabiyyah) can affect the rational soul to facecharges. He will be given the advantage of manners(fadilat al-hilm) and the benefit of boldness to remain

calm. Moreover, if the privilege of courage (fadilatal-shaja cah) enables him to control his temper, thenhe will be brave (shajacah) to uphold justice and havefaith in making the right decision for himself.

Miskawayh separated the eight types of courageinto greatness of spirit, intrepidity, composure, for-titude, magnanimity, self-possession, manliness, andendurance. Fakhruddin al-Razi (Al-Razi, 1978), how-ever, asserted that humans are the God creatures whohave the intellect and wisdom other than the naturalfeeling and the orgasm. Such features of creation ex-poses humans to do damage on the face of the earth.This is because the combination of lust, emotional andintellectual emotions, can induce a person to be dom-inated by lust and excessive anger. Based on surah al-Baqarah (2:30), al-Razi (Al-Razi, 1978; Manawi andAkib, 2018)(tt: 4-5) explains that the damage on theearth is caused by lust, while the bloodshed is causedby angry emotions. However, the personality of an in-dividual will be perfect by always purifying God andpraising and admiring His supremacy.

Big Data is revolutionizing the peace and justicesector, declaration of data authorities, artificial intel-ligence processing technologies for case law analyticsand big data analysis for decision making. An idea ofdata justice is needed to establish the rule of law, con-cern for the new public–private interfaces of big data,namely the disciplinary and frequently discriminatorynature of large-scale databases, activist organizationsin the field of data and rights. For example, dealingwith data-driven for business transformation, obtain-ing coward demographics data based and potentialmisuse of data to unintended consequences. Theseare the challenges for courage to deal with difficultissues and impossible circumstances. Data collectionand analysis are shared between public authorities andthe commercial firms. The shared declaration is pro-vided by mobile phone, internet access and the userapplications (apps). Thus, the related social justiceconcern with datafication will benefit everyone in so-ciety, data fully support efficiency in the public sec-tor and public security. Hence, big data security forIoT domains should be an effective way in line withdata recovery. Enhancing Data Protection Standardsincrease the recognition of the need for accessing ahuge volume of the dataset across the world.

The process begins with developing a transferencedata guideline toolkit and clear knowledge reposi-tory of case studies for policymaker and policy leaderglobally. For instance, it requires trust and courage tomake a report on data leakage or cyber-attack. It is il-legal to transfer data that required cyber security anddata security. Data leakage can be protected by ad-vanced mathematical modeling in the encryption and

Four Types of Moral Holistic Values for Revolutionizing the Big Data Analytics in IoT-based Applications

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decryption of cryptography theory. Therefore, to pre-vent disclosing security breaches, they must be exer-cised with a sense of responsibility, integrity, honesty,courage and persisting for what is right.

2.4 Justice (al-cadalah)

Miskawayh (Miskawayh, 1977) recognized the moralholistic values with truly understanding the term it-self. Someone will be fair and just (al- cadalah)if they can control rational nature, anger and lust.These three privilege values are interconnected witheach other to support the justice attribute (fadilat al-cadalah). Moreover, if the three powerful values arepractised, then fairness and justice can be achievedglobally (Miskawayh, 1977)(Miskawayh, 1964) clas-sified that there are eight types of justice; friendship,concord, family fellowship, recompense, fair play,honest dealing, amiability and worship (al-ibadah).He said that man is both a social and political being bynature. He is born neither complete nor self-sufficientbut with deficiencies. He cannot, therefore, live byhimself alone but has to have the resources to helpother people in order to preserve himself as well as toremedy his weakness and become complete throughthe co-operation of others (Miskawayh, 1977; Misk-awayh, 1964; Miskawayh, 1951).

The concept of data justice is that everyone has theright to be treated fairly by the public and private au-thorities. Data justice affects different aspects of ourlives. The production of digital data is fairness in theway people are made visible, represented and treated.Fair data principles emphasize enhancing the abilityof machines to find and to use the data automatically(Alias et al., 2018).

In addition, these principles support its reuse byindividuals in the e-community for case law analyt-ics. Data analysis should be performed by fair mea-surement and fair decision making. Moreover, fairtreatment is an important tool in justice work. Dataprovider, data repositor and data depositor should betreated fairly and with sensible principles in the digitallibrary and the repository management. Big data setscan improve the accountability and functionally of thedigital library and repository. Hence, worldwide dataecosystem will be encountered by the fair data sys-tem. Furthermore, inspiring the sense of wisdom andfairness of spirit is the main focus in the revolutionof big data analytics and IoT applications. The moralholistic values help to bring the revolution of humandevelopment.

For instance, Khan et al. (Miskawayh, 1964) clas-sified the value of the different phases of IoT data col-lection including all phases of its business value. To

decide ethical parts, all four holistic values are neededto establish the rule of law and data justice.

3 IMPLEMENTATION ANDRESULTS

Since the inception of HPC systems, it was realizedthat IoT is a crucial tool to be utilized by the human.The behavior, psychological and physiological prin-ciples were influenced by the moral holistic value andgood human factors. The billions of physical devicesaround the world are presently connected to the in-ternet, gathering and sharing data information basedon IoT innovations. Xie, R., et al., (Xie et al., 2018)stated issues such as huge communication costs, high-speed training for the machine learning process, se-curity for managing a big data require the successfulintegration of holistic values and high generation ofcomputer systems. In order to fulfill people’s ben-eficial values, it is necessary to have a superior un-derstanding of transition from small to huge data an-alytics, the idea of sharing for conducting the hugememory architecture of HPC, the integrity, safety andprivacy values in preventing the leaking of data (Liuet al., 2015), trust in the network communication andthe information bank sharing. Hence, for cloud aswell as IoT dataset, authenticator-based informationintegrity validation techniques were analysed by Liu,C., et al. (Liu et al., 2015). An analysis regardinglightweight asymmetric encryption, the AAβ (AA-Beta) was performed by Adnan, Isa and Hashi (Adnanet al., 2016). It is possible that the execution on the‘Things’ is practiced as a way to enhance the networkcommunication of IoT. In order to ensure the abil-ity of authentication, privacy and integrity through-out the collection of sensed data, a flexible method-ology which applied elliptic curve cryptography wasproposed by Al-Turjman and Alturjman (Al-Turjmanand Alturjman, 2018).


Most research activities involve physical equipment,data collection and analysis of the IoT-based applica-tion. Next, the research proposed the prediction anddecision making based on the analysis indicator ofthe parameter changes. For example, eye blinks, eyemovements, and muscle stress are important biolog-ical sources to investigate the characterization of dy-namic brain activation. We can build a holistic expe-rience for data collecting process across IoT devices


360

that span ensuring the impact of IoT technologies andcharacteristics of the glory morality and ethical be-havior.

By ensuring data quality, we will mitigate risksassociated with bad data and eliminate data doubts.Trusted network communication among HPC is ableto support the message passing paradigm and largesparce memory allocation. Second, the machinelearning was chosen to implement ANN honestly.For fair decisions, a classification algorithm of ma-chine learning is based on the most accurate classi-fication rule on possibly-reweighted data, while thefairness enforcer checks the chosen weighted param-eter. The training data is reweighted based on the out-put of the fairness enforcer and passed back the pa-rameter changes to train the classification algorithm.Third, in parallelelization process, data decomposi-tion is a highly effective technique for breaking workinto small tasks. Data derived from decompositiontechniques are applied to explain fairness phenom-ena. Making decisions are also taking responsibilityand learning courage to deal with the consequences.Lastly, to control the parameter changes process, webbased software is developed. Thus, justice must beginwith a decision concerning the integrated methods tobe employed rationally.

5 CONCLUSION

The sustainable of big data analytics in IoT-based ap-plications should be integrated with four moral holis-tic values. This cycle starts from things to data, infor-mation, knowledge, wisdom, glory morality, courage,justice, services, people and back to things. Intel-ligent information technology application constructsIoT cycle, which leads to a harmonious symbiosis.The harmonious attention obtains an accurate predic-tion, visualization and decision making. Thus, thispaper highlights four privilege values to bridge thegap between IoT-based applications, people and prac-tice which contribute to revolutionizing the big dataanalytics in IoT application holistically.

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Al-Razi, A. B. (1978). al-tibb al-ruhani. Disunting olehMajid Fakhri in al-Fikr al-Akhlaqi al-Arabi, 2:27–64.

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AUTHOR INDEX

Abdurrahman, M. 15, 315, 331Abuadabba, M. . . . . . . . . . . 175Afdhol, M. . . . . . . . . . . . . . . 315Afrireksa, B. . . . . . . . . . 15, 331Alfroji, M. . . . . . . . . . . . . . . 175Alias, N. . . . . . . . . . . . . . 49, 357Amar, I. . . . . . . . . . . . . . . . . . 175Anif, B. . . . . . . . . . . . . . . . . . 229Ardiansyah, R. . . . . . . . . . . . . 74Ariadji, T. . . . . . . . . . . 285, 342Ariyon, M. . . . . . . . . . . . . . . 102Arridho, S. . . . . . . . . . . . . . . . 80Arta, Y. . . . 125, 146, 200, 211,

243, 268Asteriani, F. . . . . . . . . . 169, 182Astuti, P. . . . . . . . . . . . . . . . . 169Aziz, P. . . . . . . . . 285, 291, 342

Bae, W. . . . . . . . . . . . . . . . . . . 15Batara . . . . . . . . . . . . . . . 35, 237Binti Mohd Zaid, H. . . . . . . 322Bonti, R. . . . . . . . . . . . . . . . . 285

Chandra, S. . . . . .285, 291, 342Choanji, T. . . . . . . . . . . . . . . . 26

Dalilla, F. . . . . . . . . . . . . . . . . 74Damanhuri, H. . . . . . . . . . . . . 90Damayandri, D. . . . . . . . . . . . 15Daton, W. . . . . . . 285, 291, 342Defitra, B. . . . . . . . . . . . . . . . . 26Desti . . . . . . . . . . . . . . . . . . . 250Dwimax, H. . . . . . . . . . . . . . 285

Efras, M. . . . . . . . . . . . . . . . . 114Eka Putra, D. . . . . . . . . . 35, 120Elvitaria, L. . . . . . . . . . . . . . . 68Erdisna . . . . . . . . . . . . . . . . . 146Erfando, T. . . . . . . . . . .175, 299

Fahroji . . . . . . . . . . . . . . . . . . 151Fathan, E. . . . . . . . . . . . . . . . 299Febrianti, D. . . . . . . . . . . . . . 194Fitmawati . . . . . . . . . . . . . . . 250

Gunawan, H. . . . . . . . . . . . . . 11

Habibi, M. . . . . . . . . . . . . . . . .35Hadi, N. . . . . . . . . . . . . . . . . . . 49Hadziqoh, N. . . . . . . . . . . . . 322Hafizhah T., M. . . . . . . . . . . 182Hakim, A. . . . . . . . . . . . . . . . . 55Hariyadi, D. . . . . . . . . . . . . . . 85

Herianto . . . . . . . . . . . . . . . . 291Heriyadi, N. . . . . . . . . . . . . . . . 5Hidayat, F. . . . . . . . . . . . . . . 315Hisyam, M. . . . . . . . . . . . . . . . 74

Ilona, D. . . . . . . . . . . . . . 90, 229Indra, Z. . . . . . . . . . . . . . . . . . .68Irie, H. . . . . . . . . . . . . . . . . . . 130Isda, M. . . . . . . . . . . . . . . . . . 250

Jannah, M. . . . . . . . . . . . . . . 219Junaidi . . . . . . . . . . . . . . . . . . . 90

Kadir, E. 20, 64, 130, 135, 140Kausarian, H. . . . 35, 120, 219,

237Khaerani, L. . . . . . . . . . . . . . 274Khalid, I. . . . . . . . . . . . . . . . . 322Kiswiranti, D. . . . . . . . . . . . . . . 5

Labellapansa, A. . . 64, 98, 326Latief, Y. . . . . . . . . 41, 258, 274Lubis, H. . . . . . . . . . . . . . . . . 315Lubis, M. . . . . . . . . . . . . . . . 237

Machfudiyanto, R. . . . 258, 274Mardianto . . . . . . . . . . . . . . . 182Mildawati, R. . . . . . . . . . . . . 311Mindhayani, I. . . . . . . . . . . . . . 5Mualfah, D. . . . . . . . . . . . . . . 85Muchlis . . . . . . . . . . . . . . . . . . . 5Muchtar, A. . . . . . . . . . . . . . 254Muhammad, R. . . . . . . . . . . 163Mulyaningsih, S. . . . . . . 5, 349Mursyidah . . . . . . . . . . . . . . 322

Nainggolan, J. . . . . . . . . . . . 342Nasution, A. . . . . . 55, 155, 163Nasution, S. . . . . . 55, 155, 163Ngipol, D. . . . . . . . . . . . . . . . 304Nopiyanto . . . . . . . . . . . . . . . 219Novendra, R. . . . . . . . . . . . . 188Novriansyah, A. . . . . . . 15, 331Novrianti . . . . . . . . . . . . . . . . 114Nugraha, I. . . . . . . . . . . . . . . . 74Nugraha, P. . . . . . . . . . . . . . . . 31Nugrahawan, S. . . . . . . . . . . 342

Othman, M. . . . . . . . . . . 64, 135

Palaoag, T. . . . . . . . . . . . . . . 304Pratama, H. . . . . . . . . . . . . . 268Pratiwi, E. . . . . . . . . . . . . . . . 169

Primawati . . . . . . . . . . . . . . . 237Puri, A. . . . . . . . . . . . . . . . . . 311Putra, D. . . . . . . . . . . . . 219, 237Putri, T. . . . . . . . . . . . . . . . . . 169

Rahmadani, A. . . . . . . . . . . . 322Ramadhan, R. . . . . . . . . . . . . 85Revolin, E. . . . . . . . . . . . . . . 342Rita, N. . . . . . . . . . . . . . . . . . 102Rizki, S. . . . . . . . . . . . . . . . . 211Rizki, Y. . . . . . . . . . . . . . . . . 163Rosa, S. . . . . 20, 130, 135, 140Rosadi, S. . . . . . . . . . . . . . . . 169Rosyadi . . . . . . . . . . . . . . . . . 254Rulan S., A. . . . . . . . . . . . . . 182

Saad, B. . . . . . . . . . . . . . . . . . 140Sabli, T. . . . . . . . . . . . . . . . . . . 80Sabri, S. . . . . . . . . . . . . . . . . .243Sagita, L. . . . . . . . . . . . . . . . . . 41Salih, Z. . . . . . . . . . . . . . . . . .175Salman . . . . . . . . . . . . . . . . . 205Salman, S. . . . . . . . . . . . . . . 205Samba, M. . . . . . . . . . . . . . . 175Samsunan . . . . . . . . . . . . . . . 194Sanjaya, R. . . . . . . . . . . . . . . . 11Saputra, S. . . . . . . . . . . . . . . 151Sari, N. . . . . . . . . . . . . . . . . . 315Setiawan, P. . . . . . . . . . 200, 268Setiawan, T. . . . . . . . . . . . . . 102Shin, H. . . . . . . . . . . . . . . . . . 331Siahaan, N. . . . . . . . . . . . . . . . 41Siswanto, A. 11, 125, 211, 268Sjarmidi, A. . . . . . . . . . . . . . 205Solihin, M. . . . . . . . . . . . . . . 311Suandi, F. . . . . . . . . . . . . . . . 188Suhartono . . . . . . . . . . . . . . . . . 5Sukirman . . . . . . . . . . . . . . . . . . 5Sundaram, M. . . . . . . . . . . . . 64Suryadi, A. . . . . . . . . . . 35, 237Suryani, D. . . . . . . . . . . . . . . 146Sutisna, R. . . . . . . . . . . . . . . 200Sutrisna, N. . . . . . . . . . . . . . 151Swastika, S. . . . . . . . . . . . . . 151Syafitri, N. . . . . . . . . . . . . . . 211Syaliman, K. . . . . . . . . . . . . 326Syarif, F. . . . . . . . . . . . 120, 219Syawaldi . . . . . . . . . . . . . . . . 109Syukur, A. . . . . . 140, 243, 268

Tanjung, M. . . . . . . . . . . . . . . 74Tripardi, J. . . . . . . . . . . . . . . 219

363

Trisnawati, L. . . . . . . . . . . . . . 68

Ulhaq, A. . . . . . . . . . . . . . . . 258Ulpah, S. . . . . . . . . . . . . 80, 151

Wahyuni, S. . . . . . . . . . . . . . 125Wijaya, R. . . . . . . . . . . . . . . . 315

Winaldi, D. . . . . . . . . . . . . . . 114Wongso, J. . . . . . . . . . . . . . . 229

Yamita, F. . . . . . . . . . . . . . . . 155Yuliani, A. . . . . . . . . . . . . . . . .98Yulianti, A. . . . . . . . 64, 98, 326

Yulis, P. . . . . . . . . . . . . . . . . . 250Yuskar, Y. . . . . . . . . . . . . . . . . 26

Zaitul . . . . . . . . . . . . . . . 90, 229Zamsuri, A. . . . . . . . . . . . . . 188Zulrian Aldio, R. . . . . . . . . . 337

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