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Wahyu Hadikristanto
Universitas Pelita Bangsa
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Grouping of Village Status in West Java Province Using the Manhattan, Euclidean and Chebyshev Methods on the K-Mean Algorithm Pranoto, Gatot Tri; Hadikristanto, Wahyu; Religia, Yoga
JISA(Jurnal Informatika dan Sains) Vol 5, No 1 (2022): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v5i1.1097

Abstract

The Ministry of Villages, Development of Disadvantaged Areas and Transmigration (Ministry of Village PDTT) is a ministry within the Indonesian Government in charge of rural and rural development, empowerment of rural communities, accelerated development of disadvantaged areas, and transmigration. Village Potential Data for 2014 (Podes 2014) in West Java Province is data issued by the Central Statistics Agency in collaboration with the Ministry of Village PDTT which is in unsupervised data format, consists of 5319 village data. The Podes 2014 data in West Java Province were made based on the level of village development (village specific) in Indonesia, by making the village as the unit of analysis. Base on the Regulation of the Minister of Villages, Disadvantaged Areas and Transmigration of the Republic of Indonesia number 2 of 2016 concerning the village development index, the Village is classified into 5 village status, namely Very Disadvantaged Village, Disadvantaged Village, Developing Village, Advanced Village and Independent Village based on the ability to manage and increase the potential of social, economic and ecological resources. Village status is in fact inseparable from village development that is under government funding support. However, village development funds have not been distributed effectively and accurately according to the conditions and potential of the village due to the lack of clear information about the status of the village. Therefore, the information regarding the villages priority in term of which villages needs more funding and attention from the government is still lacking. Data mining is a method that can be used to group objects in a data into classes that have the same criteria (clustering). One of the algorithms that can be used for the clustering process is the k-means algorithm. Data grouping using k-means is done by calculating the closest distance from data to a centroid point. In this study, different types of distance calculation in the K-means algorithm are compared. Those types are Manhattan, Euclidean and Chebyshev. Validation tests have been carried out using the execution time and Davies Bouldin index. From this test, the data Village Potential 2014 in West Java province have grouped all the 5 status of the village with the obtained number of villages for each cluster is a cluster village Extremely Backward many as 694 villages, cluster Villages 567 villages, cluster village Evolving as much as 1440 villages, the cluster with Desa Maju1557 villages and the cluster Independent Village for 1061 villages. For distance calculation, Chebyshev has the most efficient accumulation time of 1 second compared to Euclidean 1.6 seconds and Manhattan 2.4 seconds. Meanwhile, the Euclidean method has the value, Davies Index most optimal which is 0.886 compared to the Manhattan method 0.926 and Chebyshev 0.990.
Co-Authors ., Sapardi Abdul Halim Anshor Abdul Hasyim Abimanyu, Aldo Anggito Achmad Firmansyah Putra Adriansyah, Putri Nabila Adinda Agung Nugroho Ahmad Gunawan Ahmad Zy Ahmad, Asyari Alfarizi, Muhammad Farhan Ali Nurdiansyah Ananto Tri Sasongko Andika, Sophian Andri Firmansyah Anggara, Bastian Anisa Anisa Anisa Rahmawati Anshor , Abdul Halim Ansor, Abdul Halim Ariandi, Sheva Rizky Arvita Emarilis Intani Aswan S Sunge Atma, Dodit Ardi Atthoriq, Syaifullah Ayu Fitriyani Badruzzaman, Aceng Dahyoung Yenuargo Dichi Setiawan Diki Febriani Dodit Ardiatma Doni, Muhamad Edi Junianto Edi Widodo Edora Edora Edora Edora, Edora Edy Widodo Eko Budiarto Ermanto Fadlurrohman, Muhammad Shiddiq Fajar Arief Rachman Fatchan, Muhammad Fauzi Ahmad Muda Gatot Tri Pranoto Hanif, Sa’ad Khairudin Herdyanto, Febro Herol, Herol Holwati Ikmal Riyan Firmansyah Imam Nasai2 Indradewa, Rhian Intan Sari Rahayu Irfan Afriantoro Irfan Afriantoro Ismasari Ismasari Jamroni, A. Reza Baehaqa Jamroni Karsito, Karsito Keswanto Kurniadi, Nanang Tedi Laki, Abraham Leo Contantinus Meze Listanto, Firgiawan Maulida Ramadhan Mico Giovanni Dermawan Miharja, Muhammad Najamuddin Dwi Muhamad Fatchan Muhammad Fatchan Muhammad Makmun Effendi Muhammad Suprayogi2 Naufal Muyassar Nawangsih, Ismasari Nita Paramita Njai Njai Nur Azizah Nurhadi Surojudin Nurul Ariffaeni Islami Oktavianto, Rainal Zulian Permana , Indra Pradini, Purnama Sakhrial Prasetyo Prasetyo Pratama, Galang Rintang Widya Prayoga, Dimas Purdianto Purdianto Purwanto Purwanto Purwanto Putri N.A, Anindya Rahmawati, Shinta Melliana Rahmawati Rasmiati Nur Aeni Retno Purwani Setyaningrum Risky Bambang Sutrisna romanuddin, ahmad Rosyati Adelia S Suprapto Sandi Salvan N N Sanudin Satria Permana, Muhammad Safri Setiawan, Dani Yuda Dwi Siska Wulandari, Siska Suderajat, Agung Sufajar, Sufajar Sufajar, Suprapto Suhardian Suhardian Suherman Suherman Suherman Sunaryati , Titin Sunita Dasman Sya syah Apriliyani Syach, Ridwan Syariefur Rakhmat, Adrianna Taofik Safrudin Taufik Hidayat Tiani Ayu Lestari Tiara Deswara Pungkas Tri Ngudi Wiyatno Turmudi Zy, Ahmad Vidya Anis Fitri Yahya, Adiba Yahya, Adibah Yoga Religia Yusup, Diana