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All Journal Jurnal Tekno Kompak Journal of Students‘ Research in Computer Science (JSRCS)
Arrasyid, Rizky Maulana
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Journal : Journal of Students‘ Research in Computer Science (JSRCS)

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Pengelompokan Penerima Bantuan Kerusakan Bangunan Akibat Bencana Alam di Jawa Barat Menggunakan Algoritma K-Means Arrasyid, Rizky Maulana; Herlawati, Herlawati
Journal of Students‘ Research in Computer Science Vol. 5 No. 1 (2024): Mei 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/c8btc203

Abstract

Disasters have a tremendous impact on society, one of the impacts of natural disasters is building damage, a province that is very prone to natural disasters is West Java province and results in a lot of building damage due to disasters, the solution to this disaster needs building assistance caused by natural disasters. In this study discusses the application of the K-Means Clustering algorithm for recipients of aid due to natural disasters, this study took data from West Java open data with a data set of house damage this data consists of 2012-2022 covering 27 districts / cities in West Java Province. This research uses the Cross-Industry Standard Process for Data Mining (CRISP-DM) method which has six stages. The results of the data processed using K-Means clustering are divided into 4 clusters, namely, the level of highly prioritized clusters (C0), the level of prioritized clusters (C1), the level of less prioritized clusters (C2), and the level of non-prioritized clusters (C3), In this study, clusters that are highly prioritized in receiving assistance are Bogor Regency, Bandung Regency, Cianjur Regency, Garut Regency, Sukabumi Regency, and Tasikmalaya Regency.
Co-Authors Herlawati Herlawati Putera, Diaz Enggar Yusuf, Ajif Yunizar Pratama