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All Journal INFORMAL: Informatics Journal
Fajrin Nurman Arifin
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Computer Science & IT

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Pengelompokkan Daerah Rawan Bencana di Kabupaten Jember Menggunakan Metode K-Means Clustering Nilam Wahidah; Oktalia Juwita; Fajrin Nurman Arifin
INFORMAL: Informatics Journal Vol 8 No 1 (2023): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v8i1.29542

Abstract

This research aims to classify disaster-prone areas in Jember Regency based on disaster-prone index indicators in 31 sub-districts in Jember Regency. The 6 indicators used in this study are the number of disaster events, the number of victims killed, the number of injured victims, the number of damaged houses, the amount of damage to infrastructure and population density. The clustering method used is the K-Means Clustering method. This method is considered quite effective and efficient for grouping large amounts of data. Researchers also used the Davies Bouldin Index (DBI) method to determine the optimal number of clusters (k) used in the clustering process. The results of this study are the optimal number of clusters (k) is k = 3 with the cluster test k = 2 to k = 10, by classifying groups of low vulnerability, medium vulnerability and high vulnerability.
Co-Authors Nilam Wahidah Oktalia Juwita