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Viki Flendiansyah
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Clustering of Earthquakes on The Island of Java Using K-Means Algorithm Based on Magnitude and Depth Viki Flendiansyah; Hakim, Dimara Kusuma; Feri Wibowo; Agung Purwo Wicaksono
Jurnal E-Komtek (Elektro-Komputer-Teknik) Vol 9 No 1 (2025)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/e-komtek.v9i1.2397

Abstract

Indonesia is one of the countries with a high level of earthquake vulnerability because it is located in the Pacific Ring of Fire. Java Island, as the most populous region and the center of the national economy, has a great risk of earthquake impacts. This study aims to analyze earthquakes in Java Island during the 2019-2024 period using the K-Means algorithm. Clustering the data based on magnitude, depth, location, and time of occurrence resulted in three clusters that reflect the characteristics of earthquakes in the region. This clustering provides important insights into the distribution and intensity of earthquakes in Java. The information obtained can be used to support disaster mitigation efforts more strategically. The government and community are expected to be able to increase preparedness for disaster risks and design effective mitigation policies to minimize the impact of future earthquakes. This research shows the great potential of applying data-driven technology as a basis for decision-making in disaster mitigation in Indonesia.