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p-Index From 2021 - 2026
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All Journal UNP Journal of Statistics and Data Science
Zahrani Asyati Zulika
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Journal : UNP Journal of Statistics and Data Science

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Cluster Analysis of Earthquakes on the Island of Sumatera in 2024 Using the DBSCAN Method Zahrani Asyati Zulika; Yenni Kurniawati
UNP Journal of Statistics and Data Science Vol. 4 No. 1 (2026): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol4-iss1/466

Abstract

Earthquakes are one of the most destructive and unpredictable natural disasters. Sumatera Island, being located along the Semangko Fault, typically experiences seismic movement due to contact between the Indo-Australian plate and the Eurasian plate. In this study, the DBSCAN method classifies earthquake incidents in Sumatera in 2024 into magnitude and depth categories. The data set, collected by the Meteorology, Climatology, and Geophysics Agency (BMKG), includes 163 earthquake events that occurred in Sumatera Island during 2024. The clustering process identified two main clusters: one representing deep earthquakes in inland areas and another consisting of shallow earthquakes along the western offshore region, near the megathrust zone. The Silhouette Coefficient was used to verify the clustering outcome, and the result was 0,58, which verifies a good formation of clusters. These findings provide insights into seismic patterns in Sumatera and can support disaster mitigation efforts.
Co-Authors Yenni Kurniawati