DOI: https://doi.org/10.14710/jfma.v7i2.21931

Recognizing the Spatial Distribution and Voronoi Patterns of the Recorded Earthquake Epicenters in Sunda Strait, Indonesia

Triyana Muliawati  -  Department of Mathematics, Institut Teknologi Sumatera, Indonesia
*Fuji Lestari orcid  -  Department of Actuarial Sains, Sumatera Institute of Technology, Lampung Selatan, Lampung, Indonesia, Indonesia
Mika Alvionita  -  Department of Science Data, Institut Teknologi Sumatera, Indonesia
Ardika Satria  -  Department of Actuarial Science, Institut Teknologi Sumatera, Indonesia
DG Harbowo  -  Center for Sustainable Development Goals Studies (ITERA SDGs Center) and Department of Geology, Institut Teknologi Sumatera, Indonesia

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Abstract

Currently, Sunda Strait is one of the most active transportation hubs. However, this region also bears a notable history of geohazards associated with the dynamics of tectonic activity of the Eurasian and Indo-Australian tectonic plates, such as the super-eruption of Krakatoa volcano in 1883, the Sunda Strait tsunami in 2018, and decades of frequent earthquakes. To address these challenges, this study conducted a statistical analysis of the frequency and distribution of seismic activities in the Sunda Strait region based on recorded epicenter data in the United States Geological Survey's (USGS) Earthquake catalog. We assembled 440 multivariate earthquake data points between 1990 and 2023 (over three decades). The results of this study indicate that the machine learning approach precisely identifies four relevant parameters for -means clustering, followed by an analysis of silhouette values to recognize Voronoi patterns. These statistical patterns also have significant implications for the number of epicenter clusters and recognizing their spatial distribution. It provides a new understanding of the spatial-temporal characteristics and locates the list of frequent earthquake regions. Having all the necessary information would help to comprehensively evaluate geohazard risks in Sunda Strait region.

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Keywords: earthquake, k-means clustering, silhouette, sunda strait, voronoi

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Section: FUNDAMENTAL MATHEMATICS AND APPLICATIONS
Language : EN
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