Exploring the Discretization of Peak Ground Acceleration Variables: a Comparative Analysis of K-means and K-medoids

The susceptibility of Indonesia to seismic activity as a result of intricate interactions between tectonic plates highlights the imperative for a robust policy aimed at mitigating the impact of such events. Although accurately predicting the precise timing of an earthquake remains a formidable task, evaluating the possibility for resultant damage can significantly enhance efforts in disaster preparedness. The primary objective of this study is to investigate the process of discretizing the variable known as peak ground acceleration (PGA). Discretization refers to the process of transforming a continuous variable into a finite set of discrete values. In the present context, the K-means and K-medoids clustering algorithms were modified and assessed in terms of their effectiveness in discretizing PGA variables. The utilized assessment metric is the average silhouette width, which serves as a quantifiable indicator of the quality of clusters. Based on a thorough analysis and comparison of outcomes, it has been ascertained that the K-means algorithm has enhanced discretization capabilities, leading to the formation of distinct clusters characterized by increased cohesiveness and separation. The aforementioned findings provide a contribution to the progress of earthquake damage assessment approaches and offer vital insights for disaster management and response planning in regions prone to earthquakes. The correlation between the discretization capabilities of the K-means algorithm and its contribution to damage assessment, particularly considering that PGA is a critical factor in determining damage levels. PGA indicates the strength and duration of the shock depending on the size and location of the source. Information from the PGA can be useful for minimizing losses arising from earthquake phenomena in the area. Therefore, studying the magnitude of PGA, one of which is maximum ground acceleration, is important in evaluating the impact it has on the condition of an area and can be a reference for the government and society in the process of building earthquake-resistant structural and infrastructure facilities.

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Publication Details

Journal
The Philippine journal of science
Published
2024-10-01
DOI
https://doi.org/10.56899/153.05.14
Citations
1
Primary Topic
Diverse Approaches in Healthcare and Education Studies
Type
article
Field-Weighted Citation Impact
0.54
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article

Exploring the Discretization of Peak Ground Acceleration Variables: a Comparative Analysis of K-means and K-medoids

Dedi Rosadi, Devni Prima Sari, Media Rosha
1 citations
The Philippine journal of science
Diverse Approaches in Healthcare and Education Studies
0.54
article

Exploring the Discretization of Peak Ground Acceleration Variables: a Comparative Analysis of K-means and K-medoids

Dedi Rosadi, Devni Prima Sari, Media Rosha
article en
1 citations

Abstract

The susceptibility of Indonesia to seismic activity as a result of intricate interactions between tectonic plates highlights the imperative for a robust policy aimed at mitigating the impact of such events. Although accurately predicting the precise timing of an earthquake remains a formidable task, evaluating the possibility for resultant damage can significantly enhance efforts in disaster preparedness. The primary objective of this study is to investigate the process of discretizing the variable known as peak ground acceleration (PGA). Discretization refers to the process of transforming a continuous variable into a finite set of discrete values. In the present context, the K-means and K-medoids clustering algorithms were modified and assessed in terms of their effectiveness in discretizing PGA variables. The utilized assessment metric is the average silhouette width, which serves as a quantifiable indicator of the quality of clusters. Based on a thorough analysis and comparison of outcomes, it has been ascertained that the K-means algorithm has enhanced discretization capabilities, leading to the formation of distinct clusters characterized by increased cohesiveness and separation. The aforementioned findings provide a contribution to the progress of earthquake damage assessment approaches and offer vital insights for disaster management and response planning in regions prone to earthquakes. The correlation between the discretization capabilities of the K-means algorithm and its contribution to damage assessment, particularly considering that PGA is a critical factor in determining damage levels. PGA indicates the strength and duration of the shock depending on the size and location of the source. Information from the PGA can be useful for minimizing losses arising from earthquake phenomena in the area. Therefore, studying the magnitude of PGA, one of which is maximum ground acceleration, is important in evaluating the impact it has on the condition of an area and can be a reference for the government and society in the process of building earthquake-resistant structural and infrastructure facilities.

The Philippine journal of scienceVol. 153(5)
Openalex Percentile: Top 25%
Diverse Approaches in Healthcare and Education Studies
0.54
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Exploring the Discretization of Peak Ground Acceleration Variables: a Comparative Analysis of K-means and K-medoids — Dedi Rosadi, Devni Prima Sari, et al. · The Philippine journal of science (2024) | TGRS Research Map | TGRS