Performance Evaluation of the K-Means Clustering Method in Grouping Indonesian Provinces Based on Potential Disaster Impact

Sitti Masyitah Meliyana; Anugra S. S. Dunggio; Ansari Saleh Ahmar

doi:10.35877/454RI.jinav4696

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JINAV: Journal of Information and Visualization

Vol. 6 No. 2 (2025), Pages 123-131 · 2025-12-31

OriginalPaper | Open access | Published: December 31, 2025

Performance Evaluation of the K-Means Clustering Method in Grouping Indonesian Provinces Based on Potential Disaster Impact

Sitti Masyitah Meliyana, Anugra S. S. Dunggio, Ansari Saleh Ahmar

JINAV: Journal of Information and Visualization, Vol. 6 No. 2 (2025), pp. 123-131 https://doi.org/10.35877/454RI.jinav4696 Published: 2025-12-31

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Abstract

This study aims to cluster the provinces in Indonesia based on their level of potential disaster impact, which consists of hazard area, exposed population, physical losses, economic losses, and environmental damage, using the K-Means clustering algorithm and to evaluate the performance of the resulting model. The optimal number of clusters was determined using the Silhouette Coefficient and the Elbow Method with the Within-Cluster Sum of Squares (WSS) approach. The performance evaluation of the K-Means clustering was conducted using the Davies–Bouldin Index (DBI). Based on the selection of the optimal number of clusters, the Silhouette Coefficient produced the highest value at K=3, with a score of 0.699. Similarly, the Elbow Method showed a significant decrease in the mean WSS at K=3, indicating that three clusters were optimal. The performance evaluation using DBI for K=3 resulted in a score of 0.30. According to the principle of DBI evaluation, the closer the DBI value is to zero (without being negative), the better the clustering quality. Therefore, it can be concluded that the K-Means clustering algorithm successfully produced a very good clustering structure in grouping Indonesian provinces based on their potential disaster impact.

Keywords

Davies-Bouldin Index (DBI)Disaster Impact Elbow K-Means Clustering Silhouette Coefficient

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How to Cite

Meliyana, S. M., Dunggio, A. S. S., & Ahmar, A. S. (2025). Performance Evaluation of the K-Means Clustering Method in Grouping Indonesian Provinces Based on Potential Disaster Impact . JINAV: Journal of Information and Visualization, 6(2), 123–131. https://doi.org/10.35877/454RI.jinav4696