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All Journal Jurnal Statistika dan Komputasi (STATKOM)
Sulistiyani, Dwi
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

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Pengelompokkan Wilayah Banjir di Jawa Tengah untuk Mitigasi Banjir Menggunakan Pendekatan K-Medoids Sanmas, Safril Ahmadi; Nurmalita, Rahma; Sulistiyani, Dwi; Haris, M. Al
Jurnal Statistika dan Komputasi Vol. 3 No. 2 (2024): Jurnal Statistika dan Komputasi
Publisher : Universitas Nahdlatul Ulama Sunan Giri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/statkom.v3i2.3223

Abstract

Background: Flooding is a natural event that can occur at any time, often resulting in fatalities and significant material losses. Mapping flood zones in Central Java based on flood occurrences is crucial for optimizing disaster management. Clustering approaches are highly relevant and potential methods for tackling flood mitigation challenges in Central Java. Objective: To map flood zoning in Central Java using the optimal K-Medoids method based on the Silhouette Coefficient. Methods: This study uses the K-Medoids method for Clustering analysis because it is more resistant to outliers. Unlike K-Means, K-Medoids selects the medoid as the cluster center, making it more stable against extreme values. The data used was obtained from the Dinas PUSDATARU of Central Java Province regarding flood events in the region from October 1, 2022, to March 2023. Results: The K-Medoids method with k=2 produced the highest Silhouette Coefficient of 0.83748, Clustering 34 districts/cities with low flood occurrences and 1 district/city with high flood occurrences. This model evaluation supports the planning of disaster mitigation policies that focus more on flood-prone areas. Conclusion: There are two groups of districts/cities based on flood occurrence levels. The high Silhouette Coefficient value indicates a good cluster structure.
Co-Authors M. Al Haris Nurmalita, Rahma Sanmas, Safril Ahmadi