<![CDATA[Food security in West Java Province exhibits significant variation across regencies/cities, influenced by differences in socioeconomic conditions, health, and sanitation. This condition necessitates an analytical approach based on regional clustering to support the formulation of more precise policies. This study aims to cluster regions based on the Food Security Index (FSI) and to evaluate the performance of K-Means and Hierarchical Clustering (Ward) in producing an optimal cluster structure. The data used comprised 27 regencies/cities with eight standardized FSI indicators. Cluster quality was evaluated using the Silhouette Coefficient and the Davies-Bouldin Index. The results indicate that the optimal FSI structure is divided into three clusters, each exhibiting distinct regional characteristics. Both methods produced consistent patterns; however, K-Means demonstrated superior performance to Ward, yielding a Silhouette Coefficient of 0.3048 and a Davies-Bouldin Index of 1.0725, which were respectively higher and lower than those obtained by Ward (0.2806 and 1.1241). This finding indicates the superiority of K-Means in forming more compact and well-separated clusters within relatively homogeneous data. Further analysis reveals that disparities in food security are primarily influenced by access to sanitation, poverty, education, and the ratio of health workers. This study provides empirical evidence on the effectiveness of clustering methods for FSI analysis and offers a regional clustering framework capable of supporting data-driven food security policy formulation at the regional level.]]>
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