Regional advancement is underpinned by human development. Its constituent dimensions encompass health, education, and decent living standards. Based on Human Development Index, this study aims to classify 35 regencies in Central Java. The clustering algorithm utilizes Block-based K-Medoids, employing the Elbow Method to determine the optimal number of clusters and applying the Euclidean Distance to calculate object distances. Through four iterations, the study yields three optimal clusters. Cluster 1 (high category) comprises 4 members, cluster 2 (medium category) consists of 15 members, and cluster 3 (low category) encompasses 16 members. Cluster 1 demonstrates satisfactory achievements in each dimension of human development. Cluster 2 requires improvement in its educational dimension, particularly regarding the average length of schooling indicator. Cluster 3 demands greater attention to enhance educational and decent living standards dimension.
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