<![CDATA[Employment is an important dimension of regional development because it reflects job opportunities, labour market participation, and social welfare. Single indicators cannot fully capture employment conditions, especially in regions with significant labour market disparities such as Central Java. This study groups regencies and cities in Central Java using multiple employment indicators and the Block-Based K-Medoids clustering algorithm. The study uses 2024 secondary data from the Central Java Statistics Agency, comprising the open unemployment rate, labour force participation rate, average monthly wage, proportion of youth aged 15–24 classified as NEET (not in education, employment or training), and number of industries. All variables were normalized with Min-Max normalization before clustering to ensure comparability across indicators with different measurement scales. The optimal number of clusters was determined using the Silhouette, Calinski-Harabasz, and Hartigan indices, all of which indicated that three clusters were optimal. The results show that Cluster 1 is characterized by relatively high unemployment and NEET rates and low wages, Cluster 2 represents regions with the most favourable employment conditions, and Cluster 3 has the highest average wages but the lowest labour force participation rate. These findings provide a useful basis for more targeted employment policy formulation in accordance with regional labour market characteristics, and they may support local governments in identifying priority areas for intervention and development planning.]]>
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