K-Medoids Clustering Analysis of Regional Development in West Sumatra Based on Socioeconomic Indicators

Abstrak

Regional development disparities among districts and cities in West Sumatra Province remain a persistent challenge, reflected in significant differences across economic, social, and employment indicators. This study aims to cluster 19 districts/cities in West Sumatra Province based on socioeconomic indicators using the K-Medoids clustering method. The variables include GRDP per capita, economic growth rate, GRDP percentage distribution, Human Development Index (HDI), poverty rate, and open unemployment rate, using 2024 data obtained from the Central Bureau of Statistics (BPS) of West Sumatra Province. The optimal number of clusters was determined using the Elbow method, resulting in three clusters. Cluster 1 consists of 12 districts characterized by the lowest average GRDP per capita and HDI, along with the highest poverty rate. Cluster 2 comprises only Kota Padang, which recorded the highest values across most indicators including GRDP per capita, economic growth rate, and HDI, yet also exhibited the highest open unemployment rate. Cluster 3 includes 6 cities with relatively high HDI and the lowest poverty rate among the three clusters. Cluster validation using the Davies-Bouldin Index (DBI) produced a value of 0.8341, indicating that the clustering results are optimal. The findings are expected to provide a reference for local governments and the Regional Development Planning Agency (Bappeda) of West Sumatra Province in formulating more targeted regional development policies based on the characteristics of each cluster.