Comparison of District/City Clusters in West Sumatra Province 2019–2025 Based on Labor Indicators Using K-Means Method

Abstrak

This study aims to analyze the clustering of districts/cities in West Sumatra Province based on labor market indicators, namely the Open Unemployment Rate (OUR) and the Labor Force Participation Rate (LFPR for the period 2019–2025. The data used were sourced from the Central Statistics Agency and cover 19 districts/cities. The analysis method employed was C-Means clustering, a method of grouping data based on similarity using Euclidean distance. Two clusters were identified to facilitate interpretation and inter-year comparisons. The results of the study indicate that the regencies/cities are divided into two clusters with distinct characteristics: Cluster 1, characterized by relatively favorable labor market conditions (low OUR and high LFPR), and Cluster 2, characterized by the opposite conditions (high OUR and low LFPR). Cluster membership changes from year to year, indicating the dynamic nature of labor market conditions across regions. Validation results using the Silhouette Coefficient yielded a value of 0.54, indicating a reasonably good quality of clustering. It is hoped that these research findings can serve as a basis for formulating more targeted labor policie.