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

Abstract

This study is motivated by the differences in labor conditions among regencies/cities in West Sumatra Province, as indicated by the Open Unemployment Rate (OUR) and the Labor Force Participation Rate (LFPR). In addition, the impact of the COVID-19 pandemic and the economic recovery process during the 2019–2025 period are assumed to have caused changes in labor characteristics across regions. However, the patterns of similarities and differences in labor conditions among regions have not been clearly identified, making it necessary to conduct a regional clustering analysis based on labor characteristics. This study aims to analyze the clustering of regencies/cities in West Sumatra Province based on the OUR and LFPR indicators during 2019–2025. The data used were obtained from the Central Statistics Agency, covering 19 regencies/cities. The analytical method applied was K-Means clustering using Euclidean distance, while cluster validation was conducted using the Silhouette Coefficient. This study used two clusters to facilitate the interpretation of results. The findings show that the regencies/cities in West Sumatra Province were divided into two clusters with different characteristics. Cluster 1 represents regions with better labor conditions, characterized by lower OUR and higher LFPR, while Cluster 2 represents regions with relatively poorer labor conditions, characterized by higher OUR and lower LFPR. Cluster membership changed from year to year, indicating dynamic labor conditions across regions. The results of this study are expected to serve as a basis for formulating more targeted labor policies according to the characteristics of each region.