The ROCK Ensemble Cluster Method for People's Welfare Analysis A Mixed Data Approach : Metode Ensemble Cluster untuk Analisis Kesejahteraan Rakyat Pendekatan Data Campuran

Abstract

This study clusters districts/cities in West Sumatra based on public welfare indicators using the Ensemble Cluster Method with the ROCK algorithm. This approach handles mixed data, where numeric data is clustered with Hierarchical Agglomerative Clustering, while categorical data uses ROCK. The clustering results are combined through Cluster Ensemble to improve accuracy. Secondary data from BPS 2023 includes eight indicators of people's welfare. Clustering was validated using Compactness (CP). Results showed five optimal clusters, with a CP value of 0.44. Cluster 1 has the greatest welfare challenges, while Cluster 5 shows the highest welfare. These findings can be used as a basis for formulating more targeted regional development policies.