Penerapan Algoritma K-Means untuk Pengelompokan Pola Konsumsi Energi di Tingkat Kabupaten/Kota - Muhammad Pazri Hasibuan; Helmi Fauzi Siregar (Universitas Batanghari Jambi, 2026)
This study aims to analyze and classify energy consumption levels across districts and cities in Indonesia using the K-Means Clustering algorithm. Per capita food energy consumption serves as an indicator of community welfare and food security. The main issue addressed is the significant variation in energy consumption between regions, which requires data-based analysis to understand the patterns. Data from official national sources were processed using the K-Means algorithm to group areas with similar energy consumption characteristics. The results show three main categories: low, medium, and high energy consumption. The web-based system developed in this study helps make the analysis faster, more accurate, and easier to interpret. The findings are expected to support the formulation of more targeted and sustainable energy and food policies.