The energy crisis due to the dominance of fossil fuels has encouraged the development of sustainable alternative energy sources. Biomass energy offers significant potential, especially in Riau Province, which has numerous plantations. This study analyzes the biomass energy potential of palm oil, coconut, sugarcane, pulp paper, and rice in Riau Province using a GIS approach. The methods used include mapping mill locations, clustering using the hybrid K-Means and DBSCAN clustering methods, and determining collection points based on highest production and proximity to the mean center. K-Means produces evenly distributed clusters but is less spatially efficient, so the DBSCAN method was used. DBSCAN, with a radius of 11 km, forms a denser and more efficient twelvecluster system. The collection point is determined based on the factory with the highest production for clusters 2, 4, 5, 6, 7, 8, 9, 10, 11, and 12 and if two or more factories have the same production, additional consideration is given, namely looking at the proximity of the location to the mean center for cluster 1 and cluster 3. The total potential electrical energy from all clusters reaches 4.730.686,55 kWh, with cluster 1, cluster 7, cluster 9, cluster 10, and cluster 12 as the largest energy contributors.