SPATIAL K-MEANS CLUSTERING FOR IDENTIFYING OPTIMAL SUSTAINABLE AVIATION FUEL PRODUCTION LOCATIONS IN INDONESIA - Khansa Ghumaydha Dzikra; Roni Kastaman; Januardi Januardi (Politeknik Negeri Batam, 2026)
Indonesia holds substantial feedstock potential for Sustainable Aviation Fuel (SAF) production, particularly from Used Cooking Oil (UCO) and Palm Oil Mill Effluent (POME), yet only one SAF production facility is currently in operation. The geographical mismatch between widely dispersed feedstock sources and centralized production infrastructure remains a key bottleneck for national SAF development. This study applies a Spatial K-Means Clustering approach to the coordinates of 15 feedstock-producing provinces and 36 international airports across Indonesia to identify optimal locations for SAF production facilities. Three scenarios were comparatively analyzed using the Within-Cluster Sum of Squares (WCSS) metric, which covers configurations of 2, 3, and 4 production facilities with the existing facility in Cilacap incorporated as a fixed centroid. The results show that the 3-facility scenario is the most optimal configuration, recommending two new facilities in Riau and Central Kalimantan to complement the existing Cilacap facility, achieving a 55% reduction in WCSS compared to the 2-facility scenario. This study also identifies an infrastructure gap in Eastern Indonesia that warrants a dedicated policy approach, given the limited availability of UCO and POME feedstock in that region.