Robust nuclear power plant site selection using SWARA, MABAC, and SMART: A GIS-Based study on the Muria Peninsula

Selecting a suitable site for nuclear power plant (NPP) development requires balancing safety, environmental, and socio-economic criteria to meet international standards. This study presents a robust GIS–MCDM framework integrating the Step-wise Weight Assessment Ratio Analysis (SWARA), Multi-Attributive Border Approximation Area Comparison (MABAC), and Simple Multi-Attribute Rating Technique (SMART) methods to identify suitable NPP sites on the Muria Peninsula, Indonesia. Nine spatial criteria—capable fault, seismicity, cooling water, flood level, hazardous area, population, slope, road access, and electrical grid proximity—were assessed based on IAEA safety guidelines and national geospatial datasets. The results of SWARA–MABAC and SWARA–SMART produced identical rankings: A3 (Bandengan) as the most suitable site, followed by A5 (Kedungmalang), A2 (Sinanggul), A4 (Tegalsambi), and A1 (Karanggondang). Benchmarking with AHP–TOPSIS confirmed perfect rank correlation (ρ = 1.000), and a sensitivity analysis with ±2.5% and ±5% weight variation demonstrated complete ranking stability. These results verify the reliability and consistency of the proposed model under expert judgment uncertainty. Beyond methodological validation, the findings support decision-makers in balancing safety, environmental protection, and infrastructure needs. The study concludes that the SWARA–SMART–MABAC–GIS framework offers a transparent and reproducible approach for guiding safe, data-driven, and sustainable nuclear power site selection in Indonesia.