<![CDATA[Prioritizing beneficiaries of the Program Keluarga Harapan (PKH) at the urban-village level is often conducted manually, making the process prone to subjectivity, inconsistency, and limited traceability. This study aims to develop a transparent and auditable Decision Support System (DSS) to prioritize PKH candidates objectively under multi-criteria conditions and assessment uncertainty. The proposed DSS combines AHP to verify judgment consistency, Fuzzy-AHP using Triangular Fuzzy Numbers to model linguistic uncertainty and derive criterion weights, and MOORA to compute preference values and generate candidate rankings. The approach is evaluated through a case study in Pasir Putih Urban Village involving 50 prospective beneficiaries and 18 regulation-aligned evaluation criteria. The consistency test yields a Consistency Ratio (CR) of 0.09, indicating acceptable consistency. The ranking results show that alternative A12 achieves the highest preference value, followed by A50. To assess recommendation reliability, a sensitivity analysis is performed by varying criterion weights by ±25% with proportional normalization. While several rank shifts occur, seven alternatives (A14, A32, A10, A26, A7, A12, and A50) remain relatively stable, indicating more robust outcomes. From an informatics perspective, this work contributes a reproducible MCDM-based DSS framework that integrates uncertainty modeling and robustness evaluation to improve accountability and decision transparency in public-sector social assistance prioritization.]]>
