Implementation of the Simple Additive Weighting (SAW) Method in a Decision Support System for Determining Recipients of Disaster Impact Social Assistance for Students at Universitas Budi Darma - Eltrina Naibaho (Bahasa Indonesia, 2026)
The distribution of disaster impact social assistance requires an objective and transparent decision-making mechanism to ensure that aid is allocated to the most eligible beneficiaries. This study aims to implement the Simple Additive Weighting (SAW) method in a web-based Decision Support System (DSS) to determine recipients of disaster impact social assistance among students at Universitas Budi Darma. The system evaluates five criteria: parental income (cost), number of dependents (benefit), disaster impact level (benefit), Grade Point Average (GPA) (benefit), and housing condition (benefit). Using a weighted normalization process with weight values of 0.30, 0.20, 0.20, 0.15, and 0.15 respectively, the system calculates preference scores for each student. Based on sample testing with five applicants, the highest preference value was obtained by Student A4 with a score of 0.92, followed by A2 (0.88), A5 (0.74), A1 (0.69), and A3 (0.63). The results indicate that students with lower parental income and higher disaster impact levels received higher rankings. The developed system successfully reduces subjectivity, increases transparency, and improves efficiency in the selection process. Validation through comparison with manual calculations confirms the accuracy and reliability of the implemented SAW algorithm. Therefore, the proposed DSS provides an effective and data-driven solution for fair social assistance allocation within the university environment