<![CDATA[ In social aid distribution, the selection process of recipients is a critical aspect that determines the effectiveness and fairness of the program. However, subjective and unstructured decision-making often leads to inaccurate targeting. This study aims to develop and compare a Decision Support System (DSS) to assist the selection of social aid recipients using three Multi-Criteria Decision Making (MCDM) methods: Simple Additive Weighting (SAW), Weighted Product (WP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The evaluation is based on academic (exam scores), economic (parental income), and social criteria (number of dependents and student activity). The data were processed through normalization, weighting, and ranking stages. The results showed that each method produced different rankings, with the SAW method delivering the most consistent and easy-to-interpret outcomes. These findings are in line with previous studies by Rosyani and Maulana (2023) and Rosyani and Kursniadi (2023), who emphasized the importance of DSS in reducing subjectivity within social selection contexts.]]>
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