<![CDATA[Indonesia, as an equatorial archipelago located between the Asian and Australian continents, faces high risks of natural disasters, particularly floods and landslides. These disasters cause various adverse impacts, such as infrastructure damage, psychological trauma, and social and economic losses for victims. The Regional Disaster Management Agency (BPBD), as the primary institution for disaster response, must provide effective services for community recovery, thus requiring a fast and accurate system. Therefore, this research aims to develop a Decision Support System (DSS) using the Multi-Attribute Utility Theory (MAUT) method to assist BPBD in determining priority recipients of disaster aid. The advantage of the MAUT method lies in its ability to process multi-criteria decisions, consider stakeholder preferences, and produce quantitative and transparent outputs. The system was built using PHP and designed with Unified Modeling Language (UML). Testing was conducted on 16 alternative datasets, producing a priority ranking based on the highest scores. Accuracy tests showed an 87.5% success rate, while black-box testing achieved 100%. The highest preference score (0.92083) proves MAUT's accuracy in decision-making.]]>
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