<![CDATA[This study aims to design and develop a Decision Support System (DSS) to determine the days with the highest number of customers at Spring Clothing Store using the Simple Additive Weighting (SAW) method. The research is motivated by the difficulties faced by the store owner in predicting peak customer days due to the large number of criteria that must be considered in the decision-making process. The existing manual and subjective approach, which relies heavily on intuition, often leads to inaccurate decisions, resulting in suboptimal stock management, reduced customer satisfaction, and potential financial losses. The SAW method is applied to provide a more structured, objective, and accurate approach by ranking alternative days based on predefined criteria. The research methodology includes data collection through observation, interviews, and literature studies, followed by system design and implementation using web-based programming with PHP and a MySQL database. The results indicate that the SAW-based DSS effectively assists the store owner in identifying high-traffic customer days, enabling better stock preparation and minimizing the risk of losses. This study contributes to the practical application of multi-criteria decision-making methods in small retail business management and may serve as a reference for similar implementations.]]>
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