<![CDATA[The challenge of selecting skincare products that match individual skin conditions often leads to confusion among users, especially due to the vast array of products available on the market. This study aims to assist users in choosing the most suitable local skincare products based on several criteria: skin concerns, skin type, price range, number of items in a set, and sales ratings. The method used is the Simple Additive Weighting (SAW) technique, which calculates the suitability level of each product alternative against the defined criteria to generate a ranked list of the most appropriate products. The system was developed using the Rapid Application Development (RAD) approach, which emphasizes rapid prototyping and iterative implementation. It was built as a web-based application using PHP, MySQL, HTML, CSS, JavaScript, and Bootstrap 5. Skincare product data were collected through web scraping from the Shopee platform, including information such as price, set completeness, and sales ratings. All data were verified for validity using BPOM certification and halal labels. The results of the study indicate that the decision support system can recommend up to three top local skincare products tailored to user preferences, complete with pricing, images, and brief descriptions—without displaying numeric scores. Functional testing confirmed that all features operated correctly, and a User Acceptance Test (UAT) yielded an average satisfaction score of 94%, indicating strong user acceptance. In conclusion, this system serves as a valuable digital tool to accelerate decision-making in skincare selection, reduce the risk of product mismatch, and improve both the efficiency and adoption potential of local skincare products based on user preferences in an online environment.]]>
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