Selecting high-quality coffee beans is a critical factor in maintaining flavor consistency in the coffee beverage industry. At Kopi Luar Dalam, the raw material selection process is still conducted subjectively, which can lead to inconsistent decisions. This study aims to design and implement a Decision Support System using the Simple Additive Weighting (SAW) method to determine the best coffee beans based on four criteria: cost, aroma, bean color, and physical form. The study employs a quantitative approach involving decision matrix normalization and preference value calculation. The results show that the African Blue Mountain Arabica (A8) alternative obtained the highest preference value of 0.80 and is therefore recommended as the best raw material. Methodologically, this study demonstrates that the application of SAW is capable of producing an objective, structured, and transparent selection process in the context of raw material selection for the SME-scale coffee industry.
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