<![CDATA[Consistency in coffee bean quality is essential for maintaining flavor stability and production efficiency in coffee-based beverages. However, quality evaluation in small-scale coffee industries is often subjective and lacks a structured decision support system. This study aims to develop a decision support model for evaluating coffee bean quality using a Multi-Criteria Decision Making (MCDM) approach by integrating the CRITIC (Criteria Importance Through Intercriteria Correlation) and CoCoSo (Combined Compromise Solution) methods. The CRITIC method is employed to determine objective criterion weights based on data variability and inter-criteria correlations, while the CoCoSo method is used to rank alternatives. A total of 15 coffee bean alternatives were evaluated using seven criteria: price, availability, aroma, taste, color, texture, and caffeine content. The weighting results indicate that color (0.215) and price (0.191) are the most influential criteria in the evaluation process. The ranking results show that alternative A9 achieved the highest preference score (K = 4.1634), followed by A7 (K = 3.5747) and A6 (K = 3.4920). These results demonstrate that coffee beans with strong performance across sensory and physical attributes tend to achieve higher rankings. The proposed CRITIC–CoCoSo model provides a systematic, objective, and practical decision support tool that can assist small to medium-scale coffee industries in selecting high-quality raw materials, improving product consistency, and enhancing production efficiency.]]>
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