<![CDATA[Coffee beans are one of the most important commodities in the food and beverage industry, where the quality of the beans significantly determines the final product produced. Assessing high-quality coffee beans is a crucial factor in maintaining consumer satisfaction and preserving flavor consistency. This assessment process requires an accurate and objective method, as it involves various complex factors such as size, color, aroma, taste, and moisture level. A Decision Support System (DSS) serves as an effective solution to assist in complex, multi-criteria decision-making processes. The purpose of this study is to develop and implement a DSS based on the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) to objectively assess and determine the best quality Robusta and Arabica coffee beans. The PROMETHEE method was chosen because it is capable of handling multiple evaluation criteria simultaneously and generating alternative rankings based on measurable preference levels. This study includes data collection, analysis of factors affecting coffee bean quality, and the design and implementation of the PROMETHEE method within the developed DSS. The results of the study indicate that the application of the PROMETHEE method in the DSS can provide accurate, consistent, and reliable recommendations in determining coffee bean quality. Therefore, this system can serve as an effective tool for decision-makers in evaluating coffee bean quality in a more systematic and objective manner.]]>
