<![CDATA[Decision Support Systems (DSS) play a vital role in facilitating the selection of the best catfish for consumption based on specific criteria. This study aims to develop a web-based DSS using the Fuzzy Logic method, designed to provide accurate and efficient decision-making outcomes. Fuzzy Logic was chosen for its ability to handle uncertain data and generate decisions resembling human logic. The system was developed through several main stages, including data collection, data processing using fuzzy rules, defuzzification, and decision determination. System testing was conducted to ensure the proper functionality of all features, covering input validation, fuzzy process verification, and defuzzification accuracy in determining the quality category of catfish. The system allows users, such as farmers and consumers, to input data such as size, weight, health, and color of catfish to obtain recommendations for the best quality fish. The results indicate that the system delivers outputs aligned with user input data, achieving high accuracy in decision- making processes. Moreover, functionality tests confirm that the system operates according to predefined specifications, ensuring ease of use and adding value in supporting technology-driven decision-making. Therefore, this system can be relied upon to enhance the efficiency of selecting the best catfish for consumption on both commercial and personal scales. This research is expected to serve as a foundation for developing fuzzy-based systems in other fields requiring uncertain data processing.]]>
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