<![CDATA[Interactions between drugs and food are a critical public health issue, as they can cause unwanted side effects or reduce the effectiveness of treatments. Unfortunately, awareness of these potential interactions among the Indonesian population remains low, while existing platforms generally focus only on drug–drug interactions. This study aims to develop an intelligent platform for analyzing drug–food interactions by combining fuzzy logic and certainty factor (CF) methods. Fuzzy logic is employed to handle uncertainty in interaction data, while the certainty factor enhances confidence levels based on clinical literature and expert knowledge. Drug–food interaction data were collected from validated sources and modeled using fuzzy membership functions, IF–THEN rule-based reasoning, defuzzification processes, and integration with CF. The web-based system was evaluated through accuracy testing and usability assessment using the System Usability Scale (SUS). Accuracy tests conducted on 50 interaction scenarios demonstrated a 100% match with clinical references, while the SUS evaluation involving 100 respondents yielded an average score of 77.44, falling into the “Acceptable” category and approaching “Good Usability.” These results indicate that the platform has the potential to serve both as an educational tool and as a practical aid for the public to enhance self-management of health, while also supporting government health programs.]]>
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