<![CDATA[Coffee is a key agricultural commodity that plays a strategic role in Indonesia’s economy, yet maintaining the safety and quality of post-harvest coffee beans remains a major challenge due to environmental fluctuations during storage. This study aims to apply a multi-parameter fuzzy logic system as a decision support tool for monitoring the temperature, humidity, and CO₂/VOC gas concentration in the agro-industrial coffee storage chain. A qualitative descriptive approach was employed using literature analysis and fuzzy logic simulation with the Mamdani inference method. The simulation results demonstrated that the fuzzy system can effectively classify storage risk levels into safe, moderate, and high-risk categories based on environmental variations. At optimal conditions of 20–25°C temperature and 60–70% relative humidity, the system maintained coffee bean quality in accordance with SNI 01-2907-2008 standards. Conversely, conditions exceeding 30°C and 75% humidity resulted in a high-risk index due to increased moisture, microbial growth, and oxidation. The fuzzy-based monitoring system offers a more adaptive and precise assessment compared to conventional threshold methods, enabling early detection of quality degradation. This research provides a practical reference for developing intelligent control systems to ensure sustainable post-harvest coffee quality management.]]>
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