<![CDATA[Post-harvest handling is one of the strategies to support food security in Indonesia. This handling is necessary because harvestedproducts, such as various types of leafy and fruit vegetables, have different shelf lives (Arista, 2021). Additionally, damage to harvested products occurs more quickly if handling during or after harvesting is poor. Therefore, the storage of post-harvest products requires a cooling container to maintain the quality of the harvested goods. To ensure ideal storage conditions for items that need specific conditions, a cold storage control system is a strategic step to enhance operational performance and reduce product losses due to damage during storage. To ensure food quality and safety, the cold storage parameters that need to be controlled are temperature, humidity, and air quality (Mohammed et al., 2022).This study was conducted to explain the process of controlling temperature and relative humidity in a cold storage using a fuzzylogic controller. In the control process, it was found that the chiller system has a steady state time of 4000 s or 66 minutes and 40 seconds with a steady state error of 1.63%. When disturbed, the recovery time obtained is 1,074 s (17.9 minutes) with the steady state error increasing to 2.7%. Meanwhile, the freezer system has a steady state time of 3,774 s or 62 minutes and 54 seconds, no overshoot, and no steady state error. However, when disturbed, the freezer system will have a steady state error of <1% with a recovery time of 1,094 s or 18.2 minutes. For the humidity control system, to reach 90% RH, it takes 1,950 s or 32 minutes and 30 seconds with no steady state error. However, the humidity system graph has an overshoot of 5%. When the humidity system is disturbed, the recovery time (rt) is 200 s or 3.3 minutes. However, after the disturbance, a steady state error of 0.4% is obtained. Keywords: Cold Storage Control, Temperature and humidity control, Fuzzy Logic Controller]]>
