<![CDATA[Transportation in the palm oil industry plays a strategic role, particularly in ensuring the smooth distribution of Crude Palm Oil (CPO). PT. X is a company engaged in CPO transportation services, also known as a transporter. The company operates 12 vehicles. PT. X's workflow begins with contract agreements with various clients to transport CPO from loading locations to unloading destinations as stipulated in the contracts. Each vehicle is allocated to a contract that matches its capacity and capabilities. After allocation, the vehicles transport the CPO from the loading site to the designated unloading site. Differences in distance and travel conditions between the loading and unloading locations cause variations in travel duration for each vehicle. Scheduling uncertainties often make it difficult for field employees to estimate the number of trips each vehicle can complete. Consequently, some clients have complained about delays in contract fulfillment by PT. X. This research aims to analyze the efficiency of travel time for CPO transport vehicles using the Fuzzy Mamdani method. The main focus is on variables such as loading and unloading times, average vehicle speed, and travel distance. The collected data were processed through the stages of fuzzification, inference, and defuzzification to generate travel time estimates. The results show that the Fuzzy Mamdani-based system can accurately predict travel times. This method also facilitates operational decision-making in managing CPO transportation, thereby minimizing delays and improving efficiency. The implementation of this system significantly contributes to optimizing vehicle allocation and supporting the smooth execution of transportation contracts]]>
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