<![CDATA[Uncontrolled palm oil inventory can increase operational costs and disrupt production flow. This study aims to validate the effectiveness of the Monte Carlo simulation method in predicting the total palm oil inventory costs at PT. Perkebunan Nusantara IV. Unlike conventional approaches that ignore uncertainty, this study uses Monte Carlo simulation to model cost variability based on historical data from January to December 2024. The simulation process is performed by generating random numbers using the Linear Congruential Generator (LCG) method and determining the probability distribution from historical data. The simulation is run once using the probability distribution obtained from 12 months of historical data. The simulation results show a predicted total inventory cost of Rp 918.117.054.635.00, lower than the actual cost of Rp 919.958.281.123.00, resulting in a potential savings of Rp 1.841.226.488.00. To measure the reliability of the Monte Carlo simulation results, a MAPE calculation was performed by comparing the simulation results with actual data. The calculation results show that the MAPE value is 0.2%. These findings prove that Monte Carlo simulation not only improves forecasting accuracy but also empirically supports more optimal decision-making in inventory management and efficient stock level determination.]]>
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