Raw Material Inventory Control Using Probabilistic Methods and P Models as an Effort to Reduce the Risk of Out of Stock at UD XYZ

The calculation of raw material inventory for pentol frozen products at UD XYZ using the probabilistic P Model Back Order indicates that the application of this method effectively helps the company optimize its inventory control. The probabilistic approach provides more accurate considerations in determining order quantities, order intervals, and minimizing the risk of stock shortages. The results show that beef reaches its optimal point with orders placed every 3 days at a quantity of 278.24 kg and a total cost of Rp 9,705,474, with a service level of 75%. Chicken also achieves optimal results with an order interval of every 3 days at 109.05 kg and a total cost of Rp 1,481,784 with an 80% service level. For sago flour, optimal inventory performance is achieved with orders every 6 days totaling 152.58 kg at a cost of Rp 946,617 and a service level of 76%. Meanwhile, tapioca flour reaches its optimal point with orders every 6 days amounting to 76.02 kg, a total cost of Rp 200,186, and an 81% service level. Overall, the application of the probabilistic P Model Back Order has proven to produce an efficient and measurable inventory system that supports the smooth production process of pentol frozen products at UD XYZ.