Policy determination of inventory control of batik fabric using Q and P lost sale probabilistic model through montecarlo simulation approach as the system testing analysis

The material inventory control system in the company shows that the addition of material inventory is carried out repeatedly and the demand (needs) of the material becomes rigid because it is highly dependent on the needs of the production process. The implementation of Make to Order system within the production process creates a demand that is probabilistic in nature as such that it requires proper raw material inventory planning. At present, inventory control policies in the company are not accurate in anticipating probabilistic demand, leading to a high number of lost sale products. The problem with the company is that the company is not aware of the level and timing of orders that are appropriate in controlling raw material inventory. Based on this condition, this research aims to help the company in determining inventory control policies using Q and P lost sale through Monte Carlo simulation approach system testing analysis. After obtaining the results through Q and P models, a simulation will be performed to see the effectiveness of the policy. Based on the simulation results of inventory policy, Model Q has the advantage of saving total inventory costs by Rp13,778,373.58 and decreasing the number of lost sale products by 352 units or with a percentage increase in succession of 76% and 100% compared to the company’s current system, while Model P can also provide a total inventory cost savings of Rp10,457,037.44 and a reduction in the number of lost sale products by 352 units or with a percentage increase in succession of 59% and 84%. Based on this, we can draw a conclusion that the best alternative inventory policy model is obtained in the Q model.