Pengendalian Persediaan Spart Part

Abstract

The development of the automotive industry in Indonesia, marked by the increasing number of motor vehicles, has led to a growing demand for maintenance services and spare parts availability. Pinto Tyre Padang, as an automotive service business, faces inventory control problems characterized by overstock conditions of 58%, stockout conditions of 14%, and normal inventory conditions of 29%. These conditions indicate that the existing inventory control system has not been operating optimally, resulting in increased inventory costs and a decline in customer service levels.

This study aims to determine an inventory control policy that can minimize total inventory costs while reducing overstock and stockout conditions. The data used in this study consist of historical spare parts demand data from 2025. The methods applied include demand forecasting using Linear Regression, Quadratic Regression, and Exponential Trend methods, with the best forecasting method selected based on the lowest forecasting error. Furthermore, Economic Order Quantity (EOQ), Safety Stock, and Reorder Point (ROP) calculations were performed to determine the most economical order quantity and the optimal reorder timing.

The results show that the Exponential Trend method is the most appropriate forecasting method for estimating inventory requirements at Pinto Tyre Padang. The implementation of EOQ, Safety Stock, and ROP resulted in a more structured inventory policy, thereby reducing the risk of overstock and stockout conditions. In addition, the actual inventory cost was IDR 9.538.047.274, while the proposed inventory cost was IDR 5.129.586.785. Consequently, inventory cost savings of IDR 4.408.460.489, or 46,22%, were achieved. These findings indicate that the proposed method is more efficient than the inventory policy currently implemented by the company.