USULAN KEBIJAKAN INVENTORI BAHAN BAKU TOWER DENGAN INTERMITTENT DEMAND PADA PT JAYA ENGINEERING TECHNOLOGY

• Main Author: Floaro Qytan P, Muhammad
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/84168
• Institution: Institut Teknologi Bandung

PT Jaya Engineering Technology (JET) is an Indonesian company with core businesses in the manufacturing sector, specifically in fabrication and construction. One of the products offered by PT JET in its fabrication business is towers. In producing towers, PT JET requires raw materials such as SS400 angle iron as the main material. Currently, the quantity of raw material inventory is not optimal. This is because the company relies solely on the regulation of storing 10% of the demand data in the warehouse, without considering order lot sizes, reorder points, which results in inventory costs and impacts the company's finances. Therefore, an updated inventory policy is needed to align with the company's conditions. In this study, the proposed inventory policy method uses the Q backorder model and the P backorder model. To validate the inventory policy model, several steps were carried out, such as the KPSS test for data stationarity, demand classification based on p-values and CV^2, data forecasting using Croston’s method and the SBA method, forecasting evaluation with RMSE, and calculating existing and proposed inventory policies using the Q backorder model and the P backorder model. According to the study results, the SBA method is the forecasting method with the lowest RMSE value. Furthermore, the results of calculating the inventory policy with the Q backorder model show that the total inventory cost in the existing condition is Rp1.693.762.662,00, while the total inventory cost in the proposed condition is Rp1.172.945.486,00, resulting in a 30,7% reduction in inventory costs. Additionally, there are 11 items with the lowest inventory cost using the proposed Q backorder model and 1 item, SS400 angle iron, using the existing Q backorder model.