Reduction of Raw Material Inventory Costs with an Operational Management Approach for Beverage Products at Loca Coffee

Abdul Chalid; Wiwik  Handayani

doi:10.55927/ijbae.v4i1.13128

Authors

Abdul Chalid University of Pembangunan Nasional Veteran East Java
Wiwik Handayani University of Pembangunan Nasional Veteran East Java

DOI:

https://doi.org/10.55927/ijbae.v4i1.13128

Keywords:

Holt-Winters, Machine Learning, MRP, Python, SARIMA

Abstract

Facing significant demand fluctuations has resulted in Loca Coffee experiencing a surge in inventory costs, a lack of control over raw material inventory, and suboptimal service quality. To assist the company, this study aims to reduce inventory costs, minimize order frequency, and improve service quality. To achieve these objectives, an operational management approach is applied in this research. One of the inventory control techniques, Material Requirements Planning (MRP), will be utilized. In implementing an effective MRP system, the Holt-Winter and SARIMA methods will be applied in the forecasting process. Machine learning techniques will be employed for the forecasting model using time series sales data of Loca Coffee products, with Python programming language. As long as the approach is carried out in the appropriate manner, the findings of the research indicate that the implementation of an inventory control system that is based on MRP was successful in achieving a reduction in costs of Rp 10,335,500, a significant decrease in the frequency of orders, and an improvement in the quality of service

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