Improving Inventory Control in the Electrical Sector Using Forecasting Models: A Comparative Study of ARIMA, Exponential Smoothing, Croston, and SBA
Keywords:
forecast, ARIMA, Exponential Smoothing, Croston, Syntetos Boyland ApproximationAbstract
PT. ABC Tarahan Sector is a State-Owned Enterprise that is engaged in services to distribute electricity to the general public. PT. ABC Tarahan Sector distributes about 80% of total electricity consumption in Lampung and 20% is distributed through ABC Palembang. Material planning is one of the most important factors to meet the production targets produced every year. The purpose of this study is to determine the method with the smallest error value based on the time series data available in the company. The data used in this study is the company's material demand data in 2018-2023. The level of accuracy in the forecasting value is determined by looking at the smallest absolute error value in each method. The forecasting results will then be measured based on the value of the service level, inventory level, and inventory cost budget. The existing condition of the company produces an error value of 7.32118, the amount of material is 17,195, the service level is 95.06%, and the warehouse cost is Rp. 36,012,143,757.00. The researcher forecasts using the Arima, Exponential Smoothing, Croston, and Syntetos Boylan Approximation methods. The results of the data analysis resulted in a decrease in the error value of 31.3%, a decrease in the amount of material by 22.38%, an increase in service levels to 95.33%, and a warehouse cost savings of Rp. 182,068,361.00.
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Copyright (c) 2025 Elvi Armadani, Daniel Jeffry, Muhammad As’adi, Yulizar Widiatama (Author)
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