Forecasting Analysis of Raw Material Demand in the Battery Breaker Production Process at PT IMLI

Abstract

Accurate demand forecasting is crucial for companies engaged in smelting, such as PT IMLI, to prevent shortages and inventory increases. This research aims to determine the most appropriate forecasting method for raw material demand based on historical data. Three methods were used: moving average with n = 3 and n = 5, and exponential smoothing with α = 0.2. The results showed that the Exponential Smoothing Method with α = 0.2 had the smallest error rate, with a MAPE value of 23%, MAD of 411, and MSE of 293303. This method can be used to optimize demand forecasting for the next period, ensuring that the company has sufficient raw materials for black tin smelting. Highlight : Accurate demand forecasting is crucial for companies engaged in smelting to prevent shortages and inventory increases. Three methods were used to determine the most appropriate forecasting method for raw material demand based on historical data: moving average with n = 3 and n = 5, and exponential smoothing with α = 0.2. The Exponential Smoothing Method with α = 0.2 had the smallest error rate, with a MAPE value of 23%, MAD of 411, and MSE of 293303, and can be used to optimize demand forecasting for the next period. Keywords: demand forecasting, smelting, raw materials, historical data, moving average, exponential smoothing.