<![CDATA[PT EPC is a company that produces cardboard boxes and is facing issues with raw material overstock. This has led to inefficiencies in managing the raw materials needed for the production process. This study aims to improve the efficiency of raw material inventory planning for cardboard boxes at PT EPC by implementing forecasting methods. The methods used include Double Exponential Smoothing (DES), Moving Average (MA), and Linear Regression (LR). Raw material stock data over 12 periods were analyzed to determine the best method based on the Mean Squared Error (MSE) value. The results show that the Linear Regression method has the smallest MSE value, which is 961,198,420.99, making it the most accurate method. Additionally, the optimal safety stock was calculated at 72,278 sheets to anticipate demand fluctuations. In conclusion, the Linear Regression method is proven effective for inventory planning, reducing the risk of overstock and understock, and improving operational efficiency at PT EPC. Keywords: Double Exponential Smoothing, Forecasting, Linear Regression, Moving Average, Safety Stock]]>
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