<![CDATA[PT XYZ is a company operating in the food industry. The company produces various kinds of food, such as biscuits, wafers, vermicelli and noodles. Noodle products are the most popular products, and there are often significant changes in each period. This causes fluctuations and results in uncontrolled inventory. PT XYZ can avoid this problem if it has a way to estimate noodle demand. Forecasting is a planning method for estimating products in the future. The moving average and linear regression methods are the methods used in this research. Based on the results of the calculations carried out, the method chosen is the linear regression method because the smallest Mean Squared Error (MSE) value is 620370900 and the tracking signal results from the linear regression method are close to zero. The results of forecasting the need for noodle products for the next period were 169,524 pcs. It is hoped that the results of this forecasting can help PT XYZ in carrying out production planning. ]]>
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