<![CDATA[This study aims to analyze demand forecasting for Piping Hydraulic products at PT. X using three methods: Double Exponential Smoothing, Moving Average, and Linear Regression. The primary focus of this research is to identify significant patterns from historical demand data to generate more accurate demand predictions. By doing so, the study is expected to assist the company in improving inventory planning accuracy and supporting operational efficiency. Through a quantitative approach, this study compares the three forecasting methods to determine which is most effective in reducing prediction errors. Historical demand data were analyzed to uncover relevant trends and fluctuations, serving as the basis for selecting the appropriate forecasting method. The results indicate that all three methods used were effective in minimizing forecasting errors. Furthermore, the study provides strategic recommendations to help the company develop better production planning and design more efficient inventory policies. These findings are expected to contribute positively to the management of product demand in the future. Keywords: Demand Forecasting, Double Exponential Smoothing, Linear Regression, Moving Average, Operational Efficiency]]>
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