<![CDATA[The puzzle industry faces challenges in meeting dynamic market demands, necessitating appropriate strategies to maintain a balance between supply and demand. This research aims to design a forecasting system for stock requirements of puzzle products at PT. XYZ using the Double Moving Average (DMA) method. This method helps generate more accurate predictions, with an error rate of 7.25% based on the MAPE value from historical sales data. The analyzed data covers the period from September 2022 to October 2024, with the forecasted sales for the final month reaching 308.44 units. The analysis results are implemented in a web-based system using the Laravel framework. The system is designed to display forecasting results quickly and measurably in an interactive dashboard. With this system, the company can minimize the risks of overstocking or understocking, potentially reducing operational costs. The application of the DMA method assists PT. XYZ in understanding and responding to sales trends by producing low-error predictions, thereby supporting the company in enhancing operational efficiency and optimizing stock management to meet customer demands effectively.]]>
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