<![CDATA[Revenue is a key indicator in determining a company's financial success, both for identifying potential profits and losses. This predictive model is designed to assist management in developing strategies to increase product sales. Accurate forecasting can provide early warnings regarding the actions store management needs to take. This study employs the Double Exponential Smoothing Brown method with a smoothing parameter alpha (?) of 0.5. The analysis results indicate that the Mean Absolute Percentage Error (MAPE) values range from 0.26% to 4.29%, demonstrating a high level of accuracy. Based on these MAPE results, the predictive model is then implemented into a web-based system. This system allows management to access information anytime and anywhere. Therefore, this prediction system is expected to assist the store in making strategic decisions, particularly in managing and increasing future revenues]]>
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