<![CDATA[The business of refill drinking water depot is a business initiative that focuses on selling refilled drinking water. These depots face fluctuating demand over time, which create challenges in planning inventory and production effectively and effectively. This research aimed to apply the Trend Moment method to predict daily sales of Refill Drinking Water Depot, which allows the recognition of trends and fluctuation patterns based on existing historical sales data. Through analysis of previous sales data, the depot can describe demand development patterns and fluctuations variations. This data is combined into a prediction model to produce more precise future sales forecasts. This study applies the Waterfall Model method in the system creation process. Analysis, design, application, testing, delivery and maintenance are applied in developing a web system for daily sales predictions. The application of the trend moment method produces entirely satisfactory sales predictions. Even though the Mean Absolute Percentage Error (MAPE) figure exceeds the ideal limit of less than 50%, this model still provides essential views and insights for understanding sales patterns and trends. The low Mean Squared Error (MSE) value accurately predicts sales. Hopefully, this study can effectively forecast daily sales at the Refill Drinking Water Depot. This web-based prediction system can support business owners in analyzing expected sales patterns and increasing efficiency in their operations]]>
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