<![CDATA[This research aims to enhance the efficiency of stock and sales management at Omilen Coffee by applying the Trend Moment Method. Omilen Coffee frequently faces issues with mismatches between coffee stock and customer demand, leading to customer dissatisfaction and increased storage costs. The Trend Moment Method is used to analyze historical sales data and identify trends and seasonal patterns, resulting in more accurate predictions of future stock needs. The research involves the collection of primary and secondary data, data analysis using the Trend Moment Method, prediction validation, and the development of a web-based system to facilitate the prediction and stock management process. The results show that this method is effective in predicting coffee sales and stock, with high prediction accuracy and a MAPE value of 6.28%. The implementation of the web-based system simplifies real-time stock management, enabling Omilen Coffee to plan stock more efficiently, reduce the risk of stock shortages or surpluses, and improve customer satisfaction.]]>
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