<![CDATA[The research aims to design and build a system of inventory prediction using the Weighted Moving Average (WMA) method at ATK Partner Store. These stores have problems in managing inventory, often in excess or shortage of inventory. To address the problem, the study used the WMA method, which gives greater weight to the latest data, to improve the accuracy of predictions. The data used in this study is sales data from January to May 2024. Using this data, predictions are made for June 2024 and beyond. The research process involves several stages, including data collection, system needs analysis, system design, implementation, and system testing. The system is designed using PHP as a server-side programming language to ensure optimal performance. Research results showed that the WMA method can produce inventory predictions with a high degree of accuracy, demonstrated by a Mean Absolute Percentage Error (MAPE) below 10% for each type of goods. For example, inventory forecasts for June 2024 showed highly accurate results with a MAPE value of 0.031679478%. The system developed enabled Partner Stores to plan inventory better, reducing the risk of surpluses or stock shortages. The benefits of this research are not only perceived by the Partner Shop, but also provide new insights to students and contribute to the university in the development of science in the field of information systems and forecasting of supply. This research can also serve as a reference for further research in the future. Keywords: Inventory, Forecast, Weighted Moving Average (WMA)]]>
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