<![CDATA[The inventory system was previously operated manually, recording incoming and outgoing goods in a report book. This method posed risks of recording errors, book damage, and the lack of backup data, making efficient inventory monitoring difficult. To address these issues, a web-based inventory system was developed using PHP and MySQL. Data was collected through observation, interviews, and literature review, while the system development method used a waterfall model with stages of analysis, design, coding, testing, and implementation. This system was integrated with artificial intelligence through the K-Means Clustering algorithm for inventory grouping. As a result, the inventory information system can help admins and warehouse staff improve inventory management accuracy, accelerate decision-making, and support more organized and data-driven inventory management.]]>
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