<![CDATA[This research aims to implement Apriori algorithm for data mining in material inventory management at PT. Telkom Akses Makassar. Apriori algorithm identifies frequent itemsets and generates association rules from transaction data to optimize warehouse stock management. The methodology includes data collection through observation, interviews, and historical transaction datasets. Data processing uses Apriori to calculate support, confidence, and lift metrics. The results indicate that frequent item combinations can improve planning accuracy and reduce stockouts. A web-based application, Material Analyzer, was developed for analysis and visualization, featuring dashboard, analysis, history, and visualization modules. This study contributes practically by supporting logistics decision-making and theoretically by expanding data mining applications in inventory systems.]]>
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