<![CDATA[This study aims to examine the application of the Apriori algorithm in data mining for inventory stock optimization using a systematic literature review approach. Effective inventory management is essential for improving operational efficiency and service quality within organizations. The research method involves collecting and analyzing relevant academic articles from scientific databases, which are selected based on predefined inclusion and exclusion criteria. The results indicate that the Apriori algorithm is effective in identifying association patterns among products using transaction data. The generated information supports inventory planning, reduces the risk of overstock and stockouts, and improves overall inventory efficiency. However, several studies highlight the computational complexity of the Apriori algorithm when applied to large datasets. Therefore, future research is recommended to develop hybrid approaches and integrate big data technologies. Overall, this literature review provides a comprehensive overview of research trends and the potential application of the Apriori algorithm in data mining-based inventory management.]]>
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