<![CDATA[Population growth has an impact on economic resources. UD. Sumber Rejeki is a company that supplies goods to various companies. Sales transaction data from UD. Sumber Rejeki is important information in increasing sales. This study aims to find purchasing patterns in order to predict stock requirements, thereby increasing sales. The data used in this study are sales transaction data from January to July at UD. Sumber Rejeki Bekasi. The FP-Growth algorithm is one of the algorithms in data mining techniques used to find high-frequency purchasing patterns in transaction datasets or datasets containing items that frequently appear together. Based on these data, with the requirement of at least two types of goods in one transaction, this study uses a data mining technique based on the FP-Growth algorithm with a confidence value of 75% and a minimum support of 20%. The tool used is Rapidminer 9.10. The results of the study indicate that the FP-Growth algorithm is effective in finding relationships between products that are frequently purchased together and is able to provide information on predicting future stock requirements. These findings can be used as a reference for warehouse managers or management in optimally managing inventory, reducing storage costs, and increasing the availability of goods according to customer demand]]>
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