<![CDATA[A well-prepared abstract allows readers to quickly and accurately identify the basic content of a Local MSMEs make a significant contribution to the regional economy; however, the diversity of products offered often creates difficulties for consumers in making purchasing decisions. Therefore, this study utilizes Python-based data analysis as an approach to generate product recommendations that can support the improvement of MSMEs’ marketing strategy effectiveness. This research employs a data mining method by applying the Apriori algorithm, supported by the pandas and mlxtend libraries, to analyze consumer purchasing patterns. The data processing results indicate an association between rice and cooking oil products, where rice purchases are followed by cooking oil purchases at a rate of 60%, while cooking oil purchases are followed by rice purchases at a rate of 75%. These purchasing association patterns serve as the basis for developing product recommendations, enabling MSMEs to manage inventory more optimally and design more targeted marketing strategies.]]>
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