Abstract
This research uses the FP-Growth algorithm to identify sales patterns at the Cipta Lestari convenience store to support inventory management efficiency and marketing strategies. The data used in this research consists of daily sales transaction data that includes product types and the quantities sold. This analysis employs a support parameter of 0.95 and a confidence level of 0.8, with a maximum limit of 100,000 items. The results indicate that products such as Kchoco, sambal sauce, and tea 3350ml are often purchased together with Torabika coffee, soy sauce, and instant fried noodles. This combination pattern enables the store to create more effective product promotions and optimize inventory. The goal of this research is to develop business strategies that are more responsive to customer needs, enhance satisfaction with the right product offerings, and strengthen competitive marketing. This research is expected to contribute to the development of traditional marketing strategies and serve as a reference for analyzing consumer purchasing patterns in future studies.
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