This research is titled “Application of Sales Data Mining at Osher Store Using FP-Growth Algorithm”. Osher Store, which provides photocopying services and sells stationery, faces challenges in identifying customer purchasing patterns due to transaction data management that is still done manually. This research aims to apply the FP-Growth algorithm in analyzing sales transaction patterns over the past three months. The FP-Growth algorithm was chosen because of its efficiency in finding frequent itemset patterns without explicitly building candidates. The research process includes transaction data collection, data preprocessing, FP-Growth application, and result analysis. The results show certain purchasing patterns that can be used to strategize marketing, stock management, and increase customer satisfaction. The implementation of this algorithm is expected to help Osher Store improve operational efficiency and competitiveness through data-driven decision-making.
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