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Data Mining is the process of extracting information or something interesting from the data in the database so as to produce valuable information using techniques such as clustering, estimation, description, and others. Based on observations at AB Mart, there were 44 product items whose data was not revealed. This problem will be solved using data mining analysis. The purpose of this research is to apply market basket analysis to the sale of goods at AB Mart with the a priori algorithm. This research uses a clear structure of the framework, namely problem identification, literature study, data collection, calculation & analysis of association rules with a priori algorithm, forming association rules and making reports. The results of the sales transaction of AB Mart in August resulted in or generated relationships between shopping product items where the% purchase of Pepsodent was 115%, Frisian Flag 96%, Sugar 96%, Indomilk 93%, and Nasi Jempol 91%. The conclusion of this research is using Weka software with a priori algorithm which produces an association relationship between pepsodent goods and the number of transactions purchased

Penerapan Data Mining Menggunakan Task Market Basket Analysis Pada Transaksi Penjualan Barang di Ab Mart dengan Algoritma Apriori