<![CDATA[One of the reasons for not optimal sales in various business fields is due to the lack of data utilization. Therefore an application is needed that can analyze and process large amounts of data sets to provide an overview of the interrelationships between goods by analyzing sales transaction data, so that users can use the information from the data processing results for marketing strategies to increase sales. By using data mining methods, namely market basket analysis and a priori algorithm, produce association rules that show patterns of consumer buyers and how strong an item affects other items. The use of this algorithm will provide knowledge to users in the form or pattern of sales that occur. From the results of analysis and testing, system trials have been carried out using sales transaction data totaling 87 transactions during the period January 2022-March 2022 by changing the minimum support and minimum confidence parameters, it can be concluded that one of the item combinations that can be made for the promotion development process into a package is if consumers buy Nordic then 36.84% (consumer certainty in buying items) will buy Anubis. This information can be useful for increasing sales by knowing which product categories are frequently purchased by consumers, so that the store can make business decisions such as marketing strategies by making recommendations on package efforts to increase sales.]]>
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