<![CDATA[PT. XYZ is a company engaged in the business of selling agrocomplex products including agricultural products, plantations, fisheries, health, and household products. Transaction data continues to increase, companies have difficulty knowing the patterns of consumer purchases accurately. Huge accumulation of data can be used by companies to determine strategies that can support the company's business processes. In this study, the implementation of association rule mining was carried out to help determine consumer purchasing patterns. The technique of combining mining rules used is a priori algorithm that is applied to web-based applications to analyze nasaofficial.com transaction data. To get accurate results added calculation of lift ratio. In this study determined the minimum value of support is 10% and a minimum confidence value of 60%. The result is that there are 3 items of goods, namely viterna, hormonal, nasa. The final results of this study indicate that the mining association rules using a priori algorithms have been successfully applied in applications. The highest association rule produced in the transaction data for the past year is if consumers buy viterna (natural animal vitamins) and hormonic then buy NASA POC with a support value of 23% and 96% confidence value.]]>
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