<![CDATA[Technological developments help people live easier. One of the technological developments is being able to trade digitally or it can be called e-commerce. To increase revenue, e-commerce companies collect consumer sales history data that can be analyzed and obtain information about consumer habits. One of the analyzes that can be used is shopping basket analysis which aims to find a pattern in transaction data. In data processing and analysis is done using the R program computation and GUI R is made with a recommendation system simulation. The results of the shopping cart analysis produce as many as 22 rules using a minimum support of 0.06 and a confidence of 0.5. The greater the support value, the more often the product or rule is purchased by consumers from all data transactions and vice versa. Meanwhile, the greater the trust value, the more often the products purchased under the regulation are purchased together. Thus, the information can be used to help carry out promotions to increase sales by the company.]]>
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