Implementation of association rules on Mini data is a method used to explore data and analyze transaction data at Lotte Mart. Purchase transactions made by consumers are analyzed using the a priori algorithm. In this study it is known that the data processed is data taken from a certain time span, but it is hoped that it can represent the entire population at Lotte Mart. The results of this study found that there are several transactions that can be used as a basis for promoting products sold at Lotte Mart, this information is taken based on the results of data processing using a support value of 30%. All the antecedents found in the priori algorithm that form association rules are like if a consumer buys plain bread and free-range chicken eggs at the same time then there is a 95% chance that the customer will buy a car and the frequency of this transaction is 55%. The association rule which is the most likely rule to occur is when a customer buys plain bread and Belfoods Fav in the same transaction, the customer will buy crab sticks. The author hopes that Lotte Mart management can use the recommendations of this research to increase sales and reduce goods being discarded or returned to suppliers
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