<![CDATA[Baubau seaside restaurants have not utilized transaction data welleven though transaction data can be found behavior or consumer purchasing patterns. This study aims to analyze consumer purchasing patterns based on transaction data to identify consumer purchasing behavior, find items that are often purchased simultaneously in one transaction, and find out the value of support, confidence, and lift ratio of each association rule generated through the analysis process. Of the 701 records contained in the transaction data, the apriori algorithm method is used in analyzing consumer purchasing patterns with support parameters, association rules with confidence parameters and measuring association rules with lift ratio. Based on the results of apriori analysis, three association rules are obtained, namely: purchase of sunu ori tends to followed by mineral water (support 0.102857; confidence 0.808989; lift 2.6339), purchase of iced tea and crispy squid followed by bobara hm (support 0.087143; confidence 0.910448; lift 3.1550), and purchase of crispy squid and bobara hm followed by iced tea (support 0.087143; confidence 0.835616; lift 5.222603).]]>
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