<![CDATA[Sales pattern is one of the methods that can be used to determine sales strategy such as the products placement and promo, by seeing on how often an item purchased simultaneously in a retail store. Data mining is used for analyzing the big data to find inter-data connection and to generate useful informations for the users. So, this study used sales transaction data to determine sales pattern by using association rule and algorithm Modified-Apriori. Association rule is a method used for finding unique connection hid in big data by using the calculation of the value of support and confidence. Algorithm modified Apriori is the development of the Apriori algorithm which searches frequent itemset and joining and pruning process, then as a result, it produces faster time efficiency by using HashMap technique instead of Apriori algorithm. The results obtained from this study are the highest value of the minimum support is 9% and the highest value of minimum confidence is 80%. The length of the itemset are 2-itemset and 3-itemset. Test which used lift ratio generates rule which has value of more than 1.]]>
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