Analyzing data can help businesses find out consumer product purchasing patterns, including the coffee shop business. Transaction data can also be knowledge that can be used to determine business decisions. The study applied the association rule using the ECLAT algorithm to determine purchasing pattern of products at the Coffee Shop. The ECLAT algorithm performs a frequent itemset search using the association rule technique. Transaction data for the last 4 months is used for processing. A total of 1515 transactions were processed with a minimum support requirement of 2%. Six 2itemset combinations resulted in support above 2%. To measure the level of strength of the rules that have been formed, the lift ratio test is applied. Of the 6 combinations formed, 4 rules produce a lift ratio > 1. The rule with the highest support and passing the lift ratio test is found in the combination of mineral water and morning milk coffee cup with a support value of 6.36% and a lift ratio of 1.06. The combination of items formed can be recommended to the Coffee Shop owner to form a package menu and assist in determining future business decisions.