Inventory has a very important role in increasing sales and service to consumers. The purpose of this study was to determine the information and sales patterns in the form of association rules at a certain period that can provide advice to the pharmacy in managing drug inventory. The algorithm used in this study is a priori to determine the results of sales patterns in the form of association rules. Association rules are obtained by implementing an apriori data mining algorithm to a website-based system using laravel and the resulting calculation results are in the form of Drug Association rules purchased simultaneously. With a minimum support value of 2, there are 214 items in 1 – the itemset that passes the minimum support and 9 association rules formed from all transactions of 519 data with a confidence value of more than 30%. From the resulting Association rules, there are Association rules with the highest confidence value of 66.67% in the form of ketotifen and cupanol pairs purchased simultaneously.
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