<![CDATA[The application of the Apriori Algorithm helps in forming possible candidate item combinations, then testing whether the combination meets the minimum support and confidence parameters which are the threshold values given by the user. Even though until now, service activities and transactions at pharmacies have not experienced any significant problems, of course this situation will one day become an inhibiting factor in improving service as more and more transactions and types of items and transaction items are stored within a certain period of time, making it difficult for the pharmacy. in analyzing the types of items and itemset which consumers are most interested in or not interested in so that they can control the inventory of medical devices. The results of the study: The results of the pattern analysis above show that the greater value of support from a combination of medical devices provides recommendations for the medical devices most often purchased by consumers are thermometers, gauze, plaster, and elastic bandages. Conversely, the smaller the value of support for a combination of medical devices means that recommendations are given based on medical devices that are rarely purchased. The results of the application of the a priori method with a minimum support of 30% with a combination of 3 and 4 itemsets are if the thermometer, gauze, plaster, elastic bandages. The priori method used is quite effective in providing the final drug combination that is often purchased by consumers. The level of accuracy of the test using the a priori method is 100%.]]>
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