Implementation of Stock Goods Data Mining Using the Apriori Algorithm

Abstract

Stock inventory in the pharmacy should be well recorded. This is to provide the best service to customers/buyers. Buyers who come with empty results or the drug they want to buy will not feel disappointed, especially if they have made several purchases. This research implements data mining of drug stock inventory, where in the research carried out there are many empty and excess inventory items, resulting in less than optimal service. The research method, namely the survey research method, is a research method that is carried out using surveys or data collection through research respondents. The algorithm used in analyzing the data is the Apriori algorithm. The results of this study are the results of association rules based on predetermined parameters, namely a minimum support of 25% and a minimum confidence of 60%. The rule that is formed is that if consumers buy amoxicillin, they will buy mefenamic acid with a support value of 37% and a confidence of 183%.