Open AccessAnalysis of Data Mining Associations on Drug Sales at Pharmacies with APRIORI Techniques
Author(s) -
Salam Irianto Nadeak,
Yusmar Ali
Publication year - 2021
Publication title -
ijistech (international journal of information system and technology)
Language(s) - English
Resource type - Journals
ISSN - 2580-7250
DOI - 10.30645/ijistech.v5i1.113
Subject(s) - association rule learning , apriori algorithm , pharmacy , product (mathematics) , promotion (chess) , computer science , a priori and a posteriori , data mining , software , data science , advertising , business , mathematics , medicine , philosophy , geometry , family medicine , epistemology , politics , political science , law , programming language
The purpose of the research is to utilize artificial intelligence techniques in analyzing drug sales. Sources of data used are observations and interviews with shop owners. The method used as a solution is the Association method with the Apriori technique. By using the RapidMiner software, the test results are obtained using a minimum support of 25% and a minimum of 60% confidence as many as 5 rules with a predetermined itemset. The results of the study are expected to provide information and make it easier for related parties to find combinations of selling items. The results of this analysis can be used by pharmacies for marketing strategies and product promotion.