ATURAN ASOSIASI MENGGUNAKAN ALGORITMA APRIORI UNTUK MENCIPTAKAN STRATEGI PEMASARAN PADA APOTEK

Abstract

The sales of pharmaceutical products among the public are increasing, especially with the recent pandemic that has led to an increase in drug sales. This has created significant potential for the pharmaceutical industry or drug sales businesses. However, proper marketing plans are required in the pharmaceutical industry to optimize revenue. Analyzing drug sales trends can provide valuable insights for creating excellent marketing plans. To develop a superior marketing plan, an analysis of sales transaction data is necessary with the help of data mining, which is useful for obtaining important information from the dataset being analyzed. The Apriori algorithm is used in this research to examine association rule patterns of drug sales in pharmacies The sales information used as dataset is consisting of 600,000 transactional data collected over six years (2014–2019). This dataset includes the date and time of sales, pharmaceutical drug brands, and other relevant information.