Analysis of Cigarette Sales Transactions Using Apriori Algorithm at Madura Store - Mahendra, Mochammad Augustiar; Sa'adah, Mamba'us; Puspitarini, Erri Wahyu; Rahman, Afida (Journal of Information Technology application in Education, Economy, Health and Agriculture, 2025)
Developments in the cigarette industry continue to increase and there are also challenges in classifying cigarette sales. In this case, the method of classifying cigarette sales using the Apriori algorithm can be one way that can be used. The purpose of this study is to identify significant cigarette sales and classify sales transactions based on sales patterns. The method to be used in this study has several stages. First, we collect cigarette sales data from several different cigarette shops. The data includes information such as transaction ID, items purchased, and sales amounts. Then, we pre-process the data to prepare the raw data for further analysis. The results of this study indicate that classifying cigarette sales using the Apriori algorithm is able to identify significant sales patterns and classify transactions with a more adequate level of accuracy. This research provides new insights in analyzing cigarette sales data and can help decision-making in the cigarette industry.