Analysis of Cigarette Sales Transactions Using Apriori Algorithm at Madura Store

Abstract

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.