Analysis of Milkshake Beverage Sales using Apriori Algorithm

Abstract

This research discusses the application of Data Mining with the Apriori
algorithm on milkshake drink sales to support Business Intelligence. The
research process includes collecting sales transaction data, forming frequent
itemsets, and analyzing association rules using metrics such as support and
confidence. The results show that product combinations, such as Chocolate
and Strawberry, have high purchase rates with support reaching 75% and
confidence up to 75%. These findings provide important insights for business
owners in designing more effective marketing strategies, including
promotions and stock management optimization. By utilizing the Apriori
algorithm, this research successfully identified significant purchase patterns
that can drive growth and improve customer satisfaction in the food and
beverage industry.