Purchase Pattern Analysis on Komol Kopi Transaction Data Using Apriori Algorithm

Abstract

This research aims to analyze purchasing patterns in Komol Kopi transaction
data using the Apriori algorithm. This algorithm enables the discovery of
relationships between items in large datasets that can be used to support
business decisions, such as bundling promotions and inventory management.
The dataset includes 12 transactions with various combinations of items, such
as Kopi Hitam, Kopi Tubruk, and Nasi Telur. The analysis results show some
significant purchase patterns with high support, confidence, and lift values.
An example of an association found is between Kopi Hitam and Es Teh, which
provides insights for more effective marketing strategies. This study confirms
that the Apriori algorithm is an efficient tool in unearthing purchasing
patterns, providing a solid foundation for the development of data-driven
business strategies. Further research can integrate this analysis with
recommendation systems to improve customer experience.