The Implementation of the apriori algorithm to increase sales of clothing stores based on purchase patterns

Khoirul Muhtadin (Universitas Widya Gama Malang)
Dwi Anggarani (Universitas Widya Gama Malang)
Khojanah Hasan (Universitas Widya Gama Malang)
Survival Survival (Universitas Widya Gama Malang)
Anastasia L Maukar (President University)
Irfan Faton (Universitas Widya Gama Malang)

JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Vol. 3 No. 2 (2026): Vol. 3 No. 2 (2026): June

In the growing digital era, retail industries face significant challenges and opportunities. Clothing stores, as one type of retail industry, need to adapt to changes in consumer behavior that are increasingly complex. With the increasing variety of choices and easy access to information, understanding customer purchasing patterns is key to gaining a competitive advantage. Purchasing patterns reflect consumer preferences, not only that but can also reveal something hidden that if analyzed properly, can be utilized for a more effective marketing strategy. By applying a data-driven approach, it is hoped that clothing stores can formulate more targeted marketing strategies, improve customer satisfaction, and ultimately, drive sustainable sales growth. This research approach is exploratory quantitative, which aims to find customer purchase patterns from clothing store transaction data using the Apriori algorithm. The results of data exploration are used to develop data-based sales strategies.