The Implementation of the apriori algorithm to increase sales of clothing stores based on purchase patterns - Khoirul Muhtadin; Dwi Anggarani; Khojanah Hasan; Survival Survival; Anastasia L Maukar; Irfan Faton (Journal of Information Technology application in Education, Economy, Health and Agriculture, 2026)
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.