Penerapan Algoritma Apriori Dalam Mengidentifikasi Pola Perilaku Belanja Konsumen - Muliawan Nur, Amri; Bahtiar, Hariman; Suhartini; Fathurrahman, Imam; Muzarrofah, Liana Rozita (Infotek: Jurnal Informatika dan Teknologi, 2025)
The advancement of digital technology has brought significant changes to data management in the commercial sector, especially in retail stores. This study aims to apply the Apriori algorithm to identify patterns of consumer shopping behavior at D&D Mart, Jerowaru District, East Lombok, Indonesia. Data were collected through observation and interviews with customers. Data processing was conducted using Google Colaboratory to obtain visualizations and calculate association rules. The results show that the combination of coffee, detergent, and sugar products has a support value of 31% and a confidence level of 100%, indicating a very strong purchasing pattern for these products to occur together. This finding provides valuable insights for store owners in developing marketing strategies, such as product placement for items frequently purchased together, bundled promotional offers, and more optimal stock management. Overall, this study demonstrates that the Apriori algorithm is effective for analyzing sales transaction data in retail stores and can support data-driven business decision-making to enhance operational effectiveness and customer satisfaction.