Analisis Pola Pembelian Pelanggan Menggunakan Algoritma Apriori untuk Strategi Promosi

Abstract

This research was conducted at a cafe located in South Tangerang City. Although the cafe is quite popular, its promotional strategy management is still carried out conventionally and has not optimally utilized the available transaction data. This results in the determination of promotional packages often missing the target and failing to reflect customer preferences accurately. This research applies data mining techniques using the Apriori algorithm to extract hidden purchasing patterns from transaction data. The research utilized Altair AI Studio software with a large-scale dataset consisting of 27,251 transactions from the period of January to May 2025. The research integrated a pre-processing stage in Microsoft Excel with automatic binary transformation to obtain more precise association rules. The analysis process, using a minimum support of 1% and a minimum confidence of 10%, successfully identified significant purchasing patterns. The main findings reveal a very strong association between the purchase of Nasi Goreng Seafood and Air Mineral, with the highest lift ratio of 2.698 and a confidence value of 35.7%. In addition, patterns of association were found between snack menus (French Fries) and certain coffee variants that showed a positive correlation (lift > 1).