Algoritma Apriori untuk Menganalisis Pola Pembelian Pelanggan (Studi Kasus: Cafe dan Restaurant XYZ) - Michelle Graciela; Desi Pibriana (BETRIK, 2025)
XYZ is a cafe and restaurant engaged in the culinary field and currently often offers bundling packages to its customers. However, from the interview results it is clear that the bundling packages currently offered are not sufficient to increase sales. For this reason, it is necessary to analyze customer purchasing patterns with the Apriori algorithm to help increase sales at XYZ Cafe and Restaurant. The process of implementing the Apriori algorithm is carried out using the CRISP-DM method which consists of six stages, namely business understanding, data understanding, data preparation, modeling, evaluation, and dissemination. This algorithm is used to generate association rules that can be used as a basis for designing promotional strategies, preparing bundling packages and menu placement. Based on the results of the analysis conducted using Google Colab, the combination of items with the highest confidence and lift values was found, namely between Pekcamkee Chicken ½ Tail and Hainam Rice with a confidence of 57.14% and a lift of 17.44. The results were then visualized in the form of a dashboard built using the PHP programming language with a MySQL database to make it easier for users to understand. It can be concluded that the application of data mining can help Cafe and Restaurant XYZ find relevant customer purchasing patterns so that it can support data-based decision making