Analisa Transaksi Penjualan Menu Makanan pada Warung Makan Menggunakan Algoritma Apriori

Abstract

The increasingly rapid development of the culinary sector makes commercial competition in this field increasingly fierce. Food stalls serve a variety of menus and drinks, but stall owners need to strive to create product innovations in order to provide satisfactory service to customers. Under these conditions, a computer technician is needed to find out recommendations for food stall menus. The analysis method used is a data mining technique with the Apriori algorithm, where this algorithm is used to identify the data sets that appear most frequently (frequent itemset). The research results show that the highest support and confidence values ​​are Ayam Penyet and Fried Rice with 50% support and confidence values 76%. This can be a combination of menus suggested from data that has been collected and applied according to an a priori algorithm which is expected to be used to evaluate service and possibly increase guest satisfaction so that the Food Stall can develop more quickly.