FOOD MENU ARRANGEMENT RECOMMENDATIONS USING TRANSACTION HISTORY DATA USING THE APRIORI METHOD (CASE STUDY: BEBEK PONDOK GALIH)

Abstract

REKOMENDASI PENATAAN MENU MAKANAN MENGGUNAKAN DATA HISTORI TRANSAKSI DENGAN METODE APRIORI (STUDI KASUS: BEBEK PONDOK GALIH)

The food business goes hand in hand with the development of information technology. Process efficiency must be improved to increase sales transactions and achieve consistent profits. Bebek Pondok Galih has historical data on sales transactions from year to year, with this data being useful if management can analyze consumer buying patterns so they get information on what menus are frequently ordered and the relationship between one menu and another. Based on these problems, a data analysis process is needed to form a menu arrangement recommendation by utilizing data mining using the Apriori algorithm. The a priori algorithm is a data mining method that can produce association rules. Based on its application in this study with a minimum support value of 30% and a minimum confidence level of 80%, the final rule is that if consumers purchase 600 ml of roasted duck and aqua, they will also purchase a portion of rice. so that the three menus can be made into one menu package.