IMPLEMENTASI ALGORITMA APRIORI UNTUK REKOMENDASI PAKET MENU PADA CAFE ABC BERBASIS WEBSITE

Abstract

Increased competition that encourages business actors to make various ways in sales strategies to attract customers. One of them is the recommendation for menu packages, but in making menu package recommendations based on the wishes of the owner only. Utilization of transaction data can be used to help provide advice in the form of association rules that can provide advice to business owners to assist in making decisions for choosing menu package promotion recommendations. Association rules are obtained by implementing a priori algorithm data mining to a website-based system using Laravel and the resulting calculation results are in the form of product association rules that are purchased simultaneously. With a minimum support value of 1%, there are 48 items in the 1-itemset that pass the minimum support and 59 association rules formed from the entire transaction of 756 data with a confidence value of more than 6%. From the resulting association rules, there are association rules with the highest confidence value, which is 100% in the form of takjil and iftar pairs purchased simultaneously, so that they can provide advice to the Ruang Temu owner to recommend menu packages for takjil and iftar foods.