Implementasi Data Mining Menggunakan Metode Algoritma FP-Growth Dan Algoritma Apriori Pada Toko IBR Jaya Untuk Meningkatkan Penjualan

Abstract

Dian trading business is one of the grocery stores engaged in buying and selling the main household needs of nine basic ingredients which have been doing a lot of grocery sales transactions. This transaction Data continues to grow every day and in the IBR Jaya store sales transaction data is only presented as an archive or report and it is not mentioned what the benefits of these data are. Nah, the problem at the IBR Jaya store is the improvement of improvements due to the shortage of basic food stocks that are often purchased by consumers are not available which results in improvements and usability improvements then the FP-Growth algorithm is used to analyze patterns of improvement and a priori algorithms for comparison through archived transaction data goods that will be purchased later as a reference to increase food stocks so as to increase sales at the IBR Jaya Food Store in the hope that this increase can help this is one of many ways to make money online. Association rules are a process in Data Mining to establish all associative policies that meet the minimum requirements for support (minsup) and trust (minconf) in a database . In association rules, there are 2 methods that can be used, namely a priori method and FP-Growth method. In this study the method used is FP-Growth algorithm and a priori algorithm, FP-Growth algorithm and a priori method is a method to find the most frequently appearing data set (frequent itemset) without using candidate generation that is suitable to analyze a data transaction.