Penentuan Asosiation Rule Pada Penjualan Produk UMKM Tugu Mulyo Menggunakan Metode Apriori

Abstract

Pondok Roti has many existing variants, ranging from chocolate bread, mocca bread, round bread, donut bread, coconut bread, strawberry bread and pineapple bread, green bean bread, birthday cake, burgers, hot dogs, pizza, so the bread that is produced must be right so that the bread can be sold out without any stale and moldy bread because it is not sold. The number of unsold breads will harm the business owner. Transactions that occur in a day are quite a lot in this bread business. Sales transactions are still recorded manually using excel, and existing data has not been managed properly to become new information that can help the management in bread production. The many types and flavors of bread make it easy for buyers to choose and buy the bread they want and like. Looking at existing transaction data, it can be seen that buyers prefer certain flavors. Knowledge Discovery in Databases (KDD) is used to explain how the process of extracting information hidden in the database. Knowledge Discovery in Databases (KDD) and data mining are related to each other. This research uses the apriori algorithm to get a rule base for purchasing products at Pondok Roti stores. The apriori algorithm will later be used to find the most frequent combination of an itemset. Research data will be simulated to get the best rule base using the Weka application. The results of the research are in the form of association rules on the sale of Tugu Mulyo MSME products.