Penerapan Algoritma Apriori Dalam Memprediksi Penjualan Produk Di Pt.Miwada Industrial

Abstract

Along with the development of an increasingly advanced era, the role of information technology in the business world today is experiencing very rapid development. Data mining technology or data mining can help a company to discover new knowledge, which can help in managing business strategies. To determine and develop promotions to be more targeted and targeted, companies need to identify target markets. One way to recognize market conditions is to know products that are often sold, which can be observed through purchase order data. By using data mining methods, namely market basket analysis and apriori algorithm, association rules are generated that indicate the pattern of consumer purchases and how strong an item affects other items. From the results of the analysis and testing system tests using data purchase orders during the period of January 2015, 2016 and 2017 by changing the minimum support and minimum confidence parameters, it can be concluded that the best selling itemset product combination is P01-037, P01-070, P01-038 , P01-055, and P01-048. The conclusion that can be taken in the execution of this final project is Data mining and Apriori Algorithm is very useful to find out the relationship between the frequency of shoe sales that are most in-demand by consumers so that it can be used as valuable information in decision-makers to prepare any product stock needed later