Korelasi Permasalahan Kulit Wajah terhadap Jenis Produk yang Digunakan Menggunakan Metode Apriori

The Apriori method is one of the algorithms used in data mining to find association patterns, such as "association rules", in large data sets. This method was developed by Rakesh Agrawal and Ramakrishnan Srikant in 1994. The purpose is to test the correlation between facial skin problems and the type of product used by finding min support and min confidence using the apriori method.The results obtained based on this analysis are that there are 2 rules that meet the minimum requirements to form a combination of 2 itemsets with a minimum support value of 95% and a minimum confidence of 100%.