A Comparison of Wine Quality Classification Performance by using Data Mining Techniques

Abstract

The objective of this research is to find relationship rules to segment customers based on their purchasing behavior by using the Apriori algorithm. This research studied a sample of 1000 U.S. supermarket trade items. Data were prepared and adjusted data to find correlation rules using the Apriori algorithm by analyzing product sales data and then consider what types of purchases shoppers tend to buy and how many then it is analyzed to segment customers to find data relationship rules.The results showed that a total of nine relationship rules and relationship rules could be created. The highest research was that if a customer bought six fashion items and had a purchase of 201 to 400, the customer group was male with the highest confidence at 1, support at 0.009, and correlation (Lift) at 2.00.