Website Personalization Using Association Rules Mining

Abstract

Many companies are redefining their business strategies to improve the business output. Business over internet provides the opportunity to customers and partners where their products and specific business can be found. Web usage mining is the type of web mining activity that involves the automatic discovery of user access patterns from web servers. A real-world challenging task of the web master of an organization is to match the needs of user and keep their attention in their web site. So, web pages can capture the intuition of the user and provide them with the recommendation list. Personalize e-commerce website is done after knowing the habits and behavior patterns of customers e-commerce website using web usage mining with association rules mining apriori algorithms. The method used is a method of analysis and design. In the method of analysis, research variables are determined, and data of sales are collected. In addition, the method of analysis is also performed to measure the accuracy of the apriori algorithm. Designing apriori, program design, and the design of the screen is done in the design method. Results are achieved in the form of an e-commerce website that is personalized using association rules mining apriori algorithm that can recommend the goods in accordance with the preferences and needs of the user. The conclusion of this study is to obtain patterns of association, it takes the data transactions made by customers and the recommendations given by the apriori algorithm would be more accurate if the transaction data is processed more, the categories of goods are fewer, the limit minimum value of support and the limit minimum value of confidence are high.