Analysys of Consumer Buying Behavior of Goods and Services Using The Naïve Bayes Method and Clustering Study in The Computer Service Shop

Abstract

Based on the observation results at Anik Komputer as a company providing computer, printer, and other device services, online sales results have a significant influence on revenue generation. Therefore, it is necessary to know the most significant factors that influence consumers to buy goods and services online. This study aims to identify factors that influence purchasing decisions, evaluate consumer behavior patterns, and propose strategic steps based on web intelligent. The analysis method uses Data Mining with the Naïve Bayes and Clustering algorithms. The results of this study indicate that the factors that influence purchasing decisions at Anik Komputer are price, customer reviews, and stock availability. Customer segmentation based on purchasing patterns through Clustering analysis produces three main segments, namely loyal customers (30% of total customers) who contribute the most to total sales of 40%, price sensitive customers (50% of total customers) who contribute 45% to sales, and new customers (20% of total customers) who contribute 15% to sales. This analysis provides deeper insight into consumer behavior that can be applied in intelligent web-based marketing strategies to increase the effectiveness and efficiency of online sales.