IMPLEMENTATION OF NAIVE BAYES CLASSIFIER ALGORITHM FOR DETERMINING CUSTOMERS’ BUYING INTEREST ON SOFA (A CASE STUDY IN BAYAU KELUMER FURNITURE)

Abstract

Interest is the personal intention and related to attitude.Individuals who are interested in objects have strength and desires to approach or posses the objects. Consumers’ buying interest can be seen from many aspects. One of the aspects is sales. Sales are the important element in marketing divisions of a company to obtain more profits in order to continue the businesses. Kelumer Bayau  is the company engaged in marketing and selling sofas with 8-year experience. Kelumer Bayau has a high quality with very competitive prices. The formulation of this research was how Kelumer Bayau predicted or determined the customers’ buying interest on the sales of furniture based on recorded data. The prediction was based on the owners’ decision to determine a number of goods provided by the company and to avoid the a large quantities of goods. Therefore, the objective of this research was predicting and determining the customers’ buying interest using Naive Bayes Clasification algorithm through data mining techniques. This research used training and testing data about sofa sales for the last 3 years with the several variables i.e., types, colors, sizes, motifs and prices.

Keywords: Prediction, Naive Bayes Classification, Sofa