PENDEKATAN DATA MINING UNTUK MEMILIH PRODUK TERLARIS MENGGUNAKAN ALGORITMA NAIVE BAYES

Abstract

Technological advances today can be exploited to process data into more useful information. In data collection, information collection is especially useful to maximize profits and develop marketing strategies. One way to increase profits is by using data mining techniques to help business actors in making decisions about stocks, increased profits and more. The Matahari Department Store is the largest retail platform in Indonesia, one of the retail stores located in Batam is the Matahari Department store Nagoya Hill Batam. The transaction data on the store that is still processed does not use a method that causes the processing of product sales data to be less effective and less efficient. Seeing from the number of transactions, a system is needed to predict the sale of the best-selling product as long as it can determine the correct stock for the products sold and can increase the profit, sale and purchase of the product. This research was conducted with the aim of applying data mining methods using the Naive Bayes Classifier algorithm to select the best-selling products in the outlet of the Matahari Nagoya Hill Batam Department Store. By using the collected sales data, the system is expected to increase profits steadily and avoid shortages of product stocks. Through analysis using the Naive Bayes Classifier method, the study achieved an accuracy of 67% and obtained a bag sales result to be the best-selling sale during January 2023 through March 2023 with a sales percentage of 20%.