Penerapan Algoritma Naïve Bayes Untuk Prediksi Penjualan Produk Iconnet

Abstract

ICONNET, which is a product from PT Indonesia Comnets Plus for the retail customer segment, is a new internet provider. ICONNET intends to provide the best for the Indonesian people. They need to have a strategy in order to continue to increase sales of their products. In the sales process, one way to increase product sales is to know the history of product sales to customers. Is it in accordance with the sales target or not. So if the sales target has not been met, it can be used as a performance evaluation, especially for the marketing and sales team. Therefore, the authors created a sales prediction system by implementing the Naive Bayes Classifier Algorithm which can be used to predict sales of ICONNET products based on previously recorded data. Testing the system with the black box method and performance testing. The resulting output is a web-based system. The percentage of accuracy test results are 89.189%. While the results of performance testing obtained a score with grade A (91%). It is hoped thet in the future this system can be developed with more attention to user needs.