PENERAPAN ALGORITMA NAIVE BAYES DALAM MEMPREDIKSI PENJUALAN MATERIAL BANGUNAN - sandy, sandy; sitohang, sunarsan (Computer Science and Industrial Engineering, 2022)
Application of data mining in predicting sales of building materials PT. Tanjung Uncang uses Naïve Bayes by implementing it into the WEKA 3.9 application to predict sales of materials that are valid and unsold. In designing research designs, researchers need designs as instructions and directions for explanations starting from how to get data, process data and also the steps for completing data processing. The data mining technique uses the Naive Bayes algorithm from sales at PT. Tanjung Uncang which involves 186 building material sales data by influencing 12 variables, namely January, February, March, April, May, June, July, August, September, October, November, and December variables which have been calculated using the WEKA 3.9 application, obtaining 135 data. goods sold as much as 72,5806% and there were 51 data on goods that were not sold as much as 27,4194%. With the Naïve Bayes algorithm, it can help speed up sales data processing.