APPLICATION OF CLASSIFICATION ALGORITHM FOR SALES PREDICTION

Increasing sales results is a desired target for all companies both at home and abroad. The company has wide variety of products to offer. This paper (to fulfill Business Intelligence course assignment) the result an experiment from data (keaggle) about consumer demand during 2013-2015 period, then based on this we try predict classify product sales, in order make it easier classification predictions. To find out best-selling products, mining techniques are used, namely XGBoost, Decision Tree, Random Forest, Linear Regression, Nave Bayes. Based test five techniques, XGBoost model best with training value producing RMSE 0.68% testing 0.79%. method also better than previous studies.