LINEAR REGRESSION FOR DISCOUNTING PRESENTATION RECOMMENDATIONS (Kaggle Dataset)

Abstract

In the business of selling goods, there must be goods that do not sell well and sell well. How to make unsold items sell well by giving customers a discount or discount strategy. The goal is to provide discounted prices to attract customers' attention and increase sales turnover. Prediction to give the right discount presentation is needed in the discount strategy. How to determine discount prediction using linear regression method, looking for line equations by training data taken from Kaggle.com. The data were trained to find the constants and coefficients of the independent variables. The resulting line equation will be tested to determine the discount prediction that will be given and calculate the error value. The data used is painting sales data taken from Kaggle.com, a total dataset of 1525, and a prediction calculation is made with 225 lines of test data. The input variable used is the price of the painting, and the output variable is the discount presentation. The process of evaluating the prediction results by calculating the MAE value, the difference between the actual data and the predicted data, the MAE value from the trial is 0.108.