IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI MEMBER BARU MENGGUNAKAN LINEAR REGRESSION PADA PT. GSI - Agus Rizkiawan; Tri Wahyudi (Politeknik Bisnis Indonesia, 2023)
PT.GSI is a company that provides digital marketing learning courses. Companies market their products online to get audience data. However, it turns out that there is a discrepancy between the number of audiences and the number of those who register as new members and this makes it difficult for the company to estimate the number of new members in the future. The purpose of this study is to implement data mining using the Linear Regression algorithm in order to be able to predict new members in the future, and find out what the RMSE value is to find out the error value of the model applied in making predictions. In this study, the variables used consisted of 7 independent variables in the dataset, there were only 5 variables that affected the prediction results, these variables were Outgoing Call, Answer, Call Duration, Gold Package and Silver Package. Meanwhile, the No Answer and Candidate variables had no effect. Based on the test results with RapidMiner, it shows that the performance generated by the Linear Regression algorithm model has good performance with accurate prediction results, showing an RMSE value of 0.098.