Prediksi nilai akademik peserta didik di masa pandemi covid-19 dengan regresi linier berganda - Syaifur Rahmatullah; Eka Herdit Juningsih; Susan Rachmawati (Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta, 2023)
With the implementation of Learning From Home (BDR) learning patterns, there are several problems that exist, namely the decline in student achievement in learning outcomes, decreased interest in learning and the presence of students in online learning activities, and decreased participation of parents/guardians of students in paying attention to learning conditions and achievements of students at SDN Cengkareng Timur 01 Pagi. On the basis of all that research related to predicting the academic value of students will later be able to help the school to make permanent decisions on the problems that occur in the school environment. This study, using the multiple linear regression method, is effectively used to predict the final grades of students, so that by predicting school institutions can take preventive steps to boost student grades. The test results from 3 tools, namely Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE) show that the prediction results are accurate enough to be used as a predictive model. Therefore, it is hoped that the prediction model will periodically test the prediction model every semester and applications that can be used directly without having to use a spreadsheet.