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Universitas Tanjungpura
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Prediction Of The Number Of Course Participants Using Random Forest Regression Algorithm Rina Septiriana; Anggi Perwitasari; Tursina
Jurnal Mantik Vol. 6 No. 3 (2022): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i3.3175

Abstract

Classroom management is the process of using resources effectively to achieve goals. Planning the schedule is not easy because sometimes, after a schedule designed and when the schedule is published and used, there are problems where the class division of a course is not right on target. This study used the random forest regression method to predict the number of class participants. Data pattern affects the accuracy of calculating the predicted value. The best RMSE and MAE results in the Matematika Dasar Course are 6,51 for RMSE and 2,12 for MAE. At the same time, the prediction of course participant number is 73,18.
Co-Authors Anggi Perwitasari Rina Septiriana