Paradigma
Vol 23, No 1 (2021): Periode Maret 2021

Analisis Runtun Waktu Untuk Memprediksi Jumlah Mahasiswa Baru Dengan Model Random Forest

Marchell Rianto (STMIK-STIE Mikroskil Medan)
Roni Yunis (STMIK-STIE Mikroskil)



Article Info

Publish Date
22 Mar 2021

Abstract

Admission of new students is an important process in educational institutions such as tertiary institutions which is useful for screening accepted prospective students according to the criteria determined by the college. The purpose of this study is to predict the number of new students using the Random Forest model with the new student admissions dataset of XYZ University. The Random Forest Model is a machine learning algorithm that is excellent at solving classification and regression problems. Based on the research results, it was found that the resulting model has an accuracy rate of 99.8% with MSE and MAE values of 0.02% in predicting new students. The best parameter of the model with a maxnodes value of 100 and ntree 900 and a decreasing trend in the number of students for the next few years.

Copyrights © 2021






Journal Info

Abbrev

paradigma

Publisher

Subject

Computer Science & IT

Description

The first Paradigma Journal was published in 2006, with the registration of the ISSN from LIPI Indonesia. The Paradigma Journal is intended as a media for scientific studies of research, thought and analysis-critical issues on Computer Science, Information Systems and Information Technology, both ...