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

Paradigma - Jurnal Komputer dan Informatika

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Field Value
 
Title Analisis Runtun Waktu Untuk Memprediksi Jumlah Mahasiswa Baru Dengan Model Random Forest
 
Creator Rianto, Marchell
Yunis, Roni
 
Subject
random forest, jumlah mahasiswa baru, MSE, MAE
 
Description 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.
 
Publisher Universitas Bina Sarana Informatika
 
Contributor
 
Date 2021-03-22
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier https://ejournal.bsi.ac.id/ejurnal/index.php/paradigma/article/view/9781
10.31294/p.v23i1.9781
 
Source Paradigma - Jurnal Komputer dan Informatika; Vol 23, No 1 (2021): Periode Maret 2021
Paradigma; Vol 23, No 1 (2021): Periode Maret 2021
2579-3500
1410-5063
10.31294/p.v23i1
 
Language eng
 
Relation https://ejournal.bsi.ac.id/ejurnal/index.php/paradigma/article/view/9781/pdf
 
Rights Copyright (c) 2021 Paradigma - Jurnal Komputer dan Informatika
https://creativecommons.org/licenses/by-nc-sa/4.0
 

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