Pengembangan Model Regresi Linier Untuk Prediksi Jumlah Penerimaan Mahasiswa Baru (Studi Kasus: Mahasiswa Jurusan Matematika FMIPA UNM)

The number of students from 2000 to 2023 in mathematical courses each year increases and in mathematical education programs decreases. The data obtained is further used to predict the number of students in the next 5 years. The purpose of the study to determine the parameters of simple linear regression models used to predict the number of students on mathematical and mathematical education programs in the next 5 years. The study begins with data retrieval, data review, parameters estimation, regression assumption testing, hypothesis testing, making linear regression models simple, performing model predictions and evaluation. The results of this study showed that the number of students of mathematical programmes had increased, linear regression model y = 39,783 + 0.3774x while in mathematical education prodes had decreased, linear regression model y = 154.29 – 0.7865x. The results of the predicted number of students in 2024 - 2028 will come on mathematical prodes 49,2., 49,6., 50., 50,4., 50,7. At Mathematical Education Prodi 134.6., 133.8., 133.1., 132.3., 131.5. With model test scores on mathematical prodies are MSE=199.4., RMSE=14.12., MAPE=0.236 and on mathematical education prodies are MSE=2.076.44., RMSE=45,568., and MAPE=0.229. Which means that the model is very good and worth using in prediction.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-30
DOI
https://doi.org/10.5281/zenodo.14286520
Primary Topic
Mathematics Education and Pedagogy
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pengembangan Model Regresi Linier Untuk Prediksi Jumlah Penerimaan Mahasiswa Baru (Studi Kasus: Mahasiswa Jurusan Matematika FMIPA UNM)

Zenodo (CERN European Organization for Nuclear Research)
Mathematics Education and Pedagogy
article

Pengembangan Model Regresi Linier Untuk Prediksi Jumlah Penerimaan Mahasiswa Baru (Studi Kasus: Mahasiswa Jurusan Matematika FMIPA UNM)

article en

Abstract

The number of students from 2000 to 2023 in mathematical courses each year increases and in mathematical education programs decreases. The data obtained is further used to predict the number of students in the next 5 years. The purpose of the study to determine the parameters of simple linear regression models used to predict the number of students on mathematical and mathematical education programs in the next 5 years. The study begins with data retrieval, data review, parameters estimation, regression assumption testing, hypothesis testing, making linear regression models simple, performing model predictions and evaluation. The results of this study showed that the number of students of mathematical programmes had increased, linear regression model y = 39,783 + 0.3774x while in mathematical education prodes had decreased, linear regression model y = 154.29 – 0.7865x. The results of the predicted number of students in 2024 - 2028 will come on mathematical prodes 49,2., 49,6., 50., 50,4., 50,7. At Mathematical Education Prodi 134.6., 133.8., 133.1., 132.3., 131.5. With model test scores on mathematical prodies are MSE=199.4., RMSE=14.12., MAPE=0.236 and on mathematical education prodies are MSE=2.076.44., RMSE=45,568., and MAPE=0.229. Which means that the model is very good and worth using in prediction.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 42%
Mathematics Education and Pedagogy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Pengembangan Model Regresi Linier Untuk Prediksi Jumlah Penerimaan Mahasiswa Baru (Studi Kasus: Mahasiswa Jurusan Matematika FMIPA UNM) · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS