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Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar

Along the way with the changes in the education landscape nowadays, the grade is not the only determinant to predict the students' success. In the context of a student's academic performance, it is better to focus on measuring the efficiency of academic achievements that used multiple dete...

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主要な著者: Mohamad Razi, Nor Faezah, Baharun, Norhayati, Omar, Nasiroh
フォーマット: 論文
言語:English
出版事項: Universiti Teknologi MARA, Perak 2022
主題:
QA Mathematics
Mathematical statistics. Probabilities
Data processing
オンライン･アクセス:https://ir.uitm.edu.my/id/eprint/61732/1/61732.pdf
https://ir.uitm.edu.my/id/eprint/61732/
https://mijuitm.com.my/view-articles/
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id my.uitm.ir.61732
record_format eprints
spelling my.uitm.ir.617322023-06-22T03:12:06Z https://ir.uitm.edu.my/id/eprint/61732/ Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar msij Mohamad Razi, Nor Faezah Baharun, Norhayati Omar, Nasiroh QA Mathematics Mathematical statistics. Probabilities Data processing Along the way with the changes in the education landscape nowadays, the grade is not the only determinant to predict the students' success. In the context of a student's academic performance, it is better to focus on measuring the efficiency of academic achievements that used multiple determinants of holistic outcome rather than just focus on the student grade. Data Analysis Envelopment (DEA) is a nonparametric method that widely used in many fields to measure performances efficiency but limited research has been reported on DEA in education domain. Acknowledging DEA time consuming issue when involving a huge size of data, recent research on deploying machine learning in DEA keeps on rapid progressing. This paper presents a new research framework of DEA and Auto-ML predictive model for the academic achievement efficiency. The framework includes variety options of machine learning to be compared from the conventional manual setting into the recent Auto-ML technique. The research framework will provide new insights into the decision-making process particularly in the education context. Universiti Teknologi MARA, Perak 2022-05 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/61732/1/61732.pdf Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar. (2022) Mathematical Sciences and Informatics Journal (MIJ) <https://ir.uitm.edu.my/view/publication/Mathematical_Sciences_and_Informatics_Journal_=28MIJ=29.html>, 3 (1). pp. 86-99. ISSN 2735-0703 https://mijuitm.com.my/view-articles/ 10.24191/mij.v3i1.18284 10.24191/mij.v3i1.18284 10.24191/mij.v3i1.18284
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic QA Mathematics
Mathematical statistics. Probabilities
Data processing
spellingShingle QA Mathematics
Mathematical statistics. Probabilities
Data processing
Mohamad Razi, Nor Faezah
Baharun, Norhayati
Omar, Nasiroh
Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar
description Along the way with the changes in the education landscape nowadays, the grade is not the only determinant to predict the students' success. In the context of a student's academic performance, it is better to focus on measuring the efficiency of academic achievements that used multiple determinants of holistic outcome rather than just focus on the student grade. Data Analysis Envelopment (DEA) is a nonparametric method that widely used in many fields to measure performances efficiency but limited research has been reported on DEA in education domain. Acknowledging DEA time consuming issue when involving a huge size of data, recent research on deploying machine learning in DEA keeps on rapid progressing. This paper presents a new research framework of DEA and Auto-ML predictive model for the academic achievement efficiency. The framework includes variety options of machine learning to be compared from the conventional manual setting into the recent Auto-ML technique. The research framework will provide new insights into the decision-making process particularly in the education context.
format Article
author Mohamad Razi, Nor Faezah
Baharun, Norhayati
Omar, Nasiroh
author_facet Mohamad Razi, Nor Faezah
Baharun, Norhayati
Omar, Nasiroh
author_sort Mohamad Razi, Nor Faezah
title Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar
title_short Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar
title_full Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar
title_fullStr Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar
title_full_unstemmed Machine learning predictive model of academic achievement efficiency based on data envelopment analysis / Nor Faezah Mohamad Razi, Norhayati Baharun and Nasiroh Omar
title_sort machine learning predictive model of academic achievement efficiency based on data envelopment analysis / nor faezah mohamad razi, norhayati baharun and nasiroh omar
publisher Universiti Teknologi MARA, Perak
publishDate 2022
url https://ir.uitm.edu.my/id/eprint/61732/1/61732.pdf
https://ir.uitm.edu.my/id/eprint/61732/
https://mijuitm.com.my/view-articles/
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score 13.251813

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