Adaboost-multilayer perceptron to predict the student’s performance in software engineering
Software Engineering (SE) course is one of the backbones of today's computer technology sophistication. Effective theoretical and practical learning of this course is essential to computer students. However, there are many students fail in this course. There are many aspects that influence a st...
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| Format: | Article |
| Language: | English |
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IAES
2019
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/26805/1/Adaboost-multilayer%20perceptron%20to%20predict%20the%20student%E2%80%99s%20performance%20.pdf |
| _version_ | 1796993738766024704 |
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| author | Ahmad Firdaus, Zainal Abidin Mohd Faaizie, Darmawan Mohd Zamri, Osman Shahid, Anwar Shahreen, Kasim Yunianta, Arda Sutikno, Tole |
| author_facet | Ahmad Firdaus, Zainal Abidin Mohd Faaizie, Darmawan Mohd Zamri, Osman Shahid, Anwar Shahreen, Kasim Yunianta, Arda Sutikno, Tole |
| author_sort | Ahmad Firdaus, Zainal Abidin |
| collection | UMP |
| description | Software Engineering (SE) course is one of the backbones of today's computer technology sophistication. Effective theoretical and practical learning of this course is essential to computer students. However, there are many students fail in this course. There are many aspects that influence a student's performance. Currently, student performance analysis methods just focus on historical achievement and assessment methods given in the class. Need more research to predict student's performance to overcome the problem of student failing. The objective of this research is to perform a prediction for student's performance in the SE using enhanced Multilayer Perceptron (MLP) machine learning classification with Adaboost. This research also investigates the requirements of each student before registering in this course. This research achieved 87.76 percent accuracy in classifying the performance of SE students. |
| first_indexed | 2024-03-06T12:38:13Z |
| format | Article |
| id | UMPir26805 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:38:13Z |
| publishDate | 2019 |
| publisher | IAES |
| record_format | dspace |
| spelling | UMPir268052020-02-28T09:02:07Z http://umpir.ump.edu.my/id/eprint/26805/ Adaboost-multilayer perceptron to predict the student’s performance in software engineering Ahmad Firdaus, Zainal Abidin Mohd Faaizie, Darmawan Mohd Zamri, Osman Shahid, Anwar Shahreen, Kasim Yunianta, Arda Sutikno, Tole QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Software Engineering (SE) course is one of the backbones of today's computer technology sophistication. Effective theoretical and practical learning of this course is essential to computer students. However, there are many students fail in this course. There are many aspects that influence a student's performance. Currently, student performance analysis methods just focus on historical achievement and assessment methods given in the class. Need more research to predict student's performance to overcome the problem of student failing. The objective of this research is to perform a prediction for student's performance in the SE using enhanced Multilayer Perceptron (MLP) machine learning classification with Adaboost. This research also investigates the requirements of each student before registering in this course. This research achieved 87.76 percent accuracy in classifying the performance of SE students. IAES 2019-12 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26805/1/Adaboost-multilayer%20perceptron%20to%20predict%20the%20student%E2%80%99s%20performance%20.pdf Ahmad Firdaus, Zainal Abidin and Mohd Faaizie, Darmawan and Mohd Zamri, Osman and Shahid, Anwar and Shahreen, Kasim and Yunianta, Arda and Sutikno, Tole (2019) Adaboost-multilayer perceptron to predict the student’s performance in software engineering. Bulletin of Electrical Engineering and Informatics, 8 (4). pp. 1556-1562. ISSN 2089-3191 (Print); 2302-9285 (Online). (Published) http://journal.portalgaruda.org/index.php/EEI/article/view/1923 |
| spellingShingle | QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Ahmad Firdaus, Zainal Abidin Mohd Faaizie, Darmawan Mohd Zamri, Osman Shahid, Anwar Shahreen, Kasim Yunianta, Arda Sutikno, Tole Adaboost-multilayer perceptron to predict the student’s performance in software engineering |
| title | Adaboost-multilayer perceptron to predict the student’s performance in software engineering |
| title_full | Adaboost-multilayer perceptron to predict the student’s performance in software engineering |
| title_fullStr | Adaboost-multilayer perceptron to predict the student’s performance in software engineering |
| title_full_unstemmed | Adaboost-multilayer perceptron to predict the student’s performance in software engineering |
| title_short | Adaboost-multilayer perceptron to predict the student’s performance in software engineering |
| title_sort | adaboost multilayer perceptron to predict the student s performance in software engineering |
| topic | QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/26805/1/Adaboost-multilayer%20perceptron%20to%20predict%20the%20student%E2%80%99s%20performance%20.pdf |
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