The prediction of undergraduate student performance in chemistry course using multilayer perceptron
Chemical industries are the essential factors to convert from raw materials into the target products that we use in our daily life. This has brought a tremendous change in the way things operate. In the interest of demanding the chemical engineers is increasing, simultaneously the failure rate of a...
| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IOP Publishing
2020
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/27755/ http://umpir.ump.edu.my/id/eprint/27755/13/The%20prediction%20of%20undergraduate%20student.pdf |
| _version_ | 1848822875580006400 |
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| author | Che Akmal, Che Yahaya Che Yahaya, Yaakub Ahmad Firdaus, Zainal Abidin Mohd Faizal, Ab Razak Nuresa Fatin, Hasbullah Mohamad Fadli, Zolkipli |
| author_facet | Che Akmal, Che Yahaya Che Yahaya, Yaakub Ahmad Firdaus, Zainal Abidin Mohd Faizal, Ab Razak Nuresa Fatin, Hasbullah Mohamad Fadli, Zolkipli |
| author_sort | Che Akmal, Che Yahaya |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Chemical industries are the essential factors to convert from raw materials into the target products that we use in our daily life. This has brought a tremendous change in the way things operate. In the interest of demanding the chemical engineers is increasing, simultaneously the failure rate of a student in a chemistry course also rising. The students that register the chemistry course often fail whether in the first semester or following semester. Moreover, students also unable to recognize whether they can adapt in this course and graduate successfully. The objective of this research is to predict the students in the chemical course either quit or graduate in the future by using enhanced Multilayer Perceptron (MLP) machine learning classification with Adaboost. The accuracy of the results from this study is 92.23% percent. |
| first_indexed | 2025-11-15T02:48:11Z |
| format | Conference or Workshop Item |
| id | ump-27755 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:48:11Z |
| publishDate | 2020 |
| publisher | IOP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-277552020-12-23T02:36:12Z http://umpir.ump.edu.my/id/eprint/27755/ The prediction of undergraduate student performance in chemistry course using multilayer perceptron Che Akmal, Che Yahaya Che Yahaya, Yaakub Ahmad Firdaus, Zainal Abidin Mohd Faizal, Ab Razak Nuresa Fatin, Hasbullah Mohamad Fadli, Zolkipli QA76 Computer software Chemical industries are the essential factors to convert from raw materials into the target products that we use in our daily life. This has brought a tremendous change in the way things operate. In the interest of demanding the chemical engineers is increasing, simultaneously the failure rate of a student in a chemistry course also rising. The students that register the chemistry course often fail whether in the first semester or following semester. Moreover, students also unable to recognize whether they can adapt in this course and graduate successfully. The objective of this research is to predict the students in the chemical course either quit or graduate in the future by using enhanced Multilayer Perceptron (MLP) machine learning classification with Adaboost. The accuracy of the results from this study is 92.23% percent. IOP Publishing 2020 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/27755/13/The%20prediction%20of%20undergraduate%20student.pdf Che Akmal, Che Yahaya and Che Yahaya, Yaakub and Ahmad Firdaus, Zainal Abidin and Mohd Faizal, Ab Razak and Nuresa Fatin, Hasbullah and Mohamad Fadli, Zolkipli (2020) The prediction of undergraduate student performance in chemistry course using multilayer perceptron. In: IOP Conference Series: Materials Science and Engineering, The 6th International Conference on Software Engineering & Computer Systems , 25-27 September 2019 , Pahang, Malaysia. pp. 1-8., 769 (012027). ISSN 1757-899X (Published) https://doi.org/10.1088/1757-899X/769/1/012027 |
| spellingShingle | QA76 Computer software Che Akmal, Che Yahaya Che Yahaya, Yaakub Ahmad Firdaus, Zainal Abidin Mohd Faizal, Ab Razak Nuresa Fatin, Hasbullah Mohamad Fadli, Zolkipli The prediction of undergraduate student performance in chemistry course using multilayer perceptron |
| title | The prediction of undergraduate student performance in chemistry course using multilayer perceptron |
| title_full | The prediction of undergraduate student performance in chemistry course using multilayer perceptron |
| title_fullStr | The prediction of undergraduate student performance in chemistry course using multilayer perceptron |
| title_full_unstemmed | The prediction of undergraduate student performance in chemistry course using multilayer perceptron |
| title_short | The prediction of undergraduate student performance in chemistry course using multilayer perceptron |
| title_sort | prediction of undergraduate student performance in chemistry course using multilayer perceptron |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/27755/ http://umpir.ump.edu.my/id/eprint/27755/ http://umpir.ump.edu.my/id/eprint/27755/13/The%20prediction%20of%20undergraduate%20student.pdf |