Artificial Neural Network Model (ANN) to predict electrical students' academic performance / Siti Aishah Che Kar ... [et al.]
This research presents a study of correlation between subjects of Diploma in Electrical Engineering (Electronics/Power) at Universiti Teknologi MARA(UiTM) Cawangan Terengganu using ANN. The analysis was done to see the effect of mathematical subjects (Pre-calculus and Calculus 1) and core subjects (...
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| Main Authors: | , , , , |
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| Format: | Research Reports |
| Language: | en |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/53781/1/53781.pdf https://ir.uitm.edu.my/id/eprint/53781/ |
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| Summary: | This research presents a study of correlation between subjects of Diploma in Electrical Engineering (Electronics/Power) at Universiti Teknologi MARA(UiTM) Cawangan Terengganu using ANN. The analysis was done to see the effect of mathematical subjects (Pre-calculus and Calculus 1) and core subjects (Electric Circuit 1) towards Electronics 1, a core subject with a history of high failure rate percentage (more than 25%). This research has been conducted on current final semester students (Semester 5). Seven (7) models of ANN are developed to observe the correlation between the subjects. In order to develop an ANN model, ANN design and parameters need to be chosen to find the best model. In this study, historical data from students' databases were used for training and testing purposes. The Regression Coefficient, (R) values from the developed models was observed and analyzed to see the effect of the subject on the performance of students. It can be proven that mathematical subjects (Pre-calculus and Calculus 1) and core subjects (Electric Circuit 1) have significant correlation with the Electronics 1 subject. |
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