Predicting Employment Condition of TARC'S ICT Graduates Using Backpropagation Neural Network
This research is conducted with the purpose of classifying the employment condition of ICT students after their graduation using Backpropagation Neural Network (BPNN). To narrow down the scope of the research, ICT students from Tunku Abdul Rahman College (TARC) are targeted. The employment condition...
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| Format: | Thesis |
| Language: | eng eng |
| Published: |
2009
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| Subjects: | |
| Online Access: | https://etd.uum.edu.my/2064/1/Tay_Shu_Shiang.pdf https://etd.uum.edu.my/2064/2/1.Tay_Shu_Shiang.pdf |
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| Summary: | This research is conducted with the purpose of classifying the employment condition of ICT students after their graduation using Backpropagation Neural Network (BPNN). To narrow down the scope of the research, ICT students from Tunku Abdul Rahman College (TARC) are targeted. The employment condition will be predicted and classified based on several macroscopic and microscopic criterion indentified. The macroscopic reasons include the social and the governmental factors while the microscopic reasons cover the college and the student factors. This paper will show the BPNN steps involved in creating a suitable multilayer-perceptron classification model for the employment condition. Detail descriptions of the BPNN methodologies applied are also included in the report. The findings of the research are expected to provide TARC's management an in-depth view on their students' marketability and adaptability in the work fields. |
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