UUM Electronic Theses and Dissertation
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Predicting Employment Condition of TARC'S ICT Graduates Using Backpropagation Neural Network

Tay, Shu Shiang (2009) Predicting Employment Condition of TARC'S ICT Graduates Using Backpropagation Neural Network. Masters thesis, Universiti Utara Malaysia.

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Abstract

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.

Item Type: Thesis (Masters)
Supervisor : Mohamad Mohsin, Mohamad Farhan
Item ID: 2064
Uncontrolled Keywords: Classifications, Multi-Layer Perceptron, Backpropogation, Neural Network, Educational Data Mining (EDM), Employment Situation, Tunku Abdul Rahman College(TARC)
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions: College of Arts and Sciences (CAS)
Date Deposited: 15 Aug 2010 01:18
Last Modified: 24 Jul 2013 12:14
Department: College of Arts and Sciences
Name: Mohamad Mohsin, Mohamad Farhan
URI: https://etd.uum.edu.my/id/eprint/2064

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