Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi

The expertise of a workforce is closely related to the level of competency and other factors such as knowledge, experiences, skills, attitudes and et cetera. The problems of competency management and the methods to determine competency level of a workforce always engender an issue. As for example, w...

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Main Author:	Taib, Zakaria
Format:	Thesis
Language:	English
Published:	2006
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/4078/1/ZakariaTaibMFSKSM2006.pdf
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id	my-utm-ep.4078
record_format	uketd_dc
spelling	my-utm-ep.40782018-01-15T06:39:04Z Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi 2006-05 Taib, Zakaria QA75 Electronic computers. Computer science The expertise of a workforce is closely related to the level of competency and other factors such as knowledge, experiences, skills, attitudes and et cetera. The problems of competency management and the methods to determine competency level of a workforce always engender an issue. As for example, what is the best method or system to determine the weightage for each criterion in evaluating a certain level of competency? Among the method to solve the problem is to use neural network. But the accuracy of the network depends on the activation function used. Thus, this project aimed to compare the accuracy of several activation functions for classifying competency level of a workforce's expertise. The comparison of activation function in this study is done by using back propagation neural network and by calculating the percentage of the accuracy of the neural network as compared to the target data samples. This study reveals that the logarithmic-exponential activation function gives a better result as compared to the logistic activation function. The activation function is then used in developing a prototype module To Classify Expertise Level for Competency Management System using The Unified Software Development approach, which apply the techniques of Unified Modeling Language (UML). The prototype module has been used as an efficient and fairly method in term of getting weightage for each criterion in determining the competency level of a researcher's expertise at the Malaysian Institute for Nuclear Technology Research (MINT). 2006-05 Thesis http://eprints.utm.my/id/eprint/4078/ http://eprints.utm.my/id/eprint/4078/1/ZakariaTaibMFSKSM2006.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Taib, Zakaria Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi
description	The expertise of a workforce is closely related to the level of competency and other factors such as knowledge, experiences, skills, attitudes and et cetera. The problems of competency management and the methods to determine competency level of a workforce always engender an issue. As for example, what is the best method or system to determine the weightage for each criterion in evaluating a certain level of competency? Among the method to solve the problem is to use neural network. But the accuracy of the network depends on the activation function used. Thus, this project aimed to compare the accuracy of several activation functions for classifying competency level of a workforce's expertise. The comparison of activation function in this study is done by using back propagation neural network and by calculating the percentage of the accuracy of the neural network as compared to the target data samples. This study reveals that the logarithmic-exponential activation function gives a better result as compared to the logistic activation function. The activation function is then used in developing a prototype module To Classify Expertise Level for Competency Management System using The Unified Software Development approach, which apply the techniques of Unified Modeling Language (UML). The prototype module has been used as an efficient and fairly method in term of getting weightage for each criterion in determining the competency level of a researcher's expertise at the Malaysian Institute for Nuclear Technology Research (MINT).
format	Thesis
qualification_level	Master's degree
author	Taib, Zakaria
author_facet	Taib, Zakaria
author_sort	Taib, Zakaria
title	Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi
title_short	Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi
title_full	Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi
title_fullStr	Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi
title_full_unstemmed	Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi
title_sort	pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty Computer Science and Information System
publishDate	2006
url	http://eprints.utm.my/id/eprint/4078/1/ZakariaTaibMFSKSM2006.pdf
_version_	1747814495663685632

Pengkelasan kompetensi bidang kepakaran berasaskan rangkaian neural dalam sistem pengurusan kompetensi

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