Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam

This research project is about the handwriting analysis in revealing a personality for employee selection using the artificial neural network. The objectives of the research are to design a neural network model and to develop a neural network prototype that can be used by the employer in selecting a...

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Main Author:	Mohd Zam, Zuriana
Format:	Thesis
Language:	English
Published:	2006
Subjects:	Electronic computers. Computer science
Online Access:	http://ir.uitm.edu.my/id/eprint/1022/ http://ir.uitm.edu.my/id/eprint/1022/1/TB_ZURIANA%20MOHD%20ZAM%20CS%2006_5%20P01.pdf

id	uitm-1022
recordtype	eprints
spelling	uitm-10222018-10-22T02:56:36Z http://ir.uitm.edu.my/id/eprint/1022/ Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam Mohd Zam, Zuriana Electronic computers. Computer science This research project is about the handwriting analysis in revealing a personality for employee selection using the artificial neural network. The objectives of the research are to design a neural network model and to develop a neural network prototype that can be used by the employer in selecting and hire best applicant based in the size of the applicant handwriting that reveals the applicant personality. Two approaches that been used are distributed questionnaire among 100 respondent and using back-propagation model. This allowed researcher makes connection between handwriting analysis and neural network technique. 100 sample of handwriting has been collected from the questionnaire. From the handwriting sample, extraction feature has been done. The researcher extract an alphabet 'a' from the handwritings sample in order to represents the size of the handwriting and as the input for the back-propagation model. The network structure for the back-propagation model is 80 input nodes, 10 hidden nudes and I output node. This network structure has been tested with several number or learning rate and momentum in order to achieve more efficient network and as the result the best learning rate value and momentum value have been choose. The flexible and optimum value for stopping criteria is also being determined. At the end of completion project period, researcher found out that the result from the network model is accurate with the desired result and therefore, all objective in this research project have been achieved. 2006 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/1022/1/TB_ZURIANA%20MOHD%20ZAM%20CS%2006_5%20P01.pdf Mohd Zam, Zuriana (2006) Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam. Degree thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Electronic computers. Computer science
spellingShingle	Electronic computers. Computer science Mohd Zam, Zuriana Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam
description	This research project is about the handwriting analysis in revealing a personality for employee selection using the artificial neural network. The objectives of the research are to design a neural network model and to develop a neural network prototype that can be used by the employer in selecting and hire best applicant based in the size of the applicant handwriting that reveals the applicant personality. Two approaches that been used are distributed questionnaire among 100 respondent and using back-propagation model. This allowed researcher makes connection between handwriting analysis and neural network technique. 100 sample of handwriting has been collected from the questionnaire. From the handwriting sample, extraction feature has been done. The researcher extract an alphabet 'a' from the handwritings sample in order to represents the size of the handwriting and as the input for the back-propagation model. The network structure for the back-propagation model is 80 input nodes, 10 hidden nudes and I output node. This network structure has been tested with several number or learning rate and momentum in order to achieve more efficient network and as the result the best learning rate value and momentum value have been choose. The flexible and optimum value for stopping criteria is also being determined. At the end of completion project period, researcher found out that the result from the network model is accurate with the desired result and therefore, all objective in this research project have been achieved.
format	Thesis
author	Mohd Zam, Zuriana
author_facet	Mohd Zam, Zuriana
author_sort	Mohd Zam, Zuriana
title	Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam
title_short	Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam
title_full	Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam
title_fullStr	Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam
title_full_unstemmed	Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam
title_sort	handwriting analysis for employee selection using neural network / zuriana mohd zam
publishDate	2006
url	http://ir.uitm.edu.my/id/eprint/1022/ http://ir.uitm.edu.my/id/eprint/1022/1/TB_ZURIANA%20MOHD%20ZAM%20CS%2006_5%20P01.pdf
first_indexed	2023-09-18T22:45:21Z
last_indexed	2023-09-18T22:45:21Z
_version_	1777417187482402816

Handwriting analysis for employee selection using neural network / Zuriana Mohd Zam

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