Cover Image

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...

Full description

Saved in:
Bibliographic Details
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/1022/1/TB_ZURIANA%20MOHD%20ZAM%20CS%2006_5%20P01.pdf
http://ir.uitm.edu.my/id/eprint/1022/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uitm.ir.1022
record_format eprints
spelling my.uitm.ir.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.
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
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/1022/1/TB_ZURIANA%20MOHD%20ZAM%20CS%2006_5%20P01.pdf
http://ir.uitm.edu.my/id/eprint/1022/
_version_ 1685648106277830656
score 13.211869

Similar Items