Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih

Artificial Neural Network is one of the branches of Artificial Intelligence which is utilized for the purpose of classification and prediction based on data in hand. The purpose of the study is to develop a web-based self assessment information system that can be used to obtain a model for predicti...

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Main Author:	Hashim, Asman
Format:	Thesis
Language:	eng eng
Published:	2001
Subjects:	QA76 Computer software
Online Access:	https://etd.uum.edu.my/286/1/Hashim_bin_Asman%2C_2001.pdf https://etd.uum.edu.my/286/2/1.Hashim_bin_Asman%2C_2001.pdf
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id	my-uum-etd.286
record_format	uketd_dc
spelling	my-uum-etd.2862013-07-24T12:06:30Z Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih 2001 Hashim, Asman Sekolah Siswazah Sekolah Siswazah QA76 Computer software Artificial Neural Network is one of the branches of Artificial Intelligence which is utilized for the purpose of classification and prediction based on data in hand. The purpose of the study is to develop a web-based self assessment information system that can be used to obtain a model for prediction of information technology competency among teacher trainees in teaching institutes. The developed system is known as "NeuroCite". The system functions as a research instrument generating questionnaires as well as performing rubric assessment in information technology competency online. The data entered online using web as a medium and then executing back propagation simulation to obtain the desired neural network model, and to predict information technology competency based on the model obtained. The data was collected from various field of studies among teacher trainees in teacher training institutes. Data containing eleven predictive variables was used to train and test neural network model. The research procedures chosen were the multi-layered perceptron with back propagation algorithmic learning. The research findings show that the most suitable predictive model comprises of eleven nodes in input-layer; five nodes in hidden-layer and one node in output-layer. The performance of the selected model was reassessed and was found to be 96.77% accuracy in its prediction. The research confirmed that artificial intelligence is capable in generating instruments for measurement and educational evaluation. The developed system can be used as a tool to assist decision making in education. 2001 Thesis https://etd.uum.edu.my/286/ https://etd.uum.edu.my/286/1/Hashim_bin_Asman%2C_2001.pdf application/pdf eng validuser https://etd.uum.edu.my/286/2/1.Hashim_bin_Asman%2C_2001.pdf application/pdf eng public masters masters Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	QA76 Computer software
spellingShingle	QA76 Computer software Hashim, Asman Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
description	Artificial Neural Network is one of the branches of Artificial Intelligence which is utilized for the purpose of classification and prediction based on data in hand. The purpose of the study is to develop a web-based self assessment information system that can be used to obtain a model for prediction of information technology competency among teacher trainees in teaching institutes. The developed system is known as "NeuroCite". The system functions as a research instrument generating questionnaires as well as performing rubric assessment in information technology competency online. The data entered online using web as a medium and then executing back propagation simulation to obtain the desired neural network model, and to predict information technology competency based on the model obtained. The data was collected from various field of studies among teacher trainees in teacher training institutes. Data containing eleven predictive variables was used to train and test neural network model. The research procedures chosen were the multi-layered perceptron with back propagation algorithmic learning. The research findings show that the most suitable predictive model comprises of eleven nodes in input-layer; five nodes in hidden-layer and one node in output-layer. The performance of the selected model was reassessed and was found to be 96.77% accuracy in its prediction. The research confirmed that artificial intelligence is capable in generating instruments for measurement and educational evaluation. The developed system can be used as a tool to assist decision making in education.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Hashim, Asman
author_facet	Hashim, Asman
author_sort	Hashim, Asman
title	Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
title_short	Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
title_full	Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
title_fullStr	Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
title_full_unstemmed	Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
title_sort	permodelan rangkaian neural buatan untuk penilaian kendiri teknologi maklumat guru pelatih
granting_institution	Universiti Utara Malaysia
granting_department	Sekolah Siswazah
publishDate	2001
url	https://etd.uum.edu.my/286/1/Hashim_bin_Asman%2C_2001.pdf https://etd.uum.edu.my/286/2/1.Hashim_bin_Asman%2C_2001.pdf
_version_	1747826879649284096

Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih

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