Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin

Al-Quran is, the most important book in Muslims' life as it gives knowledge in many areas for the use of their daily life. Therefore, it is needed to be read properly so the meaning of the reading is correct. In addition, learning tajwid is a must in order to improve better reading, The main pu...

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Main Author:	Kamaruddin, Zunnajah
Format:	Thesis
Language:	English
Published:	2005
Subjects:	Electronic Computers Computer Science
Online Access:	https://ir.uitm.edu.my/id/eprint/1019/1/TB_ZUNNAJAH%20KAMARUDDIN%20CS%2005_5%20P01.pdf
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id	my-uitm-ir.1019
record_format	uketd_dc
spelling	my-uitm-ir.10192018-10-19T08:17:58Z Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin 2005 Kamaruddin, Zunnajah Electronic Computers. Computer Science Al-Quran is, the most important book in Muslims' life as it gives knowledge in many areas for the use of their daily life. Therefore, it is needed to be read properly so the meaning of the reading is correct. In addition, learning tajwid is a must in order to improve better reading, The main purpose of the project is to train artificial neural network (ANN) data to identify the tajwid. It is also trying to classify the tajwid based on letters and signs by defining their shape and location. Images are used as samples to be processed for the used of classification. In order to have a system which has an ability to learn, back-propagation learning algorithm is used. The results of the experiments done shows that the accurate results produced by the prototype is 20%. From the accurate results, 60% results are Mad Asli and 40% is lkhfa' Haqiqi. From the identification of Mad Asli, 40% accurate results are from the letter alif ( l ), 40% is from the letter wau ( و ) and 20% is from the letter ya ( ي ). As conclusion, it is hope that this project can be the starting point for a better learning of tajwid. 2005 Thesis https://ir.uitm.edu.my/id/eprint/1019/ https://ir.uitm.edu.my/id/eprint/1019/1/TB_ZUNNAJAH%20KAMARUDDIN%20CS%2005_5%20P01.pdf text en public degree Universiti Teknologi MARA Faculty of Information Technology and Quantitative Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Electronic Computers Computer Science
spellingShingle	Electronic Computers Computer Science Kamaruddin, Zunnajah Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin
description	Al-Quran is, the most important book in Muslims' life as it gives knowledge in many areas for the use of their daily life. Therefore, it is needed to be read properly so the meaning of the reading is correct. In addition, learning tajwid is a must in order to improve better reading, The main purpose of the project is to train artificial neural network (ANN) data to identify the tajwid. It is also trying to classify the tajwid based on letters and signs by defining their shape and location. Images are used as samples to be processed for the used of classification. In order to have a system which has an ability to learn, back-propagation learning algorithm is used. The results of the experiments done shows that the accurate results produced by the prototype is 20%. From the accurate results, 60% results are Mad Asli and 40% is lkhfa' Haqiqi. From the identification of Mad Asli, 40% accurate results are from the letter alif ( l ), 40% is from the letter wau ( و ) and 20% is from the letter ya ( ي ). As conclusion, it is hope that this project can be the starting point for a better learning of tajwid.
format	Thesis
qualification_level	Bachelor degree
author	Kamaruddin, Zunnajah
author_facet	Kamaruddin, Zunnajah
author_sort	Kamaruddin, Zunnajah
title	Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin
title_short	Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin
title_full	Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin
title_fullStr	Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin
title_full_unstemmed	Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin
title_sort	identification of tajwid using artificial neural networks / zunnajah kamaruddin
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Information Technology and Quantitative Sciences
publishDate	2005
url	https://ir.uitm.edu.my/id/eprint/1019/1/TB_ZUNNAJAH%20KAMARUDDIN%20CS%2005_5%20P01.pdf
_version_	1783732958794874880

Identification of tajwid using artificial neural networks / Zunnajah Kamaruddin

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