PENGENALAN MAKHRAJ HURUF HIJAIYAH MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK

HIDAYATULLAH, M ARIF IQBAL and Yusliani, Novi and Miraswan, Kanda Januar (2020) PENGENALAN MAKHRAJ HURUF HIJAIYAH MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK. Undergraduate thesis, Sriwijaya University.

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Abstract

Almost all Muslims in the world know how to read the Koran, but not all Muslims can read the Koran with the correct makhraj. One solution to overcome this problem is to use the Speech Recognition application. Speech Recognition is a process where the computer will pick up sound signals and convert them into words that are understood by the computer. This study aims to develop software for introducing makhraj hijaiyah letters. The method used in this study was 500, consisting of 400 test data and 100 training data. Convolutional Neural Network. The data used amounted to the results of the system shows that the CNN method produces an optimal accuracy of 76.80% with a combination of learning rate values of 0.005 and a filter size of 3x3.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Speech Recognition, convolutional neural network, makhraj
Subjects:	P Language and Literature > P Philology. Linguistics > P98-98.5 Computational linguistics. Natural language processing
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 7449 not found.
Date Deposited:	18 Aug 2020 02:51
Last Modified:	18 Aug 2020 02:51
URI:	http://repository.unsri.ac.id/id/eprint/33250

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