Pengenalan Makhraj Huruf Dalam Bacaan Al-Quran Menggunakan Convolution Neural Network (CNN)

Ismail, Ismail (2021) Pengenalan Makhraj Huruf Dalam Bacaan Al-Quran Menggunakan Convolution Neural Network (CNN). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dalam pembelajaran Al-Quran, elemen yang paling mendasar untuk diketahui ialah huruf-huruf Al-Quran itu sendiri. Di mana setiap huruf memiliki tempat keluarnya masing-masing saat dilafalkan yang disebut makhraj huruf. Namun dalam penerapannya, orang Indonesia masih kesulitan dalam melafalkan makhraj huruf dengan tepat dikarenakan adanya perbedaan bahasa dalam sehari-hari. Kurangnya fasilitas penunjang yang mampu beradaptasi dengan zaman sekarang juga menjadi hambatan yang mendasar. Sehingga masih diperlukan proses belajar secara manual dari para ahli dalam mempelajari makhraj. Dari permasalahan tersebut kami mengusulkan penelitian yang dapat membantu dalam pengenalan makhraj huruf sebagai penunjang umat Islam dalam belajar Al-Quran. Metode deep learning dipakai dalam pengaplikasian pembelajaran ini yaitu CNN yang akan mengenali sinyal audio yang telah diubah menjadi bentuk spectrogram. Dari penelitian ini diharapkan umat Islam lebih mudah mempelajari dan mengetahui makhraj huruf dari hasil pengenalan audio tersebut.
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In the study of the Quran, the most basic element to know is the letters of the Quran itself. Where each letter has its own exit when pronounced called makhraj letter. But in its application, Indonesians still have dificulty in pronouding makhraj letters correctly due to language differences in daily life. The lack of supporting facilities that are able to adapt to the present day is also a fundamental obstacle. So it is still necessary to learn manually from experts in learning makhraj of the Quran. From the problem we propose research that can help in makhraj letters recognition as a support for Muslims in learning the Quran. The deep learning method used in the application of this learning is CNN that will recognize audio signals that previously have been converted into a form of spectrogram. From this project, it is expected that Muslims are easier to learn and know the makhraj letters from the results of the audio recognition.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	CNN, Deep Learning, Makhraj Huruf, Speech Recognition CNN, Deep Learning, Makhraj Letters, Speech Recognition
Subjects:	B Philosophy. Psychology. Religion > BP Islam. Bahaism. Theosophy, etc L Education > L Education (General) T Technology > T Technology (General) > T57.5 Data Processing T Technology > T Technology (General) > T58.62 Decision support systems
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Ismail Ismail
Date Deposited:	02 Sep 2021 01:56
Last Modified:	02 Sep 2021 01:57
URI:	http://repository.its.ac.id/id/eprint/91309

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