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Robbani Punggawa Arcapada
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Computer Science & IT Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering

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RANCANG BANGUN MODEL PENGIDENTIFIKASI SUARA HURUF HIJAIYAH DENGAN METODE MEL FREQUENCY CEPSTRUM COEFFICIENT DAN CONVOLUTIONAL NEURAL NETWORK Robbani Punggawa Arcapada; Widyadi Setiawan; I Made Arsa Suyadnya
Jurnal SPEKTRUM Vol 8 No 4 (2021): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (711.068 KB) | DOI: 10.24843/SPEKTRUM.2021.v08.i04.p1

Abstract

Learning the Qur'an is a necessity for a Muslim, because the Qur'an acts as a guideand way of life. One thing that is learned in the Qur'an is how to pronounce Hijaiyah letters orMakharijul letters. In learning Makharijul Letters it takes an ustaz or accompanying teacher whois limited by distance and time. To overcome the limitations of distance and time, a learningapplication model is needed that can be accessed without the limitations of distance and thetime. This is studied aim to develop the Hijaiyah letter recognition model using the MelFrequency Cepstrum Coefficient (MFCC) and Convulational Neural Network (CNN) methods.Based validation results, the model built using the MFCC and CNN methods can identify theletters read with an accuracy of 49.1%. Then based of the test result with Confusion Matrix, thismodel have a precision value of 50%, recall is 53%, and F-Measure is 0.514.
Co-Authors I Made Arsa Suyadnya Widyadi Setiawan