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Aaz Muhammad Hafidz Azis
School Of Computing, Telkom University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Automatic Detection of Hijaiyah Letters Pronunciation using Convolutional Neural Network Algorithm Yana Aditia Gerhana; Aaz Muhammad Hafidz Azis; Diena Rauda Ramdania; Wildan Budiawan Dzulfikar; Aldy Rialdy Atmadja; Deden Suparman; Ayu Puji Rahayu
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.882

Abstract

Abstract— Speech recognition technology is used in learning to read letters in the Qur'an. This study aims to implement the CNN algorithm in recognizing the results of introducing the pronunciation of the hijaiyah letters. The pronunciation sound is extracted using the Mel-frequency cepstral coefficients (MFCC) model and then classified using a deep learning model with the CNN algorithm. This system was developed using the CRISP-DM model. Based on the results of testing 616 voice data of 28 hijaiyah letters, the best value was obtained for accuracy of 62.45%, precision of 75%, recall of 50% and f1-score of 58%.
XGBoost and Convolutional Neural Network Classification Models on Pronunciation of Hijaiyah Letters According to Sanad Aaz Muhammad Hafidz Azis; Dessi Puji Lestari
JOIN (Jurnal Online Informatika) Vol 8 No 2 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i2.1081

Abstract

According to Sanad, the pronunciation of Hijaiyah letters can serve as a benchmark for correct or valid reading based on the makhraj and properties of the letters. However, the limited number of Qur'anic Sanad teachers remains one of the obstacles to learning the Qur'an. This study aims to identify the most practical combination of classification models in constructing a voice recognition system that facilitates learning without requiring direct interaction with a teacher. The methods employed include the XGBoost algorithm and CNN. As a result, out of the 12 letter trait labels, the CNN model was utilized for 10 of them, specifically for traits S1, S2, S4, S5, T1, T2, T3, T4, T5, and T6, on trait labels S3 and T7 applying the XGBoost model. Furthermore, the inclusion of additional data yielded performance results for each property, with an average accuracy of 78.14% for property S (letters with opposing properties), 70.69% for property T (letters without opposing properties), and an overall average of 73.79% per letter.
Automatic Detection of Hijaiyah Letters Pronunciation using Convolutional Neural Network Algorithm Yana Aditia Gerhana; Aaz Muhammad Hafidz Azis; Diena Rauda Ramdania; Wildan Budiawan Dzulfikar; Aldy Rialdy Atmadja; Deden Suparman; Ayu Puji Rahayu
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.882

Abstract

Abstract— Speech recognition technology is used in learning to read letters in the Qur'an. This study aims to implement the CNN algorithm in recognizing the results of introducing the pronunciation of the hijaiyah letters. The pronunciation sound is extracted using the Mel-frequency cepstral coefficients (MFCC) model and then classified using a deep learning model with the CNN algorithm. This system was developed using the CRISP-DM model. Based on the results of testing 616 voice data of 28 hijaiyah letters, the best value was obtained for accuracy of 62.45%, precision of 75%, recall of 50% and f1-score of 58%.
XGBoost and Convolutional Neural Network Classification Models on Pronunciation of Hijaiyah Letters According to Sanad Aaz Muhammad Hafidz Azis; Dessi Puji Lestari
JOIN (Jurnal Online Informatika) Vol 8 No 2 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i2.1081

Abstract

According to Sanad, the pronunciation of Hijaiyah letters can serve as a benchmark for correct or valid reading based on the makhraj and properties of the letters. However, the limited number of Qur'anic Sanad teachers remains one of the obstacles to learning the Qur'an. This study aims to identify the most practical combination of classification models in constructing a voice recognition system that facilitates learning without requiring direct interaction with a teacher. The methods employed include the XGBoost algorithm and CNN. As a result, out of the 12 letter trait labels, the CNN model was utilized for 10 of them, specifically for traits S1, S2, S4, S5, T1, T2, T3, T4, T5, and T6, on trait labels S3 and T7 applying the XGBoost model. Furthermore, the inclusion of additional data yielded performance results for each property, with an average accuracy of 78.14% for property S (letters with opposing properties), 70.69% for property T (letters without opposing properties), and an overall average of 73.79% per letter.
Gamifikasi Sistem Pembelajaran Matematika Persamaan Linear Satu Variabel Untuk Siswa SMP Duke Susila , Habibie; Widowati, Sri; Hafidz Azis, Aaz Muhammad
eProceedings of Engineering Vol. 12 No. 1 (2025): Februari 2025
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak - Mayoritas sekolah di dunia mengajarkan matematika sebagai salah satu mata pelajaran dasar yang harus dikuasai semua siswa. Tetapi banyak siswa SMP masih tidak menyukai pelajaran matematika dikarenakan pelajaran matematika sulit untuk dipahami dan kurangnya motivasi dari siswa SMP untuk mempelajarinya. Video game adalah permainan berbentuk digital yang berfungsi untuk menghibur. Hampir semua orang pernah bermain game, termasuk siswa SMP. Gamifikasi adalah fenomena memasukkan elemen dari game ke dalam kehidupan sehari-hari. Salah satu implementasi gamifikasi adalah gamifikasi untuk edukasi. Dalam Tugas Akhir ini penelitian dilakukan terhadap siswa SMP dalam menggunakan sistem gamifikasi untuk mata pelajaran aljabar, khususnya persamaan satu variabel. Hasil penelitian mengungkapkan bahwa gamifikasi sistem pembelajaran matematika aljabar persamaan liner satu variabel dapat meningkatkan pemahaman siswa SMP dalam mempelajari matematika aljabar. Kata kunci - siswa SMP, gamifikasi, persamaan satu linear variabel, sistem pembelajaran, gambar
Co-Authors Aldy Rialdy Atmadja Ayu Puji Rahayu Deden Suparman, Deden Dessi Puji Lestari Diena Rauda Ramdania Duke Susila , Habibie Sri Widowati Wildan Budiawan Zulfikar Yana Aditia Gerhana