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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Communications in Science and Technology IJID (International Journal on Informatics for Development) Automata Journal of Internet and Software Engineering Aceh International Journal of Science and Technology
Rajagede, Rian Adam
Universitas Islam Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering

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Al-Quran recitation verification for memorization test using Siamese LSTM network Rajagede, Rian Adam; Hastuti, Rochana Prih
Communications in Science and Technology Vol 6 No 1 (2021)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.6.1.2021.344

Abstract

In the process of verifying Al-Quran memorization, a person is usually asked to recite a verse without looking at the text. This process is generally done together with a partner to verify the reading. This paper proposes a model using Siamese LSTM Network to help users check their Al-Quran memorization alone. Siamese LSTM network will verify the recitation by matching the input with existing data for a read verse. This study evaluates two Siamese LSTM architectures, the Manhattan LSTM and the Siamese-Classifier. The Manhattan LSTM outputs a single numerical value that represents the similarity, while the Siamese-Classifier uses a binary classification approach. In this study, we compare Mel-Frequency Cepstral Coefficient (MFCC), Mel-Frequency Spectral Coefficient (MFSC), and delta features against model performance. We use the public dataset from Every Ayah website and provide the usage information for future comparison. Our best model, using MFCC with delta and Manhattan LSTM, produces an F1-score of 77.35%
Quran Memorization Technologies and Methods: Literature Review Haryono, Kholid; Rajagede, Rian Adam; Negara, Muhammad Ulil Albab Surya
IJID (International Journal on Informatics for Development) Vol. 11 No. 1 (2022): IJID June
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2022.3746

Abstract

The application of the Qur'an for the memorizers in adding and maintaining their memorization continues to grow in number. No less than 200 digital Qur'an applications are available on mobile application providers. In addition, publications on the topic of the digital Qur'an in the last ten years have also increased. Through these applications and publications, it is an opportunity to find patterns and knowledge about current topics and features. Through this knowledge, it is hoped that it can be a recommendation for a better form of digital Al-Qur'an application system, especially providing features that affect increasing the ease and quality of memorizing the Qur'an. This paper aims to explore the application of the Qur'an specifically for memorizing and papers on the topic to provide these recommendations. The method used to get the paper using PRISMA. While the applications being reviewed are taken from the AppStore. As a result, 31 papers were reviewed and 12 main applications regarding the Qur'an for memorization were obtained. Through the answers to each research question, it can be used by subsequent researchers as well as by system developers in developing Al-Qur'an products for better memorization of tense.
Co-Authors Alfian Try Putranto Dimas Ariyoga Farah Nurul Izza Bintoro Farid Amin Ridwanto Fatih Assidhiqi Galang Prihadi Mahardika Hastuti, Rochana Prih Javier Farran Ath-Thaariq Kholid Haryono Miftakhurrokhmat Muhammad Ichlasul Amal Yulianto Muhammad Rifqi Fatchurrahman Putra Danar Muhammad Sauqi Khatami Negara, Muhammad Ulil Albab Surya Palimbani, Muhammad Adin Ridho Rahmadi Ridho Rahmadi Rizky Ainul Wildan S Yuanda Hanif Hisyam