Rancang Bangun Sistem Elektronik untuk Menyimak dan Mengetes Hafalan Al-Quran Berbasis Arabic Speech to Text dan Metode Levenshtein Distance

Muayyad, Ahmad Saad (2021) Rancang Bangun Sistem Elektronik untuk Menyimak dan Mengetes Hafalan Al-Quran Berbasis Arabic Speech to Text dan Metode Levenshtein Distance. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Al-Quran merupakan kitab suci agama Islam yang secara luas dibaca, dihafalkan, dipelajari, dan diajarkan oleh para pemeluknya. Indonesia merupakan negara dengan pemeluk agama Islam terbanyak di dunia, maka jumlah institusi dimana Al-Quran itu dihafal dan diajarkan juga sangat banyak. Berdasarkan hal tersebut, pada Tugas Akhir ini telah dibuat sebuah sistem untuk menyimak dan mengetes hafalan Al-Quran. Sistem ini menggunakan Arabic Speech-to-Text untuk mengubah input suara menjadi teks bahasa Arab, yang kemudian dibandingkan dengan data teks Al-Quran menggunakan metode Levenshtein Distance. Bila nilai perbandingan antara input dan data teks yang tersimpan melewati batas dan logika yang sudah didesain, maka sistem akan memberikan peringatan melalui output berupa suara dan tampilan visual. Sistem yang dirancang diimplementasikan menggunakan Raspberry Pi 3B+ yang dilengkapi dengan microphone, buzzer, dan Touch Screen Display. Sistem elektronik ini menggunakan data Al-Quran yang diinput secara manual dan data Al-Quran dari PyQuran sebagai rujukan. Dihasilkan persentase error sebesar 0,45% untuk penggunaan data manual dan 3,52% untuk penggunaan data PyQuran dalam pengujian 3 halaman di juz pertama Al-Quran. Latency rata-rata yang dihasilkan untuk satu kata yang diproses dengan kecepatan internet 10 Mbps adalah 0,1292 s. Kedepannya, kualitas sistem koreksi dapat ditambahkan terutama untuk PyQuran agar sistem elektronik ini dapat digunakan untuk 30 juz Al-Quran secara lengkap sehingga dapat membantu para penghafal Al-Quran ===================================================================================================== Al-Quran is Islam’s Holy Book that widely recited, memorized, studied, and taught by its followers. Indonesia is a country with the largest number of Muslim, in which many intitutions where Al-Quran are memorized and taught. Based on that, in this Final Project, an electronic system for correcting and testing Al-Quran memorization was designed. This system uses Arabic Speech-to-Text to convert audio input to Arabic text that was compared to Al-Quran text data with Levenshtein Distance Method. If the comparison value between audio input and Al-Quran text data exceeds the limit and logic that has been designed, the system will give a warning by audio and visual output. This system is designed using Raspberry Pi 3B+ equipped with microphone, buzzer, and Touch Screen Display. This electronic system uses Al-Quran data that manually input and PyQuran data as its reference. An error percentage of 0,45% was obtained using Al-Quran manual data and 3,52% was obtained using PyQuran data for 3 pages from the first juz testing. Average latency that was obtained for each word processing for 10 Mbps internet speed is 0,1292 s. In the future research, the quality of correction system can be upgraded especially for PyQuran so this system can be used for 30 juz perfectly and will be a huge benefit for Al-Quran memorizer.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Quran Memorization, Arabic Speech-to-Text, Levenshtein Distance, and Raspberry Pi, Hafalan Al-Quran, Arabic Speech-to-Text, Levenshtein Distance, dan Raspberry Pi
Subjects: B Philosophy. Psychology. Religion > BP Islam. Bahaism. Theosophy, etc
T Technology > T Technology (General) > T57.8 Nonlinear programming. Support vector machine. Wavelets. Hidden Markov models.
T Technology > TK Electrical engineering. Electronics Nuclear engineering
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5102.9 Signal processing.
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7871.674 Detectors. Sensors
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7878 Electronic instruments
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7895.S65 Speech recognition systems
Divisions: Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User: Ahmad Saad Muayyad
Date Deposited: 16 Aug 2021 11:21
Last Modified: 16 Aug 2021 11:21
URI: https://repository.its.ac.id/id/eprint/87298

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