DETEKSI HUKUM TAJWID ALIF LAM SYAMSIYAH DAN QOMARIYAH PADA CITRA AYAT AL-QUR’AN MUSHAF UTSMANI MENGGUNAKAN MODEL YOLOV11S
Abstract
The ability to read the Qur'an in accordance with the rules of tajwid is a fundamental aspect of Qur'anic learning, particularly in recognizing the rules of Alif Lam Shamsiyyah and Alif Lam Qamariyyah. However, many students still experience difficulties in accurately identifying these two tajwid rules due to the limited availability of interactive learning media and the lack of technology-based automatic detection systems. Recent advances in artificial intelligence, particularly in the fields of computer vision and object detection, offer promising opportunities to support tajwid learning in a more effective and real-time manner. This study aims to develop an automatic detection system for the tajwid rules of Alif Lam Shamsiyyah and Alif Lam Qamariyyah in images of Qur'anic verses from the Uthmani Mushaf using the YOLOv11s model. The research methodology follows the CRISP-DM framework, consisting of six stages: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The dataset comprises 1,400 images collected from a combination of the Indonesian Ministry of Religious Affairs' digital Mushaf and photographs of printed Mushaf copies. The images were subsequently annotated and augmented using Roboflow. The model was trained using Python on the Google Colab platform with an input image size of 640 × 640 pixels and the Adam optimizer. The evaluation results demonstrate that the YOLOv11s model achieved excellent detection performance, with a precision of 98.5%, a recall of 99.0%, and an mAP@50 of 98.9%. The best-performing model was then deployed as a web-based application using the Flask framework to enable automatic and real-time tajwid detection. Based on the findings, the YOLOv11s model is proven to be an effective solution for supporting interactive, adaptive, and accurate computer vision-based tajwid learning
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E. Muslimin, M. Sanusi, A. Info, And A. History, “Penerapan Metode Karimah Dalam Peningkatan Kualitas Bacaan Al Qur ’ An,” Vol. 7, Pp. 8303–8311, 2024.
T. Pendidikan, A. T. P. Q. Ibadusholihin, And B. Pulung, “Penerapan Pembelajaran Ilmu Tajwid Dalam Meningkatkan Ketepatan Bacaan Al- Qur ’ An Pada Santri,” Pp. 830–841, 2025.
K. Latambaga And K. Koaka, “Issn 2599-1248 ©Production And Hosting By Usimar Kolaka,” No. 7, Pp. 1–16, 2024.
S. N. Amartama, A. N. Hidayah, P. K. Sari, And R. A. Ramadhani, “Implementasi Convolutional Neural Network ( Cnn ) Dalam Pengenalan Pola Penulisan Tangan,” Vol. 3, Pp. 133–138, 2024.
P. Studi And S. Komputer, “Analisis Big Data Dan Artificial Intelligence ( Ai ): Dalam Industri Khususnya Prediksi Penyakit Jantung Dengan Phyton,” Vol. 30, No. 1, Pp. 76–86, 2024, Doi: 10.36309/Goi.V30i1.262.
J. Nurhakiki, “Studi Kepustakaan : Pengenalan 4 Algoritma Pada Pembelajaran Deep Learning Beserta Implikasinya,” No. 1, 2024.
C. Setianingsih, M. Kalista, B. F. Aina, And M. Syarif, “Workshop Development Object Detection System Robotics With Arei ( Asosiasi Robot Edukasi Indonesia ),” Vol. 6, Pp. 1–6, 2023.
R. Sapkota, M. F. Rizwan, And Q. Chetan, “Yolo Advances To Its Genesis : A Decadal And Comprehensive Review Of The You Only Look Once ( Yolo ) Series,” 2025.
Nur Aisyyah, “Metode Pembelajaran Baca Tulis Al-Qur’an Untuk Anak Berkebutuhan Khusus Di Sdlb Swadaya Kendal, Laporan Penelitian Individual,” Pp. 30–31, 2015.
Z. T. D. Rofi’i, M. A., Alfiani, N., & Shofianah, “Perbedaan Rasm Uthmāni Dan Kaidah Imlā’ Dalam Penulisan Al-Qur’an Serta Implikasinya Terhadap Penafsiran.,” J. Stud. Al-Qur’an, 10(2), 2024, Doi: 145–160.
A. S. Asifaq, M., Danianti, D., Wijaya, D. P., & Yazid, “Penerapan Metode Yolov11 Dalam Mendeteksi Gestur Tangan Alfabet Bisindo Berbasis Website,” J. Mhs. Tek. Inform., 2026, Doi: 215–224.
S. N. Khofifah And A. P. Astutik, “Implementasi Pembelajaran Ilmu Tajwid Dalam Meningkatkan Kemampuan Membaca Al- Qur ’ An [ Implementation Of Tajwid Learning In Improving The Ability To Read The Qur ’ An ],” Pp. 1–7.
M. K. Itsna Safira Khairunnisa And M. Khairusani, “Teori T A ’ Dib Syed Muhammad Naquib Al-Attas Dan Relevansinya Dalam Pendidikan Karakter Islam Kontemporer,” J. Pendidik. Ris. Dan Konseptual, Vol. 4, No. 4, Pp. 566–576, 2020.
H. K. Saraji, L., Miswar, A., & Daming, “Unifikasi Mushaf Usmāni,” J. Kolaboratif Sains, Vol. 8 (3), 2025, Doi: 412–421.
S. W. Tarigan And H. R. Setiawan, “Implementasi Program Tahsin Dalam Meningkatkan Kualitas Membaca Al- Qur ’ An Di Primary Satit Phatnawitya School Yala Thailand,” Vol. 8, No. April, Pp. 4443–4449, 2025.
J. Subur, M. Taufiqurrohman, P. Studi, T. Elektro, U. H. Tuah, And J. Timur, “Pemanfaatan Teknologi Computer Vision Untuk Deteksi Ukuran Ikan Bandeng Dalam Membantu Proses Sortir Ikan,” Vol. 7, No. 01, Pp. 52–60, 2024.
D. H. Naufal Dan R. Rahmadewi, “Pengelolaan Citra Digital (Perbandingan Studi Kasus Antara Klasifikasi Warna Menggunakan Pengolahan Model Warna Hsv Dan Penerapan Metode Konvolusi Dalam Pengolahan Citra Digital),” J. Ilm. Wahana Pendidik., Pp. 168–177, 2024.
Dan R. D. V. Feriska, A. Reni, “Penilaian Kesegaran Ikan Dengan Metode K-Nearest Neighbor Dan Pengolahan Citra Digital,” J. Mhs. Tek. Inform., Vol. 8, No, 2024.
M. R. Alfarizi And M. Z. Al-Farish, “Penggunaan Python Sebagai Bahasa Pemrograman Untuk Machine Learning Dan Deep Learning,” Vol. 2, Pp. 1–6, 2023.
N. Hardi And J. Sundari, “Pengenalan Telapak Tangan Menggunakan Convolutionall Neural Network ( Cnn ),” Vol. 4, No. 1, Pp. 0–5, 2022.
A. Nuraeni, F., & Pambudi, “Implementasi Algoritma Convolutional Neural Network (Cnn) Untuk Pengenalan Bacaan Tajwid Berdasarkan Gambar Tulisan Dalam Al-Qur’an.,” Jati (Jurnal Mhs. Tek. Inform., Vol. 8 (5), 2024, Doi: 5451–5458. Https://Doi.Org/10.36040/Jati.V8i5.10867.
R. M. Yusup Et Al., “Pendeteksian Objek Menggunakan Opencv Dan Metode Yolov4-Tiny Untuk Membantu Tunanetra,” Vol. 1, No. 2, Pp. 59–68, 2024.
Yodhi Ramadhani, “Wawancara,” 2025.
F. Padilah, D., Pambudi, A., & Az-Zahra, “Analisis Prediksi Tajwid Nun Mati Pada Ayat Al-Qur’an Dengan Metode Yolov8 (You Only Look Once).,” Jati (Jurnal Mhs. Tek. Inform., Vol. 8 (5), 2024, Doi: 6033–6040. Https://Doi.Org/10.36040/Jati.V8i5.11055.
Dkk Kindarya, F., “Penerapan Aplikasi Klasifikasi Hukum Tajwid Menggunakan Image Processing.,” El-Mujtama J. Pengabdi. Masy., Vol. 4 (2), 2024, Doi: 1097–1105.
D. W. Fu’adi, M., Setiawan, A. B., & Widodo, “Deteksi Hukum Tajwid Nun Mati Pada Ayat Al-Qur’an Menggunakan Deep Learning Berbasis Computer Vision. Prosiding Seminar Nasional Informatika Dan Sistem Informasi.,” 2025.
Laraswati Ariadne Anwar, “No Titlentoleransi Membayangi Dunia Pendidikan,” In Artikel, Kompas.Com, 2020. [Online]. Available: Https://Www.Kompas.Id/Baca/Dikbud/2020/01/02/Intoleransi-Membayangi-Dunia-Pendidikan
J. Penerapan, T. Informasi, B. Perhiasan, B. Flask, And D. A. N. Mongodb, “It-Explore,” Vol. 03, Pp. 162–176, 2024.
J. Fasilkom, “Augmentasi Data Pada Prasasti Logam Untuk Deteksi Aksara Kawi,” Vol. 14, No. 1, Pp. 234–241, 2024.
S. Octarina, F. M. Puspita, E. Yuliza, And G. Meeting, “Jurnal Pepadu Jurnal Pepadu,” Vol. 6, No. 1, Pp. 56–66, 2025.
B. P. Rininda, N. Amelia, Y. Fitriyani, P. Negeri, T. Laut, And K. Selatan, “Pengaruh Pemahaman, Pengetahuan, Publikasi, Dan Peran Pemerintah Terhadap Minat Muzzaki Dalam Membayar Zakat,” Vol. 5, No. 1, Pp. 12–28, 2023.
A. Ritonga, “Studi Literatur Perbandingan Bahasa Pemrograman C ++ Dan Bahasa Pemrograman Python Pada Algoritma Pemrograman,” Vol. 3, No. 3, 2023.
Singgih Santoso, Spss Mengolah Data Statistik Secara Profesional Versi 7.5, Cet.3. Jakarta Elex Media Komputindo, 2021. [Online]. Available: Http://Kin.Perpusnas.Go.Id/Displaydata.Aspx?Pid=896&Pregioncode=Plksjog&Pclientid=145
Burhan Bungin, “Metodologi Penelitian Kualitatif: Aktualisasi Metodologi Ke Arah Ragam Varian Kontemporer,” 2011.
O. Adam, “Klasifikasi Hama Pada Daun Sawi Menggunakan Convolutional Neural Network ( Cnn ) Dengan Algoritma Xcaption Dan,” Vol. 6, No. 2, Pp. 359–370, 2024, Doi: 10.33650/Jeecom.V4i2.
I. Komputer, U. Indo, G. Mandiri, And K. Palembang, “Jurnal Sains , Nalar , Dan Aplikasi Teknologi Informasi,” Vol. 4, No. 2, Pp. 103–110, 2025, Doi: 10.20885/Snati.V4.I2.40414.
R. Wulanningrum, A. N. Handayani, And A. P. Wibawa, “Perbandingan Instance Segmentation Image Pada Yolo8 Comparison Of Image Segmentation Instance On Yolo8,” Vol. 11, No. 4, 2024, Doi: 10.25126/Jtiik.1148288.
G. Rininda, I. H. Santi, And S. Kirom, “Penerapan Svm Dalam Analisis Sentimen Pada Edlink,” Vol. 7, No. 5, Pp. 3335–3342, 2023.
Dkk Supriyadi, R., Irfan, M., Hapijar, R. D., “Engembangan Aplikasi Estimasi Kalori Makanan Berbasis Citra Dengan Pendekatan Deteksi Objek Menggunakan Yolo.,” J. Inform. Dan Tek. Elektro Terap., Vol. 14(1), Pp. 88–98., 2026.
N. Burhan Et Al., “Evaluasi Kinerja Model Yolov8 Untuk Deteksi Objek Kecil,” Vol. 03, No. 01, Pp. 1–8, 2026.
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