Penerapan Program Metode Ummi dalam Pembelajaran Membaca Al-Qur’an di SDIT Widya Cendekia (Pengenalan Lapangan Persekolahan di SDIT Widya Cendekia Kelompok 44)
DOI:
https://doi.org/10.47134/pgsd.v1i1.60Keywords:
ummi method, ummi program, learning the Qur'anAbstract
This study aims to determine the application of the Ummi method program in learning to read the Qur'an by SDIT Widya Cendekia students and the results obtained from the Ummi method. In carrying out this study the authors used qualitative research this study uses data collection techniques, namely observation, interviews, and documentation. After the data is obtained, the data is processed with several techniques, namely editing and data interpretation. Furthermore, all data were analyzed using qualitative descriptive techniques. The results of this study indicate that the application of the Ummi method program has good results so that it has a good effect on students at Sdit Widya Cendekia.
References
Abdelaal, H. M. (2019a). Classification of Hadith According to Its Content Based on Supervised Learning Algorithms. IEEE Access, 7, 152379–152387. https://doi.org/10.1109/ACCESS.2019.2948159 DOI: https://doi.org/10.1109/ACCESS.2019.2948159
Abdelaal, H. M. (2019b). Knowledge Discovery in the Hadith According to the Reliability and Memory of the Reporters Using Machine Learning Techniques. IEEE Access, 7, 157741–157755. https://doi.org/10.1109/ACCESS.2019.2944118 DOI: https://doi.org/10.1109/ACCESS.2019.2944118
Afrianto, I. (2019). Hijaiyah letter interactive learning for mild mental retardation children using Gillingham method and augmented reality. International Journal of Advanced Computer Science and Applications, 10(6), 334–341. https://doi.org/10.14569/ijacsa.2019.0100643 DOI: https://doi.org/10.14569/IJACSA.2019.0100643
Ahmed, M. A. (2020). Analysis of K-means, DBSCAN and OPTICS Cluster algorithms on Al-Quran verses. International Journal of Advanced Computer Science and Applications, 11(8), 248–254. https://doi.org/10.14569/IJACSA.2020.0110832 DOI: https://doi.org/10.14569/IJACSA.2020.0110832
Al-Ayyoub, M. (2018). Using deep learning for automatically determining correct application of basic quranic recitation rules. International Arab Journal of Information Technology, 15(3), 620–625.
Alkhateeb, J. H. (2020). A machine learning approach for recognizing the Holy Quran reciter. International Journal of Advanced Computer Science and Applications, 11(7), 268–271. https://doi.org/10.14569/IJACSA.2020.0110735 DOI: https://doi.org/10.14569/IJACSA.2020.0110735
Alkouatli, C. (2018). Pedagogies in becoming Muslim: Contemporary insights from Islamic traditions on teaching, learning, and developing. Religions, 9(11). https://doi.org/10.3390/rel9110367 DOI: https://doi.org/10.3390/rel9110367
Al-Thubaity, A. (2020). Arabic Diacritization Using Bidirectional Long Short-Term Memory Neural Networks with Conditional Random Fields. IEEE Access, 8, 154984–154996. https://doi.org/10.1109/ACCESS.2020.3018885 DOI: https://doi.org/10.1109/ACCESS.2020.3018885
Andriyandi, A. P. (2020). Augmented reality using features accelerated segment test for learning tajweed. Telkomnika (Telecommunication Computing Electronics and Control), 18(1), 208–216. https://doi.org/10.12928/TELKOMNIKA.V18I1.14750 DOI: https://doi.org/10.12928/telkomnika.v18i1.14750
Bahari, A. (2018). Sacred Text Motivation for General L2 Learners: a Mixed Methods Study. Journal of Academic Ethics, 16(4), 377–407. https://doi.org/10.1007/s10805-018-9316-3 DOI: https://doi.org/10.1007/s10805-018-9316-3
Berglund, J. (2019). Qur’anic education and non-confessional RE: an intercultural perspective. Intercultural Education, 30(3), 323–334. https://doi.org/10.1080/14675986.2018.1539305 DOI: https://doi.org/10.1080/14675986.2018.1539305
Borhani, M. (2020). Multi-label Log-Loss function using L-BFGS for document categorization. Engineering Applications of Artificial Intelligence, 91. https://doi.org/10.1016/j.engappai.2020.103623 DOI: https://doi.org/10.1016/j.engappai.2020.103623
Butt, H. (2021). Attention-Based CNN-RNN Arabic Text Recognition from Natural Scene Images. Forecasting, 3(3), 520–540. https://doi.org/10.3390/forecast3030033 DOI: https://doi.org/10.3390/forecast3030033
Choudhury, M. A. (2018). Tawhidi Islamic economics in reference to the methodology arising from the Qurʾān and the Sunnah. ISRA International Journal of Islamic Finance, 10(2), 263–276. https://doi.org/10.1108/IJIF-02-2018-0025 DOI: https://doi.org/10.1108/IJIF-02-2018-0025
Elmitwally, N. S. (2020). The multi-class classification for the first six surats of the Holy Quran. International Journal of Advanced Computer Science and Applications, 11(1), 327–332. https://doi.org/10.14569/ijacsa.2020.0110141 DOI: https://doi.org/10.14569/IJACSA.2020.0110141
Hamed, H. (2021). Deep learning approach for Translating Arabic Holy Quran into Italian language. 2021 International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2021, 193–199. https://doi.org/10.1109/MIUCC52538.2021.9447650 DOI: https://doi.org/10.1109/MIUCC52538.2021.9447650
Hanafi, Y. (2019). Student’s and instructor’s perception toward the effectiveness of E-BBQ enhances Al-Qur’an reading ability. International Journal of Instruction, 12(3), 51–68. https://doi.org/10.29333/iji.2019.1234a DOI: https://doi.org/10.29333/iji.2019.1234a
Hanafi, Y. (2020). Reinforcing public university student’s worship education by developing and implementing mobile-learning management system in the ADDIE instructional design model. International Journal of Interactive Mobile Technologies, 14(2), 215–241. https://doi.org/10.3991/ijim.v14i02.11380 DOI: https://doi.org/10.3991/ijim.v14i02.11380
Izzaty, A. M. K. (2018). A multi-label classification on topics of quranic verses in English translation using Tree Augmented Naïve Bayes. 2018 6th International Conference on Information and Communication Technology, ICoICT 2018, 103–106. https://doi.org/10.1109/ICoICT.2018.8528802 DOI: https://doi.org/10.1109/ICoICT.2018.8528802
Jacoby, T. (2019). Islam and the Islamic State’s Magazine, Dabiq. Politics and Religion, 12(1), 32–54. https://doi.org/10.1017/S1755048318000561 DOI: https://doi.org/10.1017/S1755048318000561
Luthfi, E. T. (2018). Digital hadith authentication: A literature review and analysis. Journal of Theoretical and Applied Information Technology, 96(15), 5054–5068.
Mohd, M. (2021). Quranic optical text recognition using deep learning models. IEEE Access, 9, 38318–38330. https://doi.org/10.1109/ACCESS.2021.3064019 DOI: https://doi.org/10.1109/ACCESS.2021.3064019
Mosa, M. A. (2021). Predicting Semantic Categories in Text Based on Knowledge Graph Combined with Machine Learning Techniques. Applied Artificial Intelligence, 35(12), 933–951. https://doi.org/10.1080/08839514.2021.1966883 DOI: https://doi.org/10.1080/08839514.2021.1966883
Nahar, K. M. O. (2020). An efficient holy quran recitation recognizer based on SVM learning model. Jordanian Journal of Computers and Information Technology, 6(4), 392–414. https://doi.org/10.5455/jjcit.71-1593380662 DOI: https://doi.org/10.5455/jjcit.71-1593380662
Nobisa, J., & Usman. (2021). Penggunaan Metode Ummi dalam Pembelajaran Al-Qur’an. Jurnal Studi Ilmu Pendidikan dan Keislaman, 4(1). DOI: https://doi.org/10.36835/al-fikrah.v4i1.110
Pratama, S. E. (2020). Weighted inverse document frequency and vector space model for hadith search engine. Indonesian Journal of Electrical Engineering and Computer Science, 18(2), 1004–1014. https://doi.org/10.11591/ijeecs.v18.i2.pp1004-1014 DOI: https://doi.org/10.11591/ijeecs.v18.i2.pp1004-1014
Qayyum, A. (2018). Quran Reciter Identification: A Deep Learning Approach. Proceedings of the 2018 7th International Conference on Computer and Communication Engineering, ICCCE 2018, 492–497. https://doi.org/10.1109/ICCCE.2018.8539336 DOI: https://doi.org/10.1109/ICCCE.2018.8539336
Rina, N. (2020). Character education based on digital comic media. International Journal of Interactive Mobile Technologies, 14(3), 107–127. https://doi.org/10.3991/ijim.v14i03.12111 DOI: https://doi.org/10.3991/ijim.v14i03.12111
Romadhon, M. S. (2019). Blended learning system using social media for college student: A case of tahsin education. Procedia Computer Science, 161, 160–167. https://doi.org/10.1016/j.procs.2019.11.111 DOI: https://doi.org/10.1016/j.procs.2019.11.111
Rostam, N. A. P. (2021). Text categorisation in Quran and Hadith: Overcoming the interrelation challenges using machine learning and term weighting. Journal of King Saud University - Computer and Information Sciences, 33(6), 658–667. https://doi.org/10.1016/j.jksuci.2019.03.007 DOI: https://doi.org/10.1016/j.jksuci.2019.03.007
Shahriar, S. (2021). Classifying Maqams of Quranic Recitations using Deep Learning. IEEE Access. https://doi.org/10.1109/ACCESS.2021.3098415 DOI: https://doi.org/10.1109/ACCESS.2021.3098415
Supriyadi, T. (2019a). Phonological interference in reciting al-Qur’an: A critical reflection on the learning of Al-Qur’an phonology through action research. International Journal of Learning, Teaching and Educational Research, 18(9), 46–77. https://doi.org/10.26803/ijlter.18.9.3 DOI: https://doi.org/10.26803/ijlter.18.9.3
Supriyadi, T. (2019b). The problem of students in reading the Quran: A reflective-critical treatment through action research. International Journal of Instruction, 12(1), 311–326. https://doi.org/10.29333/iji.2019.12121a DOI: https://doi.org/10.29333/iji.2019.12121a
Syafei, A., Natsir, N., & Jaenudin, M. (2020). Pengaruh Khatam Al-Qur’an dan Bimbingan Guru terhadap Kemampuan Membaca Al-Qur’an di MTS Nurul Ihsan Cibinong Bogor. Jurnal Dirosah Islamiyah, 2(2), 131-150. DOI: https://doi.org/10.47467/jdi.v2i2.116
Syaifullah, A., Rahmah, F. M., & Salamah, F. (2021). Penerapan Ilmu Tajwid Dalam Pembelajaran Al-Qur’an Untuk Mengembangkan Bacaan Al-Qur’an. Seminar Nasional Pengabdian Masyarakat LPPM UMJ.
Tharwat, G. (2021). Arabic Sign Language Recognition System for Alphabets Using Machine Learning Techniques. Journal of Electrical and Computer Engineering, 2021. https://doi.org/10.1155/2021/2995851 DOI: https://doi.org/10.1155/2021/2995851
Utomo, F. S. (2019). New instances classification framework on Quran ontology applied to question answering system. Telkomnika (Telecommunication Computing Electronics and Control), 17(1), 139–146. https://doi.org/10.12928/TELKOMNIKA.v17i1.9794 DOI: https://doi.org/10.12928/telkomnika.v17i1.9794
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Enung Nugraha, Egi Desabina, Ningrat Haeliah, Nadya Fatimaturohmah, Melinda Melinda, Ulfa Masfufah, Monica Mastuti Ubudiah, Nurkhotimah Nurkhotimah, Nurlaila Harum, Siti Mahilatul Azizah, Octavia Pradya Sinta, Shiyam Putri Utami, Siti Afuah

This work is licensed under a Creative Commons Attribution 4.0 International License.