Analysis of Quality Management of Islamic Education at the Pabelan Islamic Boarding School, Mungkid District, Magelang Regency
Downloads
Abstract— This study aims to describe the management of Islamic education institutions to improve the quality of Islamic boarding schools. This research phase consisted of a number of activities, namely (1) examining the units of analysis, (2) mapping the management models of Islamic educational institutions, and (3) analyzing the management model of Islamic education to improve the quality of education in the research object. The Islamic boarding school chosen as the research location is the Pabelan Islamic Boarding School, Magelang. Pabelan Islamic Boarding School is a boarding school that has proven its existence and has graduated many alumni who are widely active in Indonesia. To facilitate this research, researchers used the theory of quality management of Islamic educational institutions which is based on four quality indicators, namely (1) the quality of graduates, (2) the quality of the learning process, (3) the quality of school services and (4) the quality of the school environment. The research method uses a qualitative descriptive method. The research subjects were leaders, senior teachers and students. The research subjects were the analysis of the quality management of the Kulliyatul Mu'allim Al-Islamiyah Pabelan Islamic Boarding School and confirmation of the correctness of the material through source triangulation and method triangulation. The results of the analysis are expected to be able to formulate quality management for Islamic educational institutions in Indonesia. This study will analyze strategies to improve the quality of education, the factors that support and inhibit the process of improving the quality of education, and the efforts made by the Pabelan Islamic Boarding School in improving the quality of education
Aldowah, H., Al-Samarraie, H., & Fauzy, W. M. (2019). Educational data mining and learning analytics for 21st century higher education: A review and synthesis. Telematics and Informatics, 37, 13–49. https://doi.org/10.1016/j.tele.2019.01.007
Alhammadi, S., Archer, S., & Asutay, M. (2020). Risk management and corporate governance failures in Islamic banks: A case study. Journal of Islamic Accounting and Business Research, 11(9), 1921–1939. https://doi.org/10.1108/JIABR-03-2020-0064
Bhatti, M. (2019). Managing Shariah Non-Compliance Risk via Islamic Dispute Resolution. Journal of Risk and Financial Management, 13(1), 2. https://doi.org/10.3390/jrfm13010002
Chandrasekar, R., Chandrasekhar, S., Sundari, K. K. S., & Ravi, P. (2020). Development and validation of a formula for objective assessment of cervical vertebral bone age. Progress in Orthodontics, 21(1), 38. https://doi.org/10.1186/s40510-020-00338-0
Craik, A., He, Y., & Contreras-Vidal, J. L. (2019). Deep learning for electroencephalogram (EEG) classification tasks: A review. Journal of Neural Engineering, 16(3), 031001. https://doi.org/10.1088/1741-2552/ab0ab5
Crawford, A., & Serhal, E. (2020). Digital Health Equity and COVID-19: The Innovation Curve Cannot Reinforce the Social Gradient of Health. Journal of Medical Internet Research, 22(6), e19361. https://doi.org/10.2196/19361
Darmaji, D., Supriyanto, A., & Timan, A. (2019). Sistem Penjaminan Mutu Internalsekolah Untuk Meningkatkan Mutu Lulusan. JMSP (Jurnal Manajemen Dan Supervisi Pendidikan), 3(3), 130–136.
Dunn, P., & Hazzard, E. (2019). Technology approaches to digital health literacy. International Journal of Cardiology, 293, 294–296. https://doi.org/10.1016/j.ijcard.2019.06.039
Estacio, E. V., Whittle, R., & Protheroe, J. (2019). The digital divide: Examining socio-demographic factors associated with health literacy, access and use of internet to seek health information. Journal of Health Psychology, 24(12), 1668–1675. https://doi.org/10.1177/1359105317695429
Guess, A. M., Lerner, M., Lyons, B., Montgomery, J. M., Nyhan, B., Reifler, J., & Sircar, N. (2020). A digital media literacy intervention increases discernment between mainstream and false news in the United States and India. Proceedings of the National Academy of Sciences, 117(27), 15536–15545. https://doi.org/10.1073/pnas.1920498117
Hasanah, M. (2021). The Role of Parents in Children Memorizing the Qur’an in Middle School Based on the Amanatul Ummah Islamic Boarding School. Tafkir: Interdisciplinary Journal of Islamic Education, 2(2), 139–156.
Hikmi, R., Simorangkir, M., & Sudrajat, A. (2020). Development Of Interactive Multimedia Lectora Inspire Problem Based On Science. Journal of Physics: Conference Series, 1485(1), 012036. https://doi.org/10.1088/1742-6596/1485/1/012036
Irwandani, Umarella, S., Rahmawati, A., Meriyati, & Susilowati, N. E. (2019). Interactive Multimedia Lectora Inspire Based on Problem Based Learning: Development in The Optical Equipment. Journal of Physics: Conference Series, 1155, 012011. https://doi.org/10.1088/1742-6596/1155/1/012011
Kang, S., & Kim, Y. (2021). Examining the quality of mobile-assisted, video-making task outcomes: The role of proficiency, narrative ability, digital literacy, and motivation. Language Teaching Research, 136216882110479. https://doi.org/10.1177/13621688211047984
Kurniawan, R. B., Mujasam, M., Yusuf, I., & Widyaningsih, S. W. (2019). Development of physics learning media based on Lectora Inspire Software on the elasticity and Hooke’s law material in senior high school. Journal of Physics: Conference Series, 1157, 032022. https://doi.org/10.1088/1742-6596/1157/3/032022
Le Berre, C., Sandborn, W. J., Aridhi, S., Devignes, M.-D., Fournier, L., Smaïl-Tabbone, M., Danese, S., & Peyrin-Biroulet, L. (2020). Application of Artificial Intelligence to Gastroenterology and Hepatology. Gastroenterology, 158(1), 76-94.e2. https://doi.org/10.1053/j.gastro.2019.08.058
Mangaroska, K., & Giannakos, M. (2019). Learning Analytics for Learning Design: A Systematic Literature Review of Analytics-Driven Design to Enhance Learning. IEEE Transactions on Learning Technologies, 12(4), 516–534. https://doi.org/10.1109/TLT.2018.2868673
McGuinness, C., & Fulton, C. (2019). Digital Literacy in Higher Education: A Case Study of Student Engagement with E-Tutorials Using Blended Learning. Journal of Information Technology Education: Innovations in Practice, 18, 001–028. https://doi.org/10.28945/4190
Morse, J. S., Lalonde, T., Xu, S., & Liu, W. R. (2020). Learning from the Past: Possible Urgent Prevention and Treatment Options for Severe Acute Respiratory Infections Caused by 2019?nCoV. ChemBioChem, 21(5), 730–738. https://doi.org/10.1002/cbic.202000047
Reffiane, F., Iswari, R. S., & Marwoto, P. (2019). The effectiveness of Lectora Inspire media assisted guided inquiry method on the students’ critical thinking skill in the science nature: A case study at gugus Diponegoro elementary schools Semarang. Journal of Physics: Conference Series, 1170, 012078. https://doi.org/10.1088/1742-6596/1170/1/012078
Shalikhah, N. D., Sari, K. P., Iman, M. S., Oktradiksa, A., Nugroho, I., & Aufa, M. (2023). Utilization Kinemaster in making learning videos for elementary school teachers. 020045. https://doi.org/10.1063/5.0125788
Sieck, C. J., Sheon, A., Ancker, J. S., Castek, J., Callahan, B., & Siefer, A. (2021). Digital inclusion as a social determinant of health. Npj Digital Medicine, 4(1), 52. https://doi.org/10.1038/s41746-021-00413-8
Solomon, D. H., & Rudin, R. S. (2020). Digital health technologies: Opportunities and challenges in rheumatology. Nature Reviews Rheumatology, 16(9), 525–535. https://doi.org/10.1038/s41584-020-0461-x
Tieman, M. (2020). Measuring corporate halal reputation: A corporate halal reputation index and research propositions. Journal of Islamic Marketing, 11(3), 591–601. https://doi.org/10.1108/JIMA-05-2018-0095
Tubagus, M., Muslim, S., & Suriani, S. (2020). Development of Learning Management System-Based Blended Learning Model using Claroline in Higher Education. International Journal of Interactive Mobile Technologies (IJIM), 14(06), 186. https://doi.org/10.3991/ijim.v14i06.13399
Van Deursen, A. J. (2020). Digital Inequality During a Pandemic: Quantitative Study of Differences in COVID-19–Related Internet Uses and Outcomes Among the General Population. Journal of Medical Internet Research, 22(8), e20073. https://doi.org/10.2196/20073
Van Workum, F., Stenstra, M. H. B. C., Berkelmans, G. H. K., Slaman, A. E., Van Berge Henegouwen, M. I., Gisbertz, S. S., Van Den Wildenberg, F. J. H., Polat, F., Irino, T., Nilsson, M., Nieuwenhuijzen, G. A. P., Luyer, M. D., Adang, E. M., Hannink, G., Rovers, M. M., & Rosman, C. (2019). Learning Curve and Associated Morbidity of Minimally Invasive Esophagectomy: A Retrospective Multicenter Study. Annals of Surgery, 269(1), 88–94. https://doi.org/10.1097/SLA.0000000000002469
Wu, L., Wang, Y., Li, X., & Gao, J. (2019). Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition. IEEE Transactions on Cybernetics, 49(5), 1791–1802. https://doi.org/10.1109/TCYB.2018.2813971
Copyright (c) 2023 Nurodin Usman, Nurodin Usman, Xie Guilin, Deng Jiao
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
