The Important Role of Social Media in Supporting Reading Skills in Islamic Boarding Schools
DOI:
https://doi.org/10.55849/attasyrih.v11i1.278Keywords:
Social Media, Reading Skills, Islamic Boarding SchoolAbstract
The problem of students in supporting reading skills is related to efforts to understand written language. Students find it difficult to understand social media learning. This reading skill support is very important for students who are in Islamic Boarding School. This is also due to the lack of innovation of students in learning at school. The purpose of this study is to find out the role of social media in supporting reading skills in the learning of students at Islamic Boarding School. The method used in this study is a quantitative method where this method can show that this research is in the form of data that contains numbers. The data was obtained by using the geogle from application as a means to create a questionnaire containing questions and then distributed to respondents as a result of the research subject. The results of this study show that there is an increase in student learning in Islamic boarding schools through social media. The conclusion of this study explains that social media can be used in learning Arabic which can increase the enthusiasm for learning with reading skills in Islamic Boarding School. The limitation of this study is that the researcher only conducts research on social media in supporting reading skills in Islamic boarding schools. This study also recommends to future researchers to be able to conduct research in supporting Arabic language learning skills, but it is further developed so that this research becomes interesting and also a challenge in the use of social media in learning Arabic language
References
Alexander, S. P. H., Christopoulos, A., Davenport, A. P., Kelly, E., Mathie, A., Peters, J. A., Veale, E. L., Armstrong, J. F., Faccenda, E., Harding, S. D., Pawson, A. J., Sharman, J. L., Southan, C., Davies, J. A., CGTP Collaborators, Abbracchio, M. P., Alexander, W., Al-hosaini, K., Bäck, M., … Yao, C. (2019). THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: G protein?coupled receptors. British Journal of Pharmacology, 176(S1). https://doi.org/10.1111/bph.14748
Al-Mallah, M. H. (2023). Broaden your horizon. Journal of Nuclear Cardiology, 30(1), 436–438. https://doi.org/10.1007/s12350-022-03188-x
Balduzzi, S., Rücker, G., & Schwarzer, G. (2019). How to perform a meta-analysis with R: A practical tutorial. Evidence Based Mental Health, 22(4), 153–160. https://doi.org/10.1136/ebmental-2019-300117
Bolyen, E., Rideout, J. R., Dillon, M. R., Bokulich, N. A., Abnet, C. C., Al-Ghalith, G. A., Alexander, H., Alm, E. J., Arumugam, M., Asnicar, F., Bai, Y., Bisanz, J. E., Bittinger, K., Brejnrod, A., Brislawn, C. J., Brown, C. T., Callahan, B. J., Caraballo-Rodríguez, A. M., Chase, J., … Caporaso, J. G. (2019). Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology, 37(8), 852–857. https://doi.org/10.1038/s41587-019-0209-9
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., Xia, J., Yu, T., Zhang, X., & Zhang, L. (2020). Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. The Lancet, 395(10223), 507–513. https://doi.org/10.1016/S0140-6736(20)30211-7
Cheung, M. L., Pires, G., & Rosenberger, P. J. (2020). The influence of perceived social media marketing elements on consumer–brand engagement and brand knowledge. Asia Pacific Journal of Marketing and Logistics, 32(3), 695–720. https://doi.org/10.1108/APJML-04-2019-0262
Chew, N. W. S., Lee, G. K. H., Tan, B. Y. Q., Jing, M., Goh, Y., Ngiam, N. J. H., Yeo, L. L. L., Ahmad, A., Ahmed Khan, F., Napolean Shanmugam, G., Sharma, A. K., Komalkumar, R. N., Meenakshi, P. V., Shah, K., Patel, B., Chan, B. P. L., Sunny, S., Chandra, B., Ong, J. J. Y., … Sharma, V. K. (2020). A multinational, multicentre study on the psychological outcomes and associated physical symptoms amongst healthcare workers during COVID-19 outbreak. Brain, Behavior, and Immunity, 88, 559–565. https://doi.org/10.1016/j.bbi.2020.04.049
Cornely, O. A., Alastruey-Izquierdo, A., Arenz, D., Chen, S. C. A., Dannaoui, E., Hochhegger, B., Hoenigl, M., Jensen, H. E., Lagrou, K., Lewis, R. E., Mellinghoff, S. C., Mer, M., Pana, Z. D., Seidel, D., Sheppard, D. C., Wahba, R., Akova, M., Alanio, A., Al-Hatmi, A. M. S., … Chakrabarti, A. (2019). Global guideline for the diagnosis and management of mucormycosis: An initiative of the European Confederation of Medical Mycology in cooperation with the Mycoses Study Group Education and Research Consortium. The Lancet Infectious Diseases, 19(12), e405–e421. https://doi.org/10.1016/S1473-3099(19)30312-3
Cui, J., Wei, L., Zhang, J., Xu, Y., & Zhong, H. (2019). An Efficient Message-Authentication Scheme Based on Edge Computing for Vehicular Ad Hoc Networks. IEEE Transactions on Intelligent Transportation Systems, 20(5), 1621–1632. https://doi.org/10.1109/TITS.2018.2827460
El-Kassar, A.-N., & Singh, S. K. (2019). Green innovation and organizational performance: The influence of big data and the moderating role of management commitment and HR practices. Technological Forecasting and Social Change, 144, 483–498. https://doi.org/10.1016/j.techfore.2017.12.016
Eltom, A., Zhong, G., & Muhammad, A. (2019). Scaffold Techniques and Designs in Tissue Engineering Functions and Purposes: A Review. Advances in Materials Science and Engineering, 2019, 1–13. https://doi.org/10.1155/2019/3429527
Enyoh, C. E., Verla, A. W., Verla, E. N., Ibe, F. C., & Amaobi, C. E. (2019). Airborne microplastics: A review study on method for analysis, occurrence, movement and risks. Environmental Monitoring and Assessment, 191(11), 668. https://doi.org/10.1007/s10661-019-7842-0
Ford, S., & Minshall, T. (2019). Invited review article: Where and how 3D printing is used in teaching and education. Additive Manufacturing, 25, 131–150. https://doi.org/10.1016/j.addma.2018.10.028
Grant, W., Lahore, H., McDonnell, S., Baggerly, C., French, C., Aliano, J., & Bhattoa, H. (2020). Evidence that Vitamin D Supplementation Could Reduce Risk of Influenza and COVID-19 Infections and Deaths. Nutrients, 12(4), 988. https://doi.org/10.3390/nu12040988
Gupta, S., Parker, J., Smits, S., Underwood, J., & Dolwani, S. (2020). Persistent viral shedding of SARS?CoV?2 in faeces – a rapid review. Colorectal Disease, 22(6), 611–620. https://doi.org/10.1111/codi.15138
Gusenbauer, M. (2019). Google Scholar to overshadow them all? Comparing the sizes of 12 academic search engines and bibliographic databases. Scientometrics, 118(1), 177–214. https://doi.org/10.1007/s11192-018-2958-5
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hart, O. E., & Halden, R. U. (2020). Computational analysis of SARS-CoV-2/COVID-19 surveillance by wastewater-based epidemiology locally and globally: Feasibility, economy, opportunities and challenges. Science of The Total Environment, 730, 138875. https://doi.org/10.1016/j.scitotenv.2020.138875
Hindricks, G., Potpara, T., Dagres, N., Arbelo, E., Bax, J. J., Blomström-Lundqvist, C., Boriani, G., Castella, M., Dan, G.-A., Dilaveris, P. E., Fauchier, L., Filippatos, G., Kalman, J. M., La Meir, M., Lane, D. A., Lebeau, J.-P., Lettino, M., Lip, G. Y. H., Pinto, F. J., … Zakirov, N. U. (2021). 2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS). European Heart Journal, 42(5), 373–498. https://doi.org/10.1093/eurheartj/ehaa612
Hitaj, B., Gasti, P., Ateniese, G., & Perez-Cruz, F. (2019). PassGAN: A Deep Learning Approach for Password Guessing. In R. H. Deng, V. Gauthier-Umaña, M. Ochoa, & M. Yung (Eds.), Applied Cryptography and Network Security (Vol. 11464, pp. 217–237). Springer International Publishing. https://doi.org/10.1007/978-3-030-21568-2_11
Jaiswal, J., & Halkitis, P. N. (2019). Towards a More Inclusive and Dynamic Understanding of Medical Mistrust Informed by Science. Behavioral Medicine, 45(2), 79–85. https://doi.org/10.1080/08964289.2019.1619511
Lai, C.-C., Shih, T.-P., Ko, W.-C., Tang, H.-J., & Hsueh, P.-R. (2020). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges. International Journal of Antimicrobial Agents, 55(3), 105924. https://doi.org/10.1016/j.ijantimicag.2020.105924
Leung, C. L. A., Marussi, S., Towrie, M., Atwood, R. C., Withers, P. J., & Lee, P. D. (2019). The effect of powder oxidation on defect formation in laser additive manufacturing. Acta Materialia, 166, 294–305. https://doi.org/10.1016/j.actamat.2018.12.027
Li, C., Deng, X., Zhang, W., Xie, X., Conrad, M., Liu, Y., Angeli, J. P. F., & Lai, L. (2019). Novel Allosteric Activators for Ferroptosis Regulator Glutathione Peroxidase 4. Journal of Medicinal Chemistry, 62(1), 266–275. https://doi.org/10.1021/acs.jmedchem.8b00315
Mazza, C., Ricci, E., Biondi, S., Colasanti, M., Ferracuti, S., Napoli, C., & Roma, P. (2020). A Nationwide Survey of Psychological Distress among Italian People during the COVID-19 Pandemic: Immediate Psychological Responses and Associated Factors. International Journal of Environmental Research and Public Health, 17(9), 3165. https://doi.org/10.3390/ijerph17093165
Mondal, S., Wijewardena, K. P., Karuppuswami, S., Kriti, N., Kumar, D., & Chahal, P. (2019). Blockchain Inspired RFID-Based Information Architecture for Food Supply Chain. IEEE Internet of Things Journal, 6(3), 5803–5813. https://doi.org/10.1109/JIOT.2019.2907658
Murray, C. J. L., Aravkin, A. Y., Zheng, P., Abbafati, C., Abbas, K. M., Abbasi-Kangevari, M., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., Abegaz, K. H., Abolhassani, H., Aboyans, V., Abreu, L. G., Abrigo, M. R. M., Abualhasan, A., Abu-Raddad, L. J., Abushouk, A. I., Adabi, M., … Lim, S. S. (2020). Global burden of 87 risk factors in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1223–1249. https://doi.org/10.1016/S0140-6736(20)30752-2
Nascimento, D. L. M., Alencastro, V., Quelhas, O. L. G., Caiado, R. G. G., Garza-Reyes, J. A., Rocha-Lona, L., & Tortorella, G. (2019). Exploring Industry 4.0 technologies to enable circular economy practices in a manufacturing context: A business model proposal. Journal of Manufacturing Technology Management, 30(3), 607–627. https://doi.org/10.1108/JMTM-03-2018-0071
O’Brien, K., Breyne, K., Ughetto, S., Laurent, L. C., & Breakefield, X. O. (2020). RNA delivery by extracellular vesicles in mammalian cells and its applications. Nature Reviews Molecular Cell Biology, 21(10), 585–606. https://doi.org/10.1038/s41580-020-0251-y
Olsen, T. L., & Tomlin, B. (2020). Industry 4.0: Opportunities and Challenges for Operations Management. Manufacturing & Service Operations Management, 22(1), 113–122. https://doi.org/10.1287/msom.2019.0796
Pitts, R. A., Bonnin, X., Escourbiac, F., Frerichs, H., Gunn, J. P., Hirai, T., Kukushkin, A. S., Kaveeva, E., Miller, M. A., Moulton, D., Rozhansky, V., Senichenkov, I., Sytova, E., Schmitz, O., Stangeby, P. C., De Temmerman, G., Veselova, I., & Wiesen, S. (2019). Physics basis for the first ITER tungsten divertor. Nuclear Materials and Energy, 20, 100696. https://doi.org/10.1016/j.nme.2019.100696
Popkin, B. M., Corvalan, C., & Grummer-Strawn, L. M. (2020). Dynamics of the double burden of malnutrition and the changing nutrition reality. The Lancet, 395(10217), 65–74. https://doi.org/10.1016/S0140-6736(19)32497-3
Purcell, R., Gwyther, K., & Rice, S. M. (2019). Mental Health In Elite Athletes: Increased Awareness Requires An Early Intervention Framework to Respond to Athlete Needs. Sports Medicine - Open, 5(1), 46. https://doi.org/10.1186/s40798-019-0220-1
Rosenberg, K. V., Dokter, A. M., Blancher, P. J., Sauer, J. R., Smith, A. C., Smith, P. A., Stanton, J. C., Panjabi, A., Helft, L., Parr, M., & Marra, P. P. (2019). Decline of the North American avifauna. Science, 366(6461), 120–124. https://doi.org/10.1126/science.aaw1313
Rudin, C. (2019). Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence, 1(5), 206–215. https://doi.org/10.1038/s42256-019-0048-x
Santomauro, D. F., Mantilla Herrera, A. M., Shadid, J., Zheng, P., Ashbaugh, C., Pigott, D. M., Abbafati, C., Adolph, C., Amlag, J. O., Aravkin, A. Y., Bang-Jensen, B. L., Bertolacci, G. J., Bloom, S. S., Castellano, R., Castro, E., Chakrabarti, S., Chattopadhyay, J., Cogen, R. M., Collins, J. K., … Ferrari, A. J. (2021). Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic. The Lancet, 398(10312), 1700–1712. https://doi.org/10.1016/S0140-6736(21)02143-7
Savitz, J. (2020). The kynurenine pathway: A finger in every pie. Molecular Psychiatry, 25(1), 131–147. https://doi.org/10.1038/s41380-019-0414-4
Shackleton, R. T., Richardson, D. M., Shackleton, C. M., Bennett, B., Crowley, S. L., Dehnen-Schmutz, K., Estévez, R. A., Fischer, A., Kueffer, C., Kull, C. A., Marchante, E., Novoa, A., Potgieter, L. J., Vaas, J., Vaz, A. S., & Larson, B. M. H. (2019). Explaining people’s perceptions of invasive alien species: A conceptual framework. Journal of Environmental Management, 229, 10–26. https://doi.org/10.1016/j.jenvman.2018.04.045
Shan, J., Ling, T., Davey, K., Zheng, Y., & Qiao, S. (2019). Transition?Metal?Doped RuIr Bifunctional Nanocrystals for Overall Water Splitting in Acidic Environments. Advanced Materials, 31(17), 1900510. https://doi.org/10.1002/adma.201900510
Stiker, H.-J. (2019). A History of Disability. University of Michigan Press. https://doi.org/10.3998/mpub.11575987
Sun, K., Xiao, B., Liu, D., & Wang, J. (2019). Deep High-Resolution Representation Learning for Human Pose Estimation. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 5686–5696. https://doi.org/10.1109/CVPR.2019.00584
Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., Jensen, L. J., & Mering, C. von. (2019). STRING v11: Protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47(D1), D607–D613. https://doi.org/10.1093/nar/gky1131
Tang, Z., Kang, B., Li, C., Chen, T., & Zhang, Z. (2019). GEPIA2: An enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Research, 47(W1), W556–W560. https://doi.org/10.1093/nar/gkz430
The UniProt Consortium, Bateman, A., Martin, M.-J., Orchard, S., Magrane, M., Agivetova, R., Ahmad, S., Alpi, E., Bowler-Barnett, E. H., Britto, R., Bursteinas, B., Bye-A-Jee, H., Coetzee, R., Cukura, A., Da Silva, A., Denny, P., Dogan, T., Ebenezer, T., Fan, J., … Teodoro, D. (2021). UniProt: The universal protein knowledgebase in 2021. Nucleic Acids Research, 49(D1), D480–D489. https://doi.org/10.1093/nar/gkaa1100
Vaishya, R., Javaid, M., Khan, I. H., & Haleem, A. (2020). Artificial Intelligence (AI) applications for COVID-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(4), 337–339. https://doi.org/10.1016/j.dsx.2020.04.012
Vos, T., Lim, S. S., Abbafati, C., Abbas, K. M., Abbasi, M., Abbasifard, M., Abbasi-Kangevari, M., Abbastabar, H., Abd-Allah, F., Abdelalim, A., Abdollahi, M., Abdollahpour, I., Abolhassani, H., Aboyans, V., Abrams, E. M., Abreu, L. G., Abrigo, M. R. M., Abu-Raddad, L. J., Abushouk, A. I., … Murray, C. J. L. (2020). Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1204–1222. https://doi.org/10.1016/S0140-6736(20)30925-9
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., McIntyre, R. S., Choo, F. N., Tran, B., Ho, R., Sharma, V. K., & Ho, C. (2020). A longitudinal study on the mental health of general population during the COVID-19 epidemic in China. Brain, Behavior, and Immunity, 87, 40–48. https://doi.org/10.1016/j.bbi.2020.04.028
Wiviott, S. D., Raz, I., Bonaca, M. P., Mosenzon, O., Kato, E. T., Cahn, A., Silverman, M. G., Zelniker, T. A., Kuder, J. F., Murphy, S. A., Bhatt, D. L., Leiter, L. A., McGuire, D. K., Wilding, J. P. H., Ruff, C. T., Gause-Nilsson, I. A. M., Fredriksson, M., Johansson, P. A., Langkilde, A.-M., & Sabatine, M. S. (2019). Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes. New England Journal of Medicine, 380(4), 347–357. https://doi.org/10.1056/NEJMoa1812389
Wu, Q., & Zhang, R. (2020). Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network. IEEE Communications Magazine, 58(1), 106–112. https://doi.org/10.1109/MCOM.001.1900107
Yaseen, Z. M., Sulaiman, S. O., Deo, R. C., & Chau, K.-W. (2019). An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction. Journal of Hydrology, 569, 387–408. https://doi.org/10.1016/j.jhydrol.2018.11.069
Zhao, Z.-Q., Zheng, P., Xu, S.-T., & Wu, X. (2019). Object Detection With Deep Learning: A Review. IEEE Transactions on Neural Networks and Learning Systems, 30(11), 3212–3232. https://doi.org/10.1109/TNNLS.2018.2876865
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Melisa Rezi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
