Penerapan Business Model Madrasah Aliyah Negeri 5 Kalimantan Selatan dengan IOT

  • Syafie Syafie Pradita University
Keywords: Internet of Things, Business Architecture, Information Architecture, Technology Architecture, Business Model


 Currently internet of things technology has developed rapidly, where almost all fields use it. One of them is the field of education, where this field utilizes internet of things technology in the teaching and learning process. During the Covid-19 pandemic, the use of the Internet of Things is very useful in the field of education. The use of this technology makes it easier for educators and students to want to explore aspects of the benefits, for example in monitoring teaching and learning activities in the classroom, educators will get information about student activities. Student attendance is directly entered into the student and educator attendance system. The problem with education at the time of the current Covid-19 pandemic, many madrasas or schools are not ready to face the pandemic. Researchers will provide an overview of the architectural model regarding the education business model using the internet of things. Where education business architecture will be discussed regarding business architecture, information architecture and technology architecture. The purpose of implementing this business model is to plan a business model based on the Internet of Things, where urgency is needed in carrying out the teaching and learning process by utilizing the Internet of Things.


[1] M. Tavana, V. Hajipour, and S. Oveisi, “IoT-based enterprise resource planning: Challenges, open issues, applications, architecture, and future research directions,” Internet of Things, vol. 11, p. 100262, 2020, doi: 10.1016/j.iot.2020.100262.
[2] F. Z. Fagroud, H. Toumi, E. H. Ben Lahmar, M. A. Talhaoui, K. Achtaich, and S. El Filali, “Impact of IoT devices in E-Health: A Review on IoT in the context of COVID-19 and its variants,” Procedia Comput. Sci., vol. 191, pp. 343–348, 2021, doi: 10.1016/j.procs.2021.07.046.
[3] D. Hindarto, R. E. Indrajit, and E. Dazki, “Sustainability of Implementing Enterprise Architecture in the Solar Power Generation Manufacturing Industry,” Sinkron, vol. 6, no. 1, pp. 13–24, 2021, [Online]. Available:
[4] J. A. Camatti, G. M. Rabelo, M. Borsato, and M. Pellicciari, “Comparative study of open IoT architectures with TOGAF for industry implementation,” Procedia Manuf., vol. 51, pp. 1132–1137, 2020, doi: 10.1016/j.promfg.2020.10.159.
[5] T. N. Gia et al., “IoT-based continuous glucose monitoring system: A feasibility study,” Procedia Comput. Sci., vol. 109, pp. 327–334, 2017, doi: 10.1016/j.procs.2017.05.359.
[6] S. Ayvaz and K. Alpay, “Predictive maintenance system for production lines in manufacturing: A machine learning approach using IoT data in real-time,” Expert Syst. Appl., vol. 173, no. January, p. 114598, 2021, doi: 10.1016/j.eswa.2021.114598.
[7] Y. M. Al-Naggar, N. Jamil, M. F. Hassan, and A. R. Yusoff, “Condition monitoring based on IoT for predictive maintenance of CNC machines,” Procedia CIRP, vol. 102, pp. 314–318, 2021, doi: 10.1016/j.procir.2021.09.054.
[8] D. Yang, D. Wang, H. Zhou, Y. Wang, S. Song, and Q. Dong, “A novel application integration architecture for the education industry,” Procedia Comput. Sci., vol. 176, pp. 1813–1822, 2020, doi: 10.1016/j.procs.2020.09.220.
[9] S. Jose, RajabooshanamArlene, and S. Lydia, “Disruptive architectural technology in engineering education.,” Procedia Comput. Sci., vol. 172, pp. 641–648, 2020, doi: 10.1016/j.procs.2020.05.083.
[10] M. S. Hadj Sassi, L. Chaari Fourati, M. Zekri, and S. Ben Yahia, “Knowledge Management Process for Air Quality Systems based on Data Warehouse Specification,” Procedia Comput. Sci., vol. 192, pp. 29–38, 2021, doi: 10.1016/j.procs.2021.08.004.
[11] M. AlMeghari, S. Taha, H. Elmahdy, and X. Shen, “A proposed authentication and group-key distribution model for data warehouse signature, DWS framework,” Egypt. Informatics J., vol. 22, no. 3, pp. 245–255, 2021, doi: 10.1016/j.eij.2020.09.002.
[12] S. Bouaziz, A. Nabli, and F. Gargouri, “Design a data warehouse schema from document-oriented database,” Procedia Comput. Sci., vol. 159, pp. 221–230, 2019, doi: 10.1016/j.procs.2019.09.177.
[13] F. Jenhani, M. S. Gouider, and L. Ben Said, “Streaming social media data analysis for events extraction and warehousing using hadoop and storm: Drug abuse case study,” Procedia Comput. Sci., vol. 159, pp. 1459–1467, 2019, doi: 10.1016/j.procs.2019.09.316.
[14] S. Kim, R. Pérez-Castillo, I. Caballero, and D. Lee, “Organizational process maturity model for IoT data quality management,” J. Ind. Inf. Integr., no. xxxx, 2021, doi: 10.1016/j.jii.2021.100256.
[15] B. A. Peterson, J. P. Fefer, R. L. Sharp, M. M. Brunson, and J. C. Skibins, “To connect or not to connect: Visitor preferences for Wi-Fi and cellular network service at a national park,” Soc. Sci. Humanit. Open, vol. 4, no. 1, p. 100179, 2021, doi: 10.1016/j.ssaho.2021.100179.
[16] A. S. Ibrahim, H. Al-Mahdi, and H. Nassar, “Characterization of task response time in a fog-enabled IoT network using queueing models with general service times,” J. King Saud Univ. - Comput. Inf. Sci., no. xxxx, 2021, doi: 10.1016/j.jksuci.2021.09.008.
[17] B. Shen, N. Chilamkurti, R. Wang, X. Zhou, S. Wang, and W. Ji, “Deadline-aware rate allocation for IoT services in data center network,” J. Parallel Distrib. Comput., vol. 118, pp. 296–306, 2018, doi: 10.1016/j.jpdc.2017.09.012.
[18] B. Sonkoly et al., “Scalable edge cloud platforms for IoT services,” J. Netw. Comput. Appl., vol. 170, no. August, 2020, doi: 10.1016/j.jnca.2020.102785.