Keywords
internet activity
logistic regression
online
pandemic
school participation
logistic regression
online
pandemic
school participation
How to Cite
Purwa, T., & Cendekia, D. G. (2022). The Nexus between Education and Internet Use of Students: Evidence from Underdeveloped Regions in Indonesia. Muslim Education Review, 1(1), 59-84. https://doi.org/10.56529/mer.v1i1.8
Abstract
During the COVID-19 pandemic and the Industry 4.0 era, the role of the Internet became extremely important for connecting the society. Unfortunately, heterogeneous geographical, socioeconomic and demographic characteristics may create different roles in using the Internet, leading to a digital divide. Utilizing National Socioeconomic Survey (Susenas) data collected early in the COVID-19 pandemic, this study employs binary logistic regression to investigate the effect of education through school participation on internet use in underdeveloped regions in Indonesia. The findings show that only one-fifth of students in underdeveloped regions are using the Internet. Looking deeper, school participation plays a prominent role for students online. The more educated the students, the more likely they are to use the Internet. Moreover, the possibility of a student using the Internet is increasing for students are getting the aid of the Program Indonesia Pintar (PIP), who live in households where the head of the household has particular characteristics, which are being female, of non-productive age, having higher education, working in the non-agricultural sector, having higher socioeconomic status and where fewer students live in the household. However, this study also finds that student gender has no significant impact on internet use. Promoting and providing proportional support by the government in terms of internet use based on school participation is principal due to the existence of the digital divide. It will also be very interesting when further research may account for other potential variables from the supply side that could explain the internet use of students in underdeveloped regions of Indonesia.References
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Hosmer, D.W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). John Wiley & Sons.
King, G., & Zeng, L. (2003). Logistic regression in rare events data. Journal of Statistical Software, 8, 137-163. https://doi.org/10.18637/jss.v008.i02
Lampropoulos, G., Siakas., K., & Anastasiadis., T. (2019). Internet of things in the context of Industry 4.0: An overview. International Journal of Entrepreneurial Knowledge, Center for International Scientific Research of VSO and VSPP, 7(1), 4-19. https://ideas.repec.org/a/jek/journl/v7y2019i1p4-19.html
Lera-López, F., Billon, M., & Gil, M. (2011). Determinants of internet use in Spain. Economics of Innovation and New Technology, 20(2), 127-152. https://doi.org/https://doi.org/10.1080/10438590903378017
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MartÃnez-DomÃnguez, M., & Fierros-González, I. (2022). Determinants of internet use by school-age children: The challenges for Mexico during the COVID-19 pandemic. Telecommunications Policy, 46(1)(102241), 1-18. https://doi.org/https://doi.org/ 10.1016/j.telpol.2021.102241
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Alderete, M.V. (2019). Examining the drivers of internet use among the poor: The case of BahÃa Blanca city in Argentina. Technology in Society, 59(101179), 1-8. https://doi.org/DOI: 10.1016/j.techsoc.2019.101179
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Alifia, U.E.A., Barasa, A.R., Bima, L., Pramana, R.P., Revina, S., & Tresnatri, F.A. (2020). Belajar dari rumah: Potret ketimpangan pembelajaran pada masa pandemi COVID-19. Catatan Penelitian Smeru, 1. https://rise.smeru.or.id/ id/publikasi/belajar-dari-rumah-potret-ketimpangan-pembelajaran-pada-masa-pandemi-covid-19
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Badan Pusat Statistik (BPS). (2020). Konsep dan definisi Susenas Maret 2020 (Buku 4). Badan Pusat Statistik (BPS).
Barua, A., Whinston, A.B., & Yin, F. (2000). Value and productivity in the Internet economy. Computer, 33(5), 102-105.
BPS-Statistics Indonesia. (2020). Persentase penduduk miskin Maret 2020 naik menjadi 9,78 persen. https://www.bps.go.id/pressrelease/2020/07/15/ 1744/persentase-penduduk-miskin-maret-2020-naik-menjadi-9-78-persen.html
BPS-Statistics Indonesia. (2021a). Persentase penduduk miskin di daerah tertinggal (Persen), 2018-2020. https://www.bps.go.id/indicator/153/1238/ 1/persentase-penduduk-miskin-di-daerah-tertinggal.html
BPS-Statistics Indonesia. (2021b). Telecommunication statistics in Indonesia, 2020. BPS-Statistics Indonesia. https://www.bps.go.id/publication/2021/ 10/11/e03aca1e6ae93396ee660328/statistik-telekomunikasi-indonesia-2020.html
Chiao, C., & Chiu, C.H. (2018). The mediating effect of ICT usage on the relationship between students' socioeconomic status and achievement. The Asia-Pacific Education Researcher, 27(2), 109-121. https://doi.org/https://doi.org/ 10.1007/s40299-018-0370-9
Cooke, L., & Greenwood, H. (2008). Cleaners don't need computers: Bridging the digital divide in the workplace. Aslib Proceedings, 60(2), 143-157.
Cucinotta, D., & Vanelli, M. (2020). WHO declares COVID-19 a pandemic. Acta Biomedica, 91(1), 157-160.
Dabla, A. (2004). The role of information technology policies in promoting social and economic development: The case of the state of Andhra Pradesh, India. The Electronic Journal on Information Systems in Developing Countries, 19(5), 1-21. https://doi.org/DOI: 10.1002/j.1681-4835.2004.tb00126.x
Dahiya, S., Rokanas, L.N., Singh, S., Yang, M., & Peha, J.M. (2021). Lessons from internet use and performance during Covid-19. Journal of Information Policy, 11, 202-221. https://doi.org/https://doi.org/10.5325/jinfopoli.11.2021.0202
DeBell, M., & Chapman, C. (2006). Computer and internet use by students in 2003 (NCES 2006-065; Statistical Analysis Report). https://nces.ed.gov/ pubs2006/2006065.pdf
Elena-Bucea, A., Cruz-Jesus, F., Oliveira, T., & Coelho, P.S. (2021). Assessing the role of age, education, gender and income on the digital divide: Evidence for the European Union. Information Systems Frontiers, 23(4), 1007-1021. https://doi.org/10.1007/s10796-020-10012-9
Eschachasthi, R., Purwa, T., & Cendekia, D.G. (2022). Does Palapa Ring Project infrastructure bridging connectivity and economic activity? In Proceedings of 2021 International Conference on Data Science and Official Statistics (ICDSOS), 418-435. https://doi.org/DOI: https://doi.org/10.34123/icdsos. v2021i1.99
Hargittai, E. (1999). Weaving the Western web: explaining differences in Internet connectivity among OECD countries. Telecommunications Policy, 23(10-11), 701-718. https://doi.org/https://doi.org/10.1016/S0308-5961(99)00050-6
Hoffman, D.L., & Novak, T.P. (1998). Bridging the digital divide: The impact of race on computer access and internet use. https://files.eric.ed.gov/fulltext/ ED421563.pdf
Hosmer, D.W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). John Wiley & Sons.
King, G., & Zeng, L. (2003). Logistic regression in rare events data. Journal of Statistical Software, 8, 137-163. https://doi.org/10.18637/jss.v008.i02
Lampropoulos, G., Siakas., K., & Anastasiadis., T. (2019). Internet of things in the context of Industry 4.0: An overview. International Journal of Entrepreneurial Knowledge, Center for International Scientific Research of VSO and VSPP, 7(1), 4-19. https://ideas.repec.org/a/jek/journl/v7y2019i1p4-19.html
Lera-López, F., Billon, M., & Gil, M. (2011). Determinants of internet use in Spain. Economics of Innovation and New Technology, 20(2), 127-152. https://doi.org/https://doi.org/10.1080/10438590903378017
Lindblom, T., & Räsänen, P. (2017). Between class and status? Examining the digital divide in Finland, the United Kingdom, and Greece. The Information Society, 33(3), 147-158. https://doi.org/https://doi.org/10.1080/01972243.2017. 1294124
Lunardon, N., Menardi, G., & Torelli, N. (2014). ROSE: A package for binary imbalanced learning. R Journal, 6(1), 79-89. https://doi.org/10.32614/rj-2014-008
Martin, S.P., & Robinson, J.P. (2007). The income digital divide: Trends and predictions for levels of internet use. Social Problems, 54(1), 1-22. https://doi.org/DOI:10.1525/SP.2007.54.1.1
MartÃnez-DomÃnguez, M., & Fierros-González, I. (2022). Determinants of internet use by school-age children: The challenges for Mexico during the COVID-19 pandemic. Telecommunications Policy, 46(1)(102241), 1-18. https://doi.org/https://doi.org/ 10.1016/j.telpol.2021.102241
Middleton, K.L., & Chambers, V. (2010). Approaching digital equity: Is wiï¬ the new leveler? Information Technology and People, 23(1), 4-22. https://doi.org/DOI: 10.1108/09593841011022528
Ministry of Education, Culture, Research, and T. (2017). Pentujuk pelaksanaan program Indonesia pintar the 2017. https://psma.kemdikbud.go.id/data/files/ Petunjuk Pelaksanaan Program Indonesia Pintar th 2017.pdf
Mubarak, F., Suomi, R., & Kantola, S-P. (2020). Confirming the links between socio-economic variables and digitalization worldwide: The unsettled debate on digital divide. Journal of Information, Communication and Ethics in Society, 18(3), 415-430. https://doi.org/https://doi.org/10.1108/JICES-02-2019-0021
Nakagawa, M., Oura, A., & Sugimoto, Y. (2022). Under-and over-investment in education: The role of locked-in fertility. Journal of Population Economics, 35(2), 755-784. https://doi.org/https://doi.org/10.1007/s00148-021-00823-8
Noce, A.A., & McKeown, L. (2008). A new benchmark for internet use: A logistic modeling of factors influencing internet use in Canada, 2005. Government Information Quarterly, 25(3), 462-476. https://doi.org/DOI: 10.1016/j.giq. 2007.04.006
Pénard, T., Poussing, N., Zomo Yebe, G., & Ella, N. (2012). Comparing the determinants of internet and cell phone use in Africa: Evidence from Gabon. Communications & Strategies, 86, 65-83. https://econpapers.repec.org/article/idtjournl/cs8603.htm
Pick, J.B., & Nishida, T. (2015). Digital divides in the world and its regions: A spatial and multivariate analysis of technological utilization. Technological Forecasting and Social Change, 91, 1-17. https://doi.org/https://doi.org/10. 1016/j.techfore.2013.12.026
Purwa, T., & Cendekia, D.G. (2021). Mapping the potential use of ICT for distance learning during Covid-19"¯: Demand and supply-side approach. 63rd ISI World Statistics Congress 2021, 1, 77-80. https://www.isi-web.org/files/docs/ papers-and-abstracts/23-day1-cps018-mapping-the-potential-use-of-i.pdf
Puspitasari, L., & Ishii, K. (2016). Digital divides and mobile internet in Indonesia: Impact of smartphones. Telematics and Informatics, 33(2), 472-483. https://doi.org/https://doi.org/10.1016/j.tele.2015.11.001
Qomariyah, A.N. (2009). Perilaku penggunaan internet pada kalangan remaja di perkotaan [Universitas Airlangga]. https://repository.unair.ac.id/18241/
Rice, R.E., & Katz, J.E. (2003). Comparing internet and mobile phone usage: Digital divides of usage, adoption, and dropouts. Telecommunications Policy, 27(8-9), 597-623. https://doi.org/https://doi.org/10.1016/S0308-5961(03)00068-5
Salas-Eljatib, C., Fuentes-Ramirez, A., Gregoire, T.G., Altamirano, A., & Yaitul, V. (2018). A study on the effects of unbalanced data when fitting logistic regression models in ecology. Ecological Indicators, 85, 502-508. https://doi.org/http://dx.doi.org/10.1016/j.ecolind.2017.10.030
Shavkun, I., Bukharina, L., Dybchynska, Y., & Onyshchenko, O. (2021). Social economic factors of ICT use in education: Lessons from the pandemic. CEUR Workshop Proceedings, 3013, 193-203. http://ceur-ws.org/Vol-3013/20210193.pdf
Singh, V. (2004). Factors associated with household internet use in Canada, 1998-2000 (No. 28034; Agriculture and Rural Working Paper Series). https://doi.org/DOI: 10.22004/ag.econ.28034
Smith, D.T., & Graham, R. (2012). Household expenditures on information and communication technologies: A proposal for a digital practice model. Race, Gender & Class, 19(3-4), 161-178. https://www.jstor.org/stable/43497494
Srivastava, A., & Mohanty, S.K. (2010). Economic proxies, household consumption and health estimates. Economic and Political Weekly, 45(16), 55-63.
Sulisworo, D. (2016). The contribution of the education system quality to improve the nation's competitiveness of Indonesia. Journal of Education and Learning, 10(2), 127-138. https://doi.org/DOI: 10.11591/edulearn.v10i2.3468
Szumilas, M. (2010). Explaining odds ratios. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 19, 227-229. https://doi.org/10. 1136/bmj.c4414
The Government of Kapuas Hulu Regency. (2020). PIP bantu pelajar pada masa pandemic Covid-19. https://info.kapuashulukab.go.id/2020/10/13/pip-bantu-pelajar-pada-masa-pandemi-covid-19/
The Jakarta Post. (2020). Indonesian internet users hit 196 million, still concentrated in Java: APJII survey. https://www.thejakartapost.com/news/ 2020/11/11/indonesian-internet-users-hit-196-million-still-concentrated-in-java-apjii-survey.html
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