The Influence of Household Socioeconomic Conditions on Elementary School Participation in Indonesia

Nia Enggrasari; Wenny Restikasari

doi:10.55927/fjmr.v4i10.549

Authors

Nia Enggrasari State University of Surabaya
Wenny Restikasari State University of Surabaya

DOI:

https://doi.org/10.55927/fjmr.v4i10.549

Keywords:

School Participation, Socioeconomic, Elementary School

Abstract

This study aims to analyze the influence of household socioeconomic conditions on elementary school participation in Indonesia. The data used sourced from the 2023 National Socio-Economic Survey (SUSENAS) with a sample size of 146,602 children. The analysis method employed was binary logistic regression. The results of the study partially indicate that residence, gender, recipients of the Indonesia Smart Card (KIP), ownership of mobile phones (HP), internet access, and access to Information and Communication Technology (ICT) significantly affect elementary school participation. These findings suggest that children who have access to technology and educational support are more likely to pursue elementary education. Therefore, policies focusing on equitable access to education and technology in rural areas are needed to reduce disparities in school participation.

References

Adipat, S., & Chotikapanich, R. (2022). Sustainable Development Goal 4: An Education Goal to Achieve Equitable Quality Education. Academic Journal of Interdisciplinary Studies, 11(6), 174–183. https://doi.org/10.36941/ajis-2022-0159

Ahmed, M. H. (2024). University expansion and female adolescents’ educational attainment in Ethiopia. Empirical Economics, 67(2), 417–448. https://doi.org/10.1007/s00181-024-02557-4

Ainantia, S. W., Hidayat, A., Muhammadiyah, U., Belitung, B., & Ohio, T. (2025). The School Participation Rates in Various Provinces and Residential Areas of Indonesia between 2021 and 2024. 1(1), 24–37.

Alderete, M. V., & Formichella, M. M. (2023). Access to ICT at Argentine elementary school children’s homes and its impact on school achievements. Education and Information Technologies, 28(3), 2767–2790. https://doi.org/10.1007/s10639-022-11227-w

Ali, Y., Mushtaq, S., Shahnawaz, A., Un Nisa, Z., Irraj Khan, H., & Shahreen,. (2025). Impact of Excessive Use of Mobile Phone on Academic Performance of Students of Mohtarma Benazir Bhutto Shaheed Medical College. Biological and Clinical Sciences Research Journal, 6(5), 87–90. https://doi.org/10.54112/bcsrj.v6i5.1759

Amponsah, K. D., Aboagye, G. K., Narh-Kert, M., Commey-Mintah, P., & Boateng, F. K. (2022). The Impact of Internet Usage on Students’ Success in Selected Senior High Schools in Cape Coast metropolis, Ghana. European Journal of Educational Sciences, 9(2), 1–18. https://doi.org/10.19044/ejes.v9no2a1

Bergman, P., & Chan, E. (2021). Leveraging Technology to Engage Parents at Scale: Evidence from a Randomized Controlled Trial. SSRN Electronic Journal, February. https://doi.org/10.2139/ssrn.2989472

Caniago, P., Elfindri, & Sari, D. T. (2021). Economics Development Analysis Journal Education Cash Transfer and High School Enrollment in Indonesia. Ecnomics Development Analysis Journal, 10(2), 184–204. http://journal.unnes.ac.id/sju/index.php/edaj

Csaba Csintalan, & Badulescu, A. (2015). Education and Human Capital as Engines for Economic Growth. A Literature Review. The Annals of the University of Oradea. Economic Sciences, XXIV(2), 665–674. http://widgets.ebscohost.com/prod/customerspecific/s9118275/vpn.php?url=http://search.ebscohost.com/login.aspx?direct=true&AuthType=ip,u id&db=buh&AN=117725783&site=eds-live&scope=site

Evans, D. K., Akmal, M., & Jakiela, P. (2020). Gender Gaps in Education: The Long View Working Paper 523 January 2020. January 2020. https://www.cgdev.org/sites/default/files/gender-gaps-education-long- view.pdf

Fonseca, J., Bahrawar, L., Dubeck, M. M., Sitabkhan, Y., Cummiskey, C., & Unadkat, D. (2023). Girls have academic advantages and so do boys: A multicountry analysis of gender differences in early grade reading and mathematics outcomes. RTI Press., May.

Gao, X., & Li, M. (2022). Differences between returns to education in Urban and rural China and its evolution from 1989 to 2019. PLoS ONE, 17(10 October), 1–20. https://doi.org/10.1371/journal.pone.0274506

Gath, M. E., Monk, L., Scott, A., & Gillon, G. T. (2024). .AR applications applied in the construction industry Smartphones at School: A Mixed-Methods Analysis of Educators’ and Students’ Perspectives on Mobile Phone Use at School. Education Sciences, 14(4).

Ghavifekr, S., & Rosdy, W. A. W. (2015). Teaching and learning with technology: Effectiveness of ICT integration in schools. International Journal of Research in Education and Science, 1(2), 175–191. https://doi.org/10.21890/ijres.23596

Gök, T. (2015). the Positive and Negative Effects of Digital Technologies on Students’ Learning. International Conference on Education in Mathematics, Science & Technology (ICEMST), April 23-26, 2015 Antalya, Turkey, 2, 173–

177. www.isres.org

Graves, J. M., Abshire, D. A., Amiri, S., & Mackelprang, J. L. (2021). Disparities in Technology and Broadband Internet Access across Rurality: Implications for Health and Education. Family and Community Health, 44(4), 257–265. https://doi.org/10.1097/FCH.0000000000000306

Guerrero, C., Jaume, A., Juiz, C., & Lera, I. (2016). Use of mobile devices in the classroom to increase motivation and participation of engineering university students. IEEE Latin America Transactions, 14(1), 411–416. https://doi.org/10.1109/TLA.2016.7430109

Gunnlaugsson, G., Baboudóttir, F. N., Baldé, A., Jandi, Z., Boiro, H., & Einarsdóttir, J. (2021). Public or private school? Determinants for enrolment of adolescents in Bissau, Guinea-Bissau. International Journal of Educational Research, 109(February), 1–15. https://doi.org/10.1016/j.ijer.2021.101851

Hazelhurst, S., Johnson, Y., & Sanders, I. (2011). An empirical analysis of the relationship between web usage and academic performance in undergraduate students. 1–23. http://arxiv.org/abs/1110.6267

Iddrisu, H. M., & Alhassan, A. S. (2025). The Impact of Parents ’ Socioeconomic Status on Students ’ Educational Success in Senior High Schools in the Northern Region of Ghana. 16(2), 49–64. https://doi.org/10.29329/ijer.2025.1320.3

Izquierdo-Condoy, J. S., Arias-Intriago, M., Nati-Castillo, H. A., Gollini- Mihalopoulos, R., Cardozo-Espínola, C. D., Loaiza-Guevara, V., Dalel- Gómez, W., Villamil, J., Suárez-Sangucho, I. A., Morales-Lapo, E., Tello-De--Torre, A., Hall, C., & Ortiz-Prado, E. (2024). Exploring smartphone use and its applicability in academic training of medical students in Latin America: a multicenter cross-sectional study. BMC Medical Education, 24(1). https://doi.org/10.1186/s12909-024-06334-w

Küçük, T. (2023). Technology Integrated Teaching and Its Positive and Negative Impacts on Education. International Journal of Social Sciences & Educational Studies, 10(1), 46–55. https://doi.org/10.23918/ijsses.v10i1p46

Ladrón de Guevara Rodríguez, M., Lopez-Agudo, L. A., Prieto-Latorre, C., & Marcenaro-Gutierrez, O. D. (2022). Internet use and academic performance: An interval approach. In Education and Information Technologies (Vol. 27, Issue 8). Springer US. https://doi.org/10.1007/s10639-022-11095-4

Li, X., Mahdzar, S. S. S., Khaidzir, K. A. M., & Ismail, I. E. (2025). The relationship between accessibility of urban and rural high schools and enrollment rate: A county-level study. Plos One, 20(6 June), 1–17. https://doi.org/10.1371/journal.pone.0325263

Liebenberg, H., Chetty, Y., & Prinsloo, P. (2012). Student access to and skills in using technology in an open and distance learning context. International Review of Research in Open and Distance Learning, 13(4), 250–268. https://doi.org/10.19173/irrodl.v13i4.1303

Ma, Z. (2025). A multidimensional analysis of the differences in urban and rural education in China. Journal of Education and Educational Policy Studies, 3(2), 1–5. https://doi.org/10.54254/3049-7248/2025.21803

Martínez-Serna, M. I., Baixauli-Soler, J. S., Belda-Ruiz, M., & Yagüe, J. (2024). The effect of online class attendance on academic performance in finance education. International Journal of Management Education, 22(3). https://doi.org/10.1016/j.ijme.2024.101023

Mulyo Prayitno, & Mami Hajaroh. (2024). Analysis of Gross Enrollment Ratio, Net Enrollment Ratio, and School Enrollment Ratio Trends at the Elementary School Level. Journal of Educational Learning and Innovation (ELIa), 4(1), 18–36. https://doi.org/10.46229/elia.v4i1.809

Mupinga, D. M. (2017).

School-wide and Classroom Policies on the Use of Mobile Technologies: An Exploratory Study

. Journal of Technology Studies, 43(2), 70–79. https://doi.org/10.21061/jots.v43i2.a.2

Muttaqin, T. (2018). Determinants of Unequal Access to and Quality of Education in Indonesia. Jurnal Perencanaan Pembangunan: The Indonesian Journal of Development Planning, 2(1), 1–23. https://doi.org/10.36574/jpp.v2i1.27

Ninghardjanti, P., Murtini, W., Hindrayani, A., & Sangka, K. B. (2023). Evaluation of the Smart Indonesia Program as a Policy to Improve Equality in Education. Sustainability (Switzerland), 15(6). https://doi.org/10.3390/su15065114

Petre, A. A., Dumitrache, L., Mareci, A., & Cioclu, A. (2025). The Urban–Rural Education Divide: A GIS-Based Assessment of the Spatial Accessibility of High Schools in Romania. ISPRS International Journal of Geo-Information, 14(5), 1–20. https://doi.org/10.3390/ijgi14050183

Rajput, N. H. (2020). Technology in action: Ascertaining the impact of cell phone calls on middle school students placed at risk of drop out. Indian Journal of Science and Technology, 13(40), 4224–4233. https://doi.org/10.17485/ijst/v13i40.1236

Rakhmah, B. I., Ari, I. R. D., & Rukmi, W. I. (2019). Spatial Modeling on Net Enrollment Rate of Junior High in Mataram. International Journal of Innovative Science and Research Technology, 4(7). www.ijisrt.com158

Savita, K. (2021). An Analytical Study of Education as a Human Capital and Investment for Economic Development of a Nation An Analytical Study of Education as a Human Capital and Investment for Economic Development of a Nation. November.

Stokes, C. S. (2015). HHS Public Access. 54(2), 295–319. https://doi.org/10.1086/652139.School

Susilo, H., & Wahyudi, S. T. (2020). Keeping rural children’s hope to stay in the Senior High School through conditional cash transfer: An Indonesian case. Sebelas Maret Business Review, 5(1), 1. https://doi.org/10.20961/smbr.v5i1.41197

Ulfa, M. F., & Rezki, J. F. (2024). Economics Development Analysis Journal The Impact of The Program Indonesia Pintar on School Participation. Economics Development Analysis Journal, 13(1), 140–151. http://journal.unnes.ac.id/sju/index.php/edaj

Wang, J. C., Hsieh, C. Y., & Kung, S. H. (2023). The impact of smartphone use on learning effectiveness: A case study of primary school students. In Education and Information Technologies (Vol. 28, Issue 6). Springer US. https://doi.org/10.1007/s10639-022-11430-9

Wells, R. S., Chen, L., Bettencourt, G. M., & Haas, S. (2023). Reconsidering Rural-Nonrural College Enrollment Gaps: The Role of Socioeconomic Status in Geographies of Opportunity. Research in Higher Education, 64(8), 1089–1112. https://doi.org/10.1007/s11162-023-09737-8

Winding, T. N., & Andersen, J. H. (2015). Socioeconomic differences in school dropout among young adults: The role of social relations. BMC Public Health, 15(1), 1–11. https://doi.org/10.1186/s12889-015-2391-0

Yngve, M., Ekbladh, E., Lidström, H., & Hemmingsson, H. (2023). Information and communication technology to improve school participation among upper secondary school students with special educational needs. Scandinavian Journal of Occupational Therapy, 30(3), 311–321. https://doi.org/10.1080/11038128.2021.1998610

Zakir, S., Hoque, M. E., Susanto, P., Nisaa, V., Alam, M. K., Khatimah, H., & Mulyani, E. (2025). Digital literacy and academic performance: the mediating roles of digital informal learning, self-efficacy, and students’ digital competence. Frontiers in Education, 10(June), 1–13. https://doi.org/10.3389/feduc.2025.1590274

Zangana, D. D., Ibrahim, A. J., Yuan, H., & Amani-Beni, M. (2024). Educational inequality in urban settings: A spatial analysis of school distribution and double-shift system challenges – A case study. Journal of Urban Management, 13(4), 832–849. https://doi.org/10.1016/j.jum.2024.08.004

Zhang, Z., Luan, W., Tian, C., & Su, M. (2025). Impact of Urban Expansion on School Quality in Compulsory Education: A Spatio-Temporal Study of Dalian, China. Land, 14(2). https://doi.org/10.3390/land14020265