Article Sidebar

Download
PDF
Statistic
Read Counter : 42 Download : 11

Main Article Content

Abstract

This study investigates the effect of social influence and price value on the behavior of high school students in using the Ruangguru educational application, with behavioral intention as a mediator. The research addresses the gap in understanding the adoption of digital learning platforms among Indonesian students, where usage decisions are often driven by contextual rather than purely psychological factors. A quantitative approach using PLS-SEM was employed, with data collected from 277 respondents through validated questionnaires (Cronbach’s α > 0.7, AVE > 0.5), chosen for its ability to test both direct and indirect relationships simultaneously. Results indicate that price value has a significant positive effect on user behavior (β = 0.421, t = 5.312, p < 0.001, R² = 0.46), while social influence (β = 0.097, p > 0.05) and behavioral intention (β = 0.083, p > 0.05) do not show significant effects. Descriptive analysis also revealed that 72% of students reported high satisfaction, and 68% expressed willingness to recommend the app, although this intention did not translate into actual usage behavior. These findings highlight that affordability and perceived benefits outweigh peer encouragement or intention in driving adoption, reflecting students’ sensitivity to price-value alignment in digital learning. The study implies that educational technology providers should prioritize accessible pricing strategies, though further research is needed to integrate other UTAUT2 constructs for a more comprehensive understanding.

Keywords

Behavior User Intention Price Values Ruangguru Social Influence

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Saputra, P. E., Manggabarani, A. S., & Saragih, G. S. (2026). Social Influence and Price Values on the Behavior of Ruang Guru Application Users Mediated by Intention. Ilomata International Journal of Social Science, 7(1), 71-86. https://doi.org/10.61194/ijss.v7i1.1912

References

  1. Abbad, M. M. (2021). Using the UTAUT model to understand students’ usage of e-learning systems. Education and Information Technologies, 26. https://doi.org/10.1007/s10639-021-10440-1
  2. Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Simintiras, A. C. (2023). Examining the role of intention–behavior gap in mobile learning adoption: Evidence from developing countries. Computers & Education, 195, 104672. https://doi.org/10.1016/j.compedu.2023.104672
  3. Alam, Md. S., Ahmad, N., Naveed, Q. N., Patel, A., Abohashrh, M., & Khaleel, M. A. (2022). E-learning services to achieve sustainable learning outcomes. Sustainability, 14(5). https://doi.org/10.3390/su14052671
  4. Al-Fraihat, D., Joy, M., Sinclair, J., & Masa’deh, R. (2020). Evaluating E-learning systems success. Computers in Human Behavior, 102. https://doi.org/10.1016/j.chb.2019.106272
  5. Alqahtani, M. A., & Rajkhan, A. A. (2020). E-learning critical success factors during COVID-19 pandemic. Education and Information Technologies, 25. https://doi.org/10.1007/s10639-020-10219-y
  6. Al-Rahmi, W. M., & al., et. (2022). Digital learning adoption and student engagement. Sustainability, 14(3). https://doi.org/10.3390/su14031536
  7. Bhikuning, D., Wasiati, H., & Rahmadani, A. N. (2024). Dampak Keputusan Investasi, Kinerja Keuntungan dan Komposisi Modal Terhadap Pencapaian Nilai Entitas Ritel (Sektor Supermarket dan Convenience Store) Yang Terdaftar di BEI Periode 2011-2022. Jurnal Ilmiah Global Education, 5(1), 76–91. https://doi.org/10.55681/jige.v5i1.2101
  8. Bond, M., & al., et. (2021). Emergency remote teaching in higher education: A systematic review. Educational Technology Research and Development, 69. https://doi.org/10.1007/s11423-021-10023-8
  9. Brailas, A., Koskinas, K., & Dafermos, M. (2021). Educational technology adoption and adolescent autonomy. Education and Information Technologies, 26. https://doi.org/10.1007/s10639-021-10485-2
  10. Chao, C.-M. (2019). Factors determining the behavioral intention to use mobile learning. Interactive Learning Environments, 27(1). https://doi.org/10.1080/10494820.2018.1481106
  11. Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2020). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 22(4), 987–1003. https://doi.org/10.1007/s10796-019-09971
  12. Hameed, A., & Sumari, M. (2024). Pricing fairness and adoption of paid educational technology. Journal of Educational Technology & Online Learning, 7(1).
  13. Ho, T.-H., & al., et. (2020). Examining consumers’ adoption intention of paid mobile learning services. Interactive Learning Environments, 28(6). https://doi.org/10.1080/10494820.2019.1703016
  14. Ikhsan, K., & Sunaryo, D. (2020). Technology Acceptance Model, Social Influence and Perceived Risk in Using Mobile Applications: Empirical Evidence in Online Transportation in Indonesia. Jurnal Dinamika Manajemen, 11(2), 127–138.
  15. Jainuri, N. & Y. H. (2021). PERANCANGAN DAN PEMBUATAN APLIKASI MOBILE POINT OF SALE PADA OUTLET MAKARONI JUDES BERBASIS ANDROID. Jurnal IPSIKOM, 9(2), 44–52.
  16. Juwairiyah, I., Andrianto, M., & Syafitri, R. (2022). Peran Perempuan dalam Membangun UMKM di Kota Tanjungpinang Article Info. Jurnal Hukum, Humaniora, Masyaratat, Dan Budaya, 2(2), 150–160. https://doi.org/10.33830/humayafhisip
  17. Kohnke, L., & Moorhouse, B. L. (2023). Adopting digital learning tools: Student motivation and intention in post-pandemic education. Education and Information Technologies, 28. https://doi.org/10.1007/s10639-023-11641-4
  18. Lewis, K. L., Howard, S. J., Verenikina, I., & Kervin, L. K. (2023). Parent perspectives on young children’s changing digital practices: Insights from Covid-19. Journal of Early Childhood Research, 21(1), 76–90. https://doi.org/10.1177/1476718X221145486
  19. Liu, Y., Zhang, H., & Li, X. (2025). Beyond intention: Understanding barriers to mobile learning adoption among high school students. Educational Technology Research and Development, 73(2), 421–440. https://doi.org/10.1007/s11423-025-10234-1
  20. Martin, F., & Bolliger, D. U. (2022). Engagement matters: Student perceptions on the importance of engagement strategies in online learning. Online Learning Journal, 26(1). https://doi.org/10.24059/olj.v26i1.2595
  21. Nguyen Trong, N., & Nguyen, C. T. (2021). Firm performance: the moderation impact of debt and dividend policies on overinvestment. Journal of Asian Business and Economic Studies, 28(1), 47–63. https://doi.org/10.1108/JABES-12-2019-0128
  22. Nurrisa, F., Hermina, D., & Norlaila. (2025). Pendekatan Kualitatif dalam Penelitian: Strategi, Tahapan, dan Analisis Data. Jurnal Teknologi Pendidikan Dan Pembelajaran (JTPP), 02(03), 793–800.
  23. Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2021). Does e-learning service quality influence e-learning student satisfaction and loyalty? Education and Information Technologies, 26. https://doi.org/10.1007/s10639-020-10330-y
  24. Rahman, Md. M., & al., et. (2021). Determinants of students’ adoption of paid e-learning platforms. Education and Information Technologies, 26. https://doi.org/10.1007/s10639-021-10462-9
  25. Rasheed, R. A., Kamsin, A., & Abdullah, N. A. (2022). Challenges in the online component of blended learning: A systematic review. Computers & Education, 181. https://doi.org/10.1016/j.compedu.2022.104444
  26. Robiul Rochmawati, D., Hatimatunnisani, H., & Veranita, M. (2023). Mengembangkan Strategi Bisnis di Era Transformasi Digital. Coopetition : Jurnal Ilmiah Manajemen, 14(1), 101–108. https://doi.org/10.32670/coopetition.v14i1.3076
  27. Salloum, S. A., & al., et. (2020). Factors affecting the adoption of e-learning systems in higher education. Education and Information Technologies, 25. https://doi.org/10.1007/s10639-020-10157-9
  28. Sheeran, P. (2002). Intention–behavior relations: A conceptual and empirical review. European Review of Social Psychology, 12(1), 1–36. https://doi.org/10.1080/14792772143000003
  29. Siron, Y., Wibowo, A., & Narmaditya, B. S. (2020). Factors affecting the adoption of e-learning in higher education. Journal of Educational Technology Systems, 49(2). https://doi.org/10.1177/0047239520934017
  30. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2020). Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead. Journal of the Association for Information Systems, 21(3).
  31. Yakubu, M. N., & Dasuki, S. I. (2022). Assessing the role of perceived value in students’ intention to use e-learning systems. Heliyon, 8(1). https://doi.org/10.1016/j.heliyon.2022.e08754
  32. Zacharis, G., & Nikolopoulou, K. (2022). Factors predicting University students’ behavioral intention to use eLearning platforms in the post-pandemic normal: an UTAUT2 approach with “Learning Value.” Education and Information Technologies, 27, 12065–12082. https://doi.org/10.1007/s10639-022-11116-2