Article Sidebar

Submitted
19 June 2025
Accepted
16 October 2025
Published
30 December 2025
Download
PDF
Statistic
Read Counter : 284 Download : 152

Main Article Content

Abstract

Digital transformation has become a prominent topic in the era of globalization. Despite the growing digital transformation trend, many health service users in Indonesia still prefer face-to-face interactions, indicating a gap in digital literacy and service adoption. In response to this issue, the Social Security Administrative Body for Health launched a digital administrative service called Pandawa (Administrative Service via WhatsApp). This study aims to explore the perceptions of National Health Insurance participants who visited Social Security Administrative Body for Health Depok in 2025, focusing on the perceived ease of use and usefulness of the Pandawa service. The research employs a quantitative approach using the Technology Acceptance Model (TAM) through a cross-sectional study design. The secondary data used in this study consists of participant visits to the agency in 2024. Primary data will also be needed through distributed questionnaires. The sample consists of 109 National Health Insurance participants who are users of the Pandawa service and visited the agency during the study, conducted in February 2025. The analysis techniques of the research used the Chi-Square Test and the Binary Logistic Regression Test. The multivariate analysis shows that age, education, perceived ease of use, perceived usefulness, and attitude are significantly related to the intention to use the Pandawa service, with attitude being the dominant factor. Meanwhile, sex does not show a significant relationship to the intention to use the Pandawa service. Overall, user acceptance of the Pandawa service is relatively good, although further improvements in service quality are necessary to optimize its implementation.

Keywords

Acceptance Digital Services Pandawa Perception technology Acceptance Model (TAM)

Article Details

Creative Commons License

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

How to Cite
Yoam, C. H. A., Pujiyanto, Atik Nurwahyuni, & Damaryanti, L. (2025). Technology Acceptance Model Toward Pandawa Service at the Social Security Administrative Body for Health Depok. Jurnal Jaminan Kesehatan Nasional, 5(2), 215–227. https://doi.org/10.53756/jjkn.v5i2.367
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Abbas, S., Koo, A., & Szabo, Z. (2022). Shopping using mobile applications and the role of the technology acceptance model: Purchase intention and social factors. Hungarian Statistical Review, 2(5), 54–81. https://doi.org/10.35618/HSR2022.02.en054
  2. Abu-Taieh, E. M., AlHadid, I., Abu-Tayeh, S., Masa’deh, R., Alkhawaldeh, R. S., Khwaldeh, S., & Alrowwad, A. (2022). Continued intention to use of m-banking in Jordan by integrating UTAUT, TPB, TAM and service quality with ML. Journal of Open Innovation: Technology, Market, and Complexity, 8(3), 120. https://doi.org/10.3390/joitmc8030120
  3. Adyas, A. (2021). The Indonesian strategy to achieve universal health coverage through national health insurance system: Its challenges in human resources. Kesmas: National Public Health Journal, 16(4). https://doi.org/10.21109/kesmas.v16i4.5440
  4. Aguilera-Hermida, A. P. (2020). College students’ use and acceptance of emergency online learning due to COVID-19. International Journal of Educational Research Open, 1, 100011. https://doi.org/10.1016/j.ijedro.2020.100011
  5. Alassafi, M. O. (2021). E-learning intention material using TAM: A case study. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2021.09.457
  6. Alfadda, H. A., & Mahdi, H. S. (2021). Measuring students’ use of Zoom application in language course based on the technology acceptance model (TAM). Journal of Psycholinguistic Research, 50(4), 883–900. https://doi.org/10.1007/s10936-020-09752-1
  7. Alghamdi, A. M., Alsuhaymi, D. S., Alghamdi, F. A., Farhan, A. M., Shehata, S. M., & Sakoury, M. M. (2021). University students’ behavioral intention and gender differences toward the acceptance of shifting regular field training courses to e-training courses. Education and Information Technologies, 27(1), 451–468. https://doi.org/10.1007/s10639-021-10701-1
  8. Al-Maatouk, Q., et al. (2020). Task-technology fit and technology acceptance model application to structure and evaluate the adoption of social media in academia. IEEE Access, 8, 78427–78440. https://doi.org/10.1109/access.2020.2990420
  9. Alnemer, H. A. (2022). Determinants of digital banking adoption in the Kingdom of Saudi Arabia: A technology acceptance model approach. Digital Business, 2(2), 100037. https://doi.org/10.1016/j.digbus.2022.100037
  10. Asosiasi Penyelenggara Jasa Internet Indonesia (APJII). (2024). Jumlah pengguna internet Indonesia tembus 221 juta orang. https://apjii.or.id/berita/d/apjii-jumlah-pengguna-internet-indonesia-tembus-221-juta-orang
  11. Badan Penyelenggara Jaminan Sosial Kesehatan. (2025). Layanan informasi dan administrasi. https://bpjs-kesehatan.go.id/#/
  12. Badan Penyelenggara Jaminan Sosial Kesehatan. (2025). Panduan layanan bagi peserta jaminan kesehatan nasional kartu Indonesia sehat (JKN-KIS). Jakarta Pusat: BPJS Kesehatan.
  13. Badan Penyelenggara Jaminan Sosial Kesehatan. (2025). Sejarah BPJS Kesehatan. https://www.bpjs-kesehatan.go.id/#/profil?tab=sejarah
  14. Bahri, S., & Amri, S. (2022). Analisis kualitas pelayanan aplikasi mobile JKN BPJS Kesehatan menggunakan metode service quality (SERVQUAL). Aceh: Universitas Malikussaleh.
  15. Dhagarra, D., Goswami, M., & Kumar, G. (2020). Impact of trust and privacy concerns on technology acceptance in healthcare: An Indian perspective. International Journal of Medical Informatics, 141, 104164. https://doi.org/10.1016/j.ijmedinf.2020.104164
  16. Disdukcapil Kota Depok. (2025). Layanan administrasi kependudukan kota Depok. https://disdukcapil.jabarprov.go.id/files/dokumen/layanan/3276.pdf
  17. Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y
  18. Fauziyah, N. (2019). Analisis data menggunakan multiple logistic regression test di bidang kesehatan masyarakat dan klinis. Bandung: Politeknik Kesehatan Kemenkes.
  19. Fussell, S. G., & Truong, D. (2021). Using virtual reality for dynamic learning: An extended technology acceptance model. Virtual Reality, 26(1). https://doi.org/10.1007/s10055-021-00554-x
  20. Gupta, M. (2018). Data entry management: A guide to efficient data handling. Tech Publications.
  21. Hanafi, T., & Nina, S. (2023). Hubungan persepsi manfaat, persepsi kemudahan, dan minat dengan pemanfaatan aplikasi Pandawa di wilayah kerja BPJS Cabang Tangerang tahun 2023. Dohara Publisher Open Access Journal, 3.
  22. Jayanthi, R., & Dinaseviani, A. (2022). Kesenjangan digital dan solusi yang diterapkan di Indonesia selama pandemi COVID-19. Badan Riset dan Inovasi Nasional, 24(2).
  23. Kasoju, N., Remya, N. S., Sasi, R., Sujesh, S., Soman, B., Kesavadas, C., Muraleedharan, C. V., Varma, P. R., & Behari, S. (2023). Digital health: Trends, opportunities, and challenges in medical devices, pharma and bio-technology. CSI Transactions on ICT, 11, 11–30.
  24. Lazim, C., Ismail, N., & Tazilah, M. (2021). Application of technology acceptance model (TAM) towards online learning during Covid-19 pandemic: Accounting students perspective. International Journal of Business, Economics and Law, 24(1).
  25. Lebang, C. G., et al. (2023). Transformasi digital Indonesia: Kondisi terkini dan proyeksi. Jakarta: Laboratorium Indonesia 2045.
  26. Li, K. (2023). Determinants of college students’ actual use of AI-based systems: An extension of the technology acceptance model. Sustainability, 15(6), 5221. https://doi.org/10.3390/su15065221
  27. Marliani, L. (2019). Definisi administrasi dalam berbagai sudut pandang. Dinamika: Jurnal Ilmiah Ilmu Administrasi Negara, 5(4), 17–21. https://doi.org/10.25157/dinamika.v5i4.1743
  28. Mohd Tanos, M. M., Man, N., & Mohd Nawi, N. (2024). Perceived ease of use, perceived usefulness, and intention to use e-commerce platforms by agribusiness owners in Malaysia: A review. International Journal of Academic Research in Business and Social Sciences, 14(2). https://doi.org/10.6007/ijarbss/v14-i2/20488
  29. Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y. (2022). Acceptance model of artificial intelligence (AI)-based technologies in construction firms: Applying the technology acceptance model (TAM) in combination with the technology–organisation–environment (TOE) framework. Buildings, 12(2), 90. https://www.mdpi.com/2075-5309/12/2/90
  30. Namahoot, K. S., & Rattanawiboonsom, V. (2022). Integration of TAM model of consumers’ intention to adopt cryptocurrency platform in Thailand: The mediating role of attitude and perceived risk. Human Behavior and Emerging Technologies, 2022, 1–12. https://doi.org/10.1155/2022/9642998
  31. Nnaji, C. (2023). A systematic review of technology acceptance models and theories in construction research. Journal of Information Technology in Construction, 28.
  32. Nurmitasari, S., Syarifah, I., & Hernando, H. (2023). Service effectiveness of Pandawa BPJS Kesehatan in Nganjuk Regency. Madiun: Politeknik Negeri Madiun.
  33. Panergayo, A. A. E., & Aliazas, J. V. C. (2021). Students’ behavioral intention to use learning management system: The mediating role of perceived usefulness and ease of use. International Journal of Information and Education Technology, 11(11), 538–545. https://doi.org/10.18178/ijiet.2021.11.11.1562
  34. Prameswari, P., & Sarno, R. (2021). Technology acceptance model analysis of m-banking using UTAUT 2 method. In Proceedings of the 3rd International Conference on Business and Management of Technology (ICONBMT 2021) (p. 202).
  35. Prastiawan, D. I., Aisjah, S., & Rofiaty, R. (2021). The effect of perceived usefulness, perceived ease of use, and social influence on the use of mobile banking through the mediation of attitude toward use. Asia Pacific Management and Business Application, 9(3), 243–260. https://doi.org/10.21776/ub.apmba.2021.009.03.4
  36. Pratiwi, A. B., Setiyaningsih, H., Kok, M. O., Hoekstra, T., Mukti, A. G., & Pisani, E. (2021). Is Indonesia achieving universal health coverage? Secondary analysis of national data on insurance coverage, health spending and service availability. BMJ Open, 11(10), e050565. https://doi.org/10.1136/bmjopen-2021-050565
  37. Rawashdeh, A. M., et al. (2021). Electronic human resources management perceived usefulness, perceived ease of use and continuance usage intention: The mediating role of user satisfaction in Jordanian hotels sector. International Journal for Quality Research, 15(2), 679–696. https://doi.org/10.24874/ijqr15.02-20
  38. Rosli, M. S., et al. (2022). A systematic review of the technology acceptance model for the sustainability of higher education during the COVID-19 pandemic and identified research gaps. Sustainability, 14(18), 11389. https://doi.org/10.3390/su141811389
  39. Sarjiyati, Sukarjono, B., Purwati, Y., & Rosada, Y. S. (2022). Kualitas pelayanan Badan Penyelenggara Jaminan Sosial Kesehatan perspektif Undang-Undang Nomor 24 Tahun 2011 (studi di Kota Madiun). Yustisia Merdeka: Jurnal Ilmiah Hukum, 8(2), 64–80. https://doi.org/10.33319/yume.v8i2.184
  40. Shamsi, M., Iakovleva, T., Olsen, E., & Bagozzi, R. P. (2021). Employees’ work-related well-being during COVID-19 pandemic: An integrated perspective of technology acceptance model and JD-R theory. International Journal of Environmental Research and Public Health, 18(22), 11888. https://doi.org/10.3390/ijerph182211888
  41. Siagian, H., Tarigan, Z. J. H., Basana, S. R., & Basuki, R. (2022). The effect of perceived security, perceived ease of use, and perceived usefulness on consumer behavioral intention through trust in digital payment platform. International Journal of Data and Network Science, 6(3), 861–874. https://doi.org/10.5267/j.ijdns.2022.2.010
  42. Status literasi digital di Indonesia 2021. (2021). https://cdn1.katadata.co.id/media/microsites/litdik/Status_Literasi_Digital_diIndonesia%20_2021_190122.pdf
  43. Sukartini, T., Arifin, H., Kurniawati, Y., Pradipta, R. O., Nursalam, N., & Acob, J. R. U. (2021). Factors associated with national health insurance coverage in Indonesia. F1000Research, 10, 563. https://doi.org/10.12688/f1000research.53672.1
  44. Sukendro, S., et al. (2020). Using an extended technology acceptance model to understand students’ use of e-learning during COVID-19: Indonesian sport science education context. Heliyon, 6(11), e05410. https://doi.org/10.1016/j.heliyon.2020.e05410
  45. To, A. T., & Trinh, T. H. M. (2021). Understanding behavioral intention to use mobile wallets in Vietnam: Extending the TAM model with trust and enjoyment. Cogent Business & Management, 8(1), 1891661. https://doi.org/10.1080/23311975.2021.1891661
  46. Undang-Undang Nomor 24 Tahun 2011 tentang Badan Penyelenggara Jaminan Sosial.
  47. Undang-Undang Nomor 40 Tahun 2004 tentang Sistem Jaminan Sosial Nasional.
  48. van Elburg, F. R. T., Klaver, N. S., Nieboer, A. P., & Askari, M. (2022). Gender differences regarding intention to use mHealth applications in the Dutch elderly population: A cross-sectional study. BMC Geriatrics, 22(1). https://doi.org/10.1186/s12877-022-03130-3
  49. Vărzaru, A. A., Bocean, C. G., Rotea, C. C., & Budică-Iacob, A.-F. (2021). Assessing antecedents of behavioral intention to use mobile technologies in e-commerce. Electronics, 10(18), 2231. https://doi.org/10.3390/electronics10182231
  50. Wang, C., Ahmad, S., Ayassrah, A., Al-Razgan, M., Khan, Y., & Han, H. (2023). An empirical evaluation of technology acceptance model for artificial intelligence in e-commerce. Heliyon, 9(8).
  51. Wang, E. Y., Qian, D., Zhang, L., Li, B. S.-K., Ko, B., Khoury, M., Renavikar, M., Ganesan, A., & Caruso, T. J. (2024). Acceptance of virtual reality in trainees using a technology acceptance model: Survey study. JMIR Medical Education, 10, e60767. https://doi.org/10.2196/60767
  52. Yuliantini, L. S., & Sukarno, M. (2023). The Twitter sentiment analysis of public service innovation: Pandawa BPJS Health Service. Proceedings of the University of Muhammadiyah Yogyakarta Undergraduate Conference, 3(1), 146–153. https://doi.org/10.18196/umygrace.v3i1.543