DOI: https://doi.org/10.14710/jmki.12.1.2024.14-24

FAKTOR YANG MEMPENGARUHI NIAT PENGGUNAAN (INTENTION TO USE) LAYANAN TELEKONSULTASI APLIKASI HALODOC PADA MASYARAKAT INDONESIA

*Hansa Nurhaida orcid  -  Fakultas Kedokteran, Universitas Indonesia, Indonesia
Eka Pramudita orcid  -  Fakultas Ekonomi dan Bisnis, Universitas Pelita Harapan, Indonesia
Hendra Achmadi orcid  -  Fakultas Ekonomi dan Bisnis, Universitas Pelita Harapan, Indonesia

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Abstract

Telemedicine is a technology-based service in the health sector without having distance as an issue. One of the services offered in the telemedicine sector is teleconsultation. This service allows doctors to provide consultation services, diagnostic services and treatment management without meeting face to face with patients. Halodoc application is one of the teleconsultation service providers. In Indonesia, The development of telemedicine is growing rapidly along with the phenomenon of the 2019 coronavirus disease (COVID-19) pandemic. During the COVID-19 pandemic, the Ministry of Health collaborated with health platforms to provide telemedicine services for COVID-19 patients with mild to moderate symptoms in self-isolation (ISOMAN). Currently the status of the COVID-19 pandemic has shifted. As a result outdoor activities and face-to-face medical services will again become an option for Indonesian society. Health technology applications must carry out self-evaluation and development to maintain their market. In Indonesia, Halodoc is the most superior application of its group. This research aims to determine the relationship between the intention to use teleconsultation services with other variables such as Subjective Health Status, Perceived Privacy and Security and Effort Expectancy. This research was conducted using an 1-5 likert scale online questionnaire involving 162 respondents who had used the Halodoc teleconsultation service. Samples were obtained using a purposive sampling method and then processed using SmartPLS 3rd version for Windows. Based on the result, Subjective Health Status did not have a positive influence on the intention to use teleconsultation. However, Perceived Privacy and Security and Effort Expectancy have a positive influence on the intention to use Halodoc teleconsultation services.

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Keywords: Intention To Use, Teleconsultation, Telemedicine, Subjective Health Status, Effort Expectancy, Perceived Privacy and Security, Halodoc, Modified TAM,

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  1. Deldar K, Bahaadinbeigy K, Tara SM. Teleconsultation and Clinical Decision Making: a Systematic Review. Acta Inform Med [Internet]. 2016 [cited 2023 Sep 25];24(4):286–92. Available from: https://pubmed.ncbi.nlm.nih.gov/27708494/
  2. World Health Organization. Intra-action Review of Indonesia’s Response to COVID-19: Summary Report for partners, August 2020 [Internet]. World Health Organization. Jakarta: World Health Organization; 2021 [cited 2023 Sep 25]. Available from: https://cdn.who.int/media/docs/default-source/searo/indonesia/intra-action-review-report-of-indonesia-s-response-to-covid-19.pdf?sfvrsn=d3756cbc_1&download=true
  3. Peraturan Menteri Kesehatan No. 46 Tahun 2017 tentang Strategi E-kesehatan Nasional [Internet]. Menteri Kesehatan Republik Indonesia. 2017 [cited 2023 Sep 25]. Available from: https://peraturan.bpk.go.id/Details/139565/permenkes-no-46-tahun-2017
  4. Peraturan Menteri Kesehatan No. 20 Tahun 2019 tentang Penyelenggaraan Pelayanan Telemedicine antar Fasilitas Pelayanan Kesehatan [Internet]. Menteri Kesehatan Republik Indonesia. 2019 [cited 2023 Sep 25]. Available from: https://peraturan.bpk.go.id/Details/138613/permenkes-no-20-tahun-2019
  5. Pusparisa Y. Indonesia Peringkat ke-3 Global Memanfaatkan Aplikasi Kesehatan [Internet]. Databoks. 2020 [cited 2023 Sep 25]. Available from: https://databoks.katadata.co.id/datapublish/2020/10/13/indonesia-peringkat-ke-3-global-memanfaatkan-aplikasi-kesehatan
  6. Annur CM. Layanan Telemedicine yang Paling Banyak Digunakan di Indonesia, Apa Saja? [Internet]. databoks. 2022 [cited 2023 Sep 25]. Available from: https://databoks.katadata.co.id/datapublish/2022/04/07/layanan-telemedicine-yang-paling-banyak-digunakan-di-indonesia-apa-saja
  7. Isnaini R. Skripsi Analisis Kepuasan Pengguna Aplikasi Halodoc Di Masa Pandemi Dengan Menggunakan Model End User Computing Satisfaction (Eucs). [Jakarta]: Universitas Islam Negeri Syarif Hidayatullah; 2022
  8. Van Houwelingen CTM, Ettema RGA, Antonietti MGEF, Kort HSM. Understanding Older People’s Readiness for Receiving Telehealth: Mixed-Method Study. J Med Internet Res [Internet]. 2018 Apr 1 [cited 2023 Sep 25];20(4). Available from: https://pubmed.ncbi.nlm.nih.gov/29625950/
  9. Murhum N, Durachman Y, Fetrina E. Pengukuran Penerimaan Pengguna Pada Aplikasi Kesehatan Halodoc dengan Menggunakan Model Unified Theory Of Acceptance And Use Of Technology 2. Jurnal SNATI. 2022;1(2):24–31
  10. Venkatesh V, Thong JYL, Xu X. Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly. 2012;36:157–78
  11. Davis F. A Technology Acceptance Model for Empirically Testing New End-User Information Systems [Thesis (Ph.D.)]. Massachusetts Institute of Technology; 1985
  12. Aggelidis VP, Chatzoglou PD. Using a modified technology acceptance model in hospitals. Int J Med Inform [Internet]. 2009 Feb [cited 2023 Sep 25];78(2):115–26. Available from: https://pubmed.ncbi.nlm.nih.gov/18675583/
  13. Kang EK, Lee H, Hong KJ, Yun J, Lee JY, Hong YC. The general public’s perspectives on telemedicine during the COVID-19 pandemic in Korea: analysis of a nationwide survey. Epidemiol Health [Internet]. 2022 [cited 2023 Sep 25];44. Available from: /pmc/articles/PMC9117104/
  14. Gataūlinas A, Banceviča M. Subjective Health and Subjective Well-Being (The Case of EU Countries). Adv Appl Sociol. 2014;04(09):212–23
  15. Peek STM, Wouters EJM, van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJM. Factors influencing acceptance of technology for aging in place: a systematic review. Int J Med Inform [Internet]. 2014 Apr [cited 2023 Sep 25];83(4):235–48. Available from: https://pubmed.ncbi.nlm.nih.gov/24529817/
  16. Wang Q, Sun X. Investigating gameplay intention of the elderly using an Extended Technology Acceptance Model (ETAM). Technol Forecast Soc Change. 2016 Jun 1;107:59–68
  17. Shin DH. The effects of trust, security and privacy in social networking: A security-based approach to understand the pattern of adoption. Interact Comput. 2010;22(5):428–38
  18. Mekovec R, Hutinski Z. The role of perceived privacy and perceived security in online market. 2012 Proceedings of the 35th International Convention MIPRO. 2012;
  19. Venkatesh V, Aloysius JA, Hoehle H, Burton S. Two Retail Store Laboratory Experiments. MIS Quarterly [Internet]. 2017;41(1):83–114. Available from: https://www.jstor.org/stable/26629638
  20. Kim B, Lee E. What Factors Affect a User’s Intention to Use Fitness Applications? The Moderating Effect of Health Status: A Cross-Sectional Study. Inquiry [Internet]. 2022 Apr 1 [cited 2023 Sep 25];59. Available from: https://pubmed.ncbi.nlm.nih.gov/35580021/
  21. Venkatesh V, Morris MG, Davis GB, Davis FD. User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly. 2003;27:425–78
  22. Yamin MAY, Alyoubi BA. Adoption of telemedicine applications among Saudi citizens during COVID-19 pandemic: An alternative health delivery system. J Infect Public Health [Internet]. 2020 Dec 1 [cited 2023 Sep 25];13(12):1845–55. Available from: https://pubmed.ncbi.nlm.nih.gov/33172819/
  23. Molfenter T, Roget N, Chaple M, Behlman S, Cody O, Hartzler B, et al. Use of Telehealth in Substance Use Disorder Services During and After COVID-19: Online Survey Study. JMIR Ment Health [Internet]. 2021 Feb 1 [cited 2023 Sep 25];8(2). Available from: /pmc/articles/PMC7895293/
  24. Hair JF, Risher JJ, Sarstedt M, Ringle CM. When to use and how to report the results of PLS-SEM. European Business Review. 2019 Mar;31:2–24
  25. Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci. 2015 Mar;43:115–35
  26. De Veer AJE, Peeters JM, Brabers AEM, Schellevis FG, Rademakers JJDJM, Francke AL. Determinants of the intention to use e-Health by community dwelling older people. BMC Health Serv Res [Internet]. 2015 Mar 15 [cited 2023 Sep 25];15(1). Available from: /pmc/articles/PMC4364096/
  27. Alviani R, Purwandari B, Eitiveni I, Purwaningsih M. Factors Affecting Adoption of Telemedicine for Virtual Healthcare Services in Indonesia. Journal of Information Systems Engineering and Business Intelligence [Internet]. 2023 Apr 28 [cited 2023 Sep 25];9(1):47–69. Available from: https://e-journal.unair.ac.id/JISEBI/article/view/41371
  28. Lee W-I, Fu H-P, Mendoza N, Liu T-Y. Determinants Impacting User Behavior towards Emergency Use Intentions of m-Health Services in Taiwan. Healthcare. 2021 Mar;9:535

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