Faktor-Faktor Penerimaan Pengguna Terhadap Teknologi Pengenalan Wajah: Sebuah Tinjauan Literatur Sistematis
DOI:
https://doi.org/10.33005/santika.v6i1.1095Keywords:
Teknologi Pengenalan Wajah, Tinjauan Literatur Sistematis, Penerimaan Teknologi, Penerimaan Pengguna, Kepercayaan pada TeknologiAbstract
Penelitian ini dilakukan dengan tujuan menganalisis faktor-faktor yang memengaruhi penerimaan pengguna terhadap teknologi pengenalan wajah yang diterapkan pada berbagai sistem melalui metode Tinjauan Literatur Sistematis. Terdapat sebanyak 20 artikel yang diterbitkan dalam periode tahun 2021 sampai dengan 2026 dianalisis secara sistematis berdasarkan kriteria inklusi dan eksklusi yang telah ditetapkan. Penerimaan terhadap teknologi pengenalan wajah sangat dipengaruhi oleh beberapa faktor utama. Faktor-faktor ini termasuk manfaat yang dirasakan dan kemudahan penggunaan. Kedua faktor ini berperan penting meningkatkan minat pengguna terhadap teknologi pengenalan wajah. Kepercayaan juga menjadi faktor penting yang mempengaruhi niat pengguna. Pengguna cenderung menerima teknologi pengenalan wajah jika merasa data biometrik mereka aman. Penelitian ini menggali persepsi masyarakat terhadap isu privasi dan keamanan terkait dengan penggunaan teknologi pengenalan wajah. Banyak pengguna khawatir terhadap risiko penyalahgunaan data biometrik. Persepsi terhadap tingkat keamanan yang ada dalam teknologi memainkan peran besar dalam keputusan pengguna mengadopsi teknologi pengenalan wajah. Kepercayaan terhadap penyedia layanan menjadi kunci utama dalam mengurangi kekhawatiran ini. Penelitian ini juga membahas mengenai tantangan dan hambatan utama yang dihadapi dalam penerimaan teknologi pengenalan wajah. Isu etika dan privasi menjadi hambatan terbesar dalam adopsi teknologi pengenalan wajah. Ketidakjelasan regulasi dan risiko kebocoran data menjadi kendala utama yang menghambat adopsi. Tantangan lain yang ditemukan adalah keterbatasan infrastruktur teknologi, bias algoritma, serta rendahnya literasi digital di kalangan pengguna. Hasil temuan penelitian ini diharapkan dapat memberikan kontribusi dalam pengembangan teknologi pengenalan wajah di masa mendatang, serta menjadi wawasan tambahan dan acuan bagi pengambil kebijakan dan pengembang aplikasi dalam meningkatkan adopsi pengguna terhadap teknologi pengenalan wajah.
References
A. Kaplan and M. Haenlein, “Rulers of the world, unite! The challenges and opportunities of artificial intelligence,” Bus. Horiz., vol. 63, no. 1,
pp. 37–50, Jan. 2020, doi: 10.1016/j.bushor.2019.09.003.
I. Adjabi, A. Ouahabi, A. Benzaoui, and A. Taleb-Ahmed, “Past, Present, and Future of Face Recognition: A Review,” Electronics (Basel)., vol. 9, no. 8, p. 1188, Jul. 2020, doi: 10.3390/electronics9081188.
H. Choung, P. David, and T.-W. Ling, “Acceptance of AI-powered facial recognition technology in surveillance scenarios: Role of trust, security, and privacy perceptions,” Technol. Soc., vol. 79, p. 102721, Dec. 2024, doi: 10.1016/j.techsoc.2024.102721.
T. Yu, C. Wang, Q. Bian, and A. P. Teoh, “Acceptance of or resistance to facial recognition payment: A systematic review,” Journal of Consumer Behaviour, vol. 23, no. 6, pp. 2933–2951, Nov. 2024, doi: 10.1002/cb.2385.
X. Wu, Z. Zhou, and S. Chen, “A mixed-methods investigation of the factors affecting the use of facial recognition as a threatening AI application,” Internet Research, vol. 34, no. 5, pp. 1872–1897, Sep. 2024, doi: 10.1108/INTR-11-2022-0894.
Aldi Bagus Hermawan, Keysya Alifia Zabina, M.Rafli Alfarisqi, and Seftin Fitri Ana Wati, “SYSTEMATIC LITERATURE REVIEW TENTANG MANAJEMEN PROYEK DALAM SISTEM
INFORMASI,” Prosiding Seminar Nasional Teknologi dan Sistem Informasi, vol. 3, no. 1, pp. 1–11, Nov. 2023, doi: 10.33005/sitasi.v3i1.453.
Nursalam et al., PEDOMAN PENYUSUNAN LITERATURE DAN
SYSTEMATIC REVIEW. Fakultas Keperawatan Universitas Airlangga, 2020.
D. Nan, Y. Kim, J. Huang, H. S. Jung, and J. H. Kim, “Factors Affecting Intention of Consumers in Using Face Recognition Payment in Offline Markets: An Acceptance Model for Future Payment Service,” Front. Psychol., vol. 13, Mar. 2022, doi: 10.3389/fpsyg.2022.830152.
C. Li and H. Li, “Disentangling facial recognition payment service usage behavior: A trust perspective,” Telematics and Informatics, vol. 77, Feb. 2023, doi: 10.1016/j.tele.2023.101939.
Y. Zhong, S. Oh, and H. C. Moon, “Service transformation under industry 4.0: Investigating acceptance of facial recognition payment through an extended technology acceptance model,” Technol. Soc., vol. 64, Feb. 2021, doi: 10.1016/j.techsoc.2020.101515.
Y. Zhang, “Impact of perceived privacy and security in the TAM model: The perceived trust as the mediated factors,” International Journal of Information Management Data Insights, vol. 4, no. 2, Nov. 2024, doi: 10.1016/j.jjimei.2024.100270.
M. Rukhiran, S. Wong-In, and P. Netinant, “User Acceptance Factors Related to Biometric Recognition Technologies of Examination Attendance in Higher Education: TAM Model,” Sustainability (Switzerland), vol. 15, no. 4, Feb. 2023, doi: 10.3390/su15043092.
M. Wang, Y. Kang, B. Deng, and X. Lan, “Exploring college students’ risk perception and acceptance intention of facial recognition technology in China,” Telematics and Informatics, vol. 95, Nov. 2024, doi: 10.1016/j.tele.2024.102193.
H. C. Boo and B. L. Chua, “An integrative model of facial recognition check-in technology adoption intention: the perspective of hotel guests in Singapore,” International Journal of Contemporary Hospitality Management, vol. 34, no. 11, pp. 4052–4079, Oct. 2022, doi: 10.1108/IJCHM-12-2021-1471.
T. Yu, A. P. Teoh, C. Wang, and Q. Bian, “Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals,” Humanit. Soc. Sci. Commun., vol. 11, no. 1, Dec. 2024, doi: 10.1057/s41599-024-03910-9.
W.-L. Shiau, C. Liu, X. Cheng, and W.-P. Yu, “Employees’ Behavioral Intention to Adopt Facial Recognition Payment to Service Customers,” Journal of Organizational and End User Computing, vol. 36, no. 1, pp. 1–32, Oct. 2024, doi: 10.4018/JOEUC.359894.
O. Ciftci, E. K. (Cindy) Choi, and K. Berezina, “Let’s face it: Are customers ready for facial recognition technology at quick-service restaurants?,” Int. J. Hosp. Manag., vol. 95, May 2021, doi: 10.1016/j.ijhm.2021.102941.
Y. W. Setiya Putra, “Implementasi Model TAM pada Sistem Informasi Presensi Online Menggunakan Face Recognition dan GPS,” Journal of Applied Computer Science and Technology, vol. 4, no. 2, pp. 147–154, Dec. 2023, doi: 10.52158/jacost.v4i2.577.
X. Lai and P. L. Patrick Rau, “Has facial recognition technology been misused? A user perception model of facial recognition scenarios,” Comput. Human Behav., vol. 124, Nov. 2021, doi: 10.1016/j.chb.2021.106894.
X. Cheng, L. Qiao, B. Yang, and X. Zhang, “Investigation on users’ resistance intention to facial recognition payment: a perspective of privacy,” Electronic Commerce Research, vol. 24, no. 1, pp. 275–301, Mar. 2024, doi: 10.1007/s10660-022-09588-y.
H. M. Kim, J. (Sunny) Kim, K. Joo, and J. Hwang, “Investigating the technology acceptance model, image congruence and cultural differences in facial recognition payment adoption,” Asia Pacific Journal of Marketing and Logistics, vol. 37, no. 1, pp. 20–41, Jan. 2025, doi: 10.1108/APJML-01-2024-0123.
T. Lyu, Y. Guo, and H. Chen, “Understanding people’s intention to use facial recognition services: the roles of network externality and privacy cynicism,” Information Technology and People, vol. 37, no. 3, pp. 1025–1051, Apr. 2024, doi: 10.1108/ITP-10-2021-0817.
V. T. Dang et al., “Consumer attitudes toward facial recognition payment: an examination of antecedents and outcomes,” International Journal of Bank Marketing, vol. 40, no. 3, pp. 511–535, Apr. 2022, doi: 10.1108/IJBM-04-2021-0135.
C. T. Lee and L. Y. Pan, “Resistance of facial recognition payment service: a mixed method approach,” Journal of Services Marketing, vol. 37, no. 3, pp. 392–407, Feb. 2023, doi: 10.1108/JSM-01-2022-0035.
H. T. Lim, A. Vafaei-Zadeh, H. Hanifah, and D. Nikbin, “Evaluating the benefits and risks of facial recognition payment systems adoption in Malaysia,” International Journal of Bank Marketing, vol. 43, no. 2,
pp. 292–320, Jan. 2025, doi: 10.1108/IJBM-05-2024-0300.
J. S. Wang, “Exploring biometric identification in FinTech applications based on the modified TAM,” Financial Innovation, vol. 7, no. 1, Dec. 2021, doi: 10.1186/s40854-021-00260-2.
M. Liu, C. Wang, and J. Hu, “Understanding older adults’ adoption of facial recognition payment: An integrated model of TAM and UXT,” PLoS One, vol. 20, no. 7 July, Jul. 2025, doi: 10.1371/journal.pone.0325291.
