Pengaruh Technology Readiness Dan Satisfaction Terhadap Penerimaan Penggunaan Safe Entry Station

The Influence of Technology Readiness and Satisfaction on Acceptance of Use Safe Entry Station


  • Gelard Godwin Rey Incorporation
  • Berlin Any Eduaward Incorporation
  • Ariana Delhi Mfinitee Incorporation
  • Po Abas Sunarya Universitas Raharja
  • Gabriela Nicola Pandawan Incorporation



The development of artificial intelligence technology has brought transformation in various sectors, including the world of health. The integration of AI in the healthcare sector has opened up new opportunities to improve diagnosis, treatment, medical data management and medical research. Safe Entry Station (SES-UR) is one of the newest technologies that has been introduced in the era of technological development that relies on the concept of artificial intelligence as the basis of its functionality, which has emerged as an innovative breakthrough in monitoring health effectively and accurately. However, new technology often involves concepts that may not yet familiar to most users. This can cause uncertainty and discomfort in using the technology. The aim of this research is to ensure that the implementation of SES-UR is successful and sustainable, so a comprehensive approach is needed in assessing the level of Technology Readiness and measuring the level of Satisfaction. The selected research focus is in the medical health sector to improve the quality of Artificial Intelligence-based health services. This research method, using the PLS-Structural Equation Modeling (SEM) method, was adopted to analyze the relationship between complex variables. To achieve accurate analysis results, this research involved the use of 25 instruments and 7 relevant constructs. The results of this research state that individuals who have a high level of Innovativeness tend to have the perception that the Safe Entry Station is easy to use, so they are more likely to accept and use this technology.


Q. Aini, W. Febriani, C. Lukita, S. Kosasi, and U. Rahardja, “New normal regulation with face recognition technology using attendx for student attendance algorithm,” in 2022 International Conference on Science and Technology (ICOSTECH), IEEE, 2022, pp. 1–7.

A. Verma and V. Ranga, “Machine learning based intrusion detection systems for IoT applications,” Wirel Pers Commun, vol. 111, pp. 2287–2310, 2020.

A. Bhawiyuga, S. A. Kharisma, B. J. Santoso, D. P. Kartikasari, and A. P. Kirana, “Cloud-based middleware for supporting batch and stream access over smart healthcare wearable device,” Bulletin of Electrical Engineering and Informatics, vol. 9, no. 5, pp. 1990–1997, 2020.

K.-C. Chang, K.-C. Chu, H.-C. Wang, Y.-C. Lin, and J.-S. Pan, “Agent-based middleware framework using distributed CPS for improving resource utilization in smart city,” Future Generation Computer Systems, vol. 108, pp. 445–453, 2020.

Q. Aini, N. Azizah, R. Salam, N. P. L. Santoso, and F. P. Oganda, “Skema Kredibilitas Sertifikat Berbasis Ilearning Gamifikasi Blockchain pada Kampus Merdeka,” Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 10, no. 1, pp. 203–214, 2023.

B. Rawat, N. Mehra, A. S. Bist, M. Yusup, and Y. P. A. Sanjaya, “Quantum computing and ai: Impacts & possibilities,” ADI Journal on Recent Innovation, vol. 3, no. 2, pp. 202–207, 2022.

U. Rahardja, Q. Aini, D. Manongga, I. Sembiring, and Y. P. A. Sanjaya, “Enhancing Machine Learning with Low-Cost P M2. 5 Air Quality Sensor Calibration using Image Processing,” APTISI Transactions on Management, vol. 7, no. 3, pp. 201–209, 2023.

N. Jasti et al., “Medical Applications of Infrared Thermography: A Narrative Review.,” J Stem Cells, vol. 14, no. 1, 2019.

N. Lutfiani, S. Wijono, U. Rahardja, A. Iriani, Q. Aini, and R. A. D. Septian, “A bibliometric study: Recommendation based on artificial intelligence for ilearning education,” Aptisi Transactions on Technopreneurship (ATT), vol. 5, no. 2, pp. 109–117, 2023.

U. Rahardja, C. T. Sigalingging, P. O. H. Putra, A. Nizar Hidayanto, and K. Phusavat, “The impact of mobile payment application design and performance attributes on consumer emotions and continuance intention,” Sage Open, vol. 13, no. 1, p. 21582440231151920, 2023.

U. Rahardja, S. Sudaryono, N. P. L. Santoso, A. Faturahman, and Q. Aini, “Covid-19: Digital Signature Impact on Higher Education Motivation Performance,” International Journal of Artificial Intelligence Research, vol. 4, no. 1, pp. 65–74, 2020.

D. Manongga, U. Rahardja, I. Sembiring, N. Lutfiani, and A. B. Yadila, “Dampak Kecerdasan Buatan Bagi Pendidikan,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 3, no. 2, pp. 41–55, 2022.

U. Rahardja, I. D. Hapsari, P. O. H. Putra, and A. N. Hidayanto, “Technological readiness and its impact on mobile payment usage: A case study of go-pay,” Cogent Eng, vol. 10, no. 1, p. 2171566, 2023.

R. Vaishya, M. Javaid, I. H. Khan, and A. Haleem, “Artificial Intelligence (AI) applications for COVID-19 pandemic,” Diabetes & Metabolic Syndrome: Clinical Research & Reviews, vol. 14, no. 4, pp. 337–339, 2020.

M. Yusup, E. Sukmawati, R. Ramadhan, and M. I. Suhaepi, “Blockchain Technology for Cashless Investments and Transactions in Digital Era With SWOT Approach,” Blockchain Frontier Technology, vol. 2, no. 1, pp. 17–23, 2022.

M. E. H. Chowdhury et al., “Can AI help in screening viral and COVID-19 pneumonia?,” Ieee Access, vol. 8, pp. 132665–132676, 2020.

S. Shukla and P. Arora, “Design and comparative analysis of aluminum-MoS2 based plasmonic devices with enhanced sensitivity and Figure of Merit for biosensing applications in the near-infrared region,” Optik (Stuttg), vol. 228, p. 166196, 2021.

S. Lalmuanawma, J. Hussain, and L. Chhakchhuak, “Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review,” Chaos Solitons Fractals, vol. 139, p. 110059, 2020.

K. M. C. Malecki, J. A. Keating, and N. Safdar, “Crisis communication and public perception of COVID-19 risk in the era of social media,” Clinical infectious diseases, vol. 72, no. 4, pp. 697–702, 2021.

G. Fersi, “Study of middleware for Internet of healthcare things and their applications,” in The Impact of Digital Technologies on Public Health in Developed and Developing Countries: 18th International Conference, ICOST 2020, Hammamet, Tunisia, June 24–26, 2020, Proceedings 18, Springer, 2020, pp. 223–231.

A. Mavrogiorgou, A. Kiourtis, and D. Kyriazis, “A pluggable IoT middleware for integrating data of wearable medical devices,” Smart Health, vol. 26, p. 100326, 2022.

Y. A. Qadri, A. Nauman, Y. Bin Zikria, A. V Vasilakos, and S. W. Kim, “The future of healthcare internet of things: a survey of emerging technologies,” IEEE Communications Surveys & Tutorials, vol. 22, no. 2, pp. 1121–1167, 2020.

S. L. Ullo and G. R. Sinha, “Advances in smart environment monitoring systems using IoT and sensors,” Sensors, vol. 20, no. 11, p. 3113, 2020.

L. Xu, J. Du, B. Song, and M. Cao, “A combined backstepping and fractional-order PID controller to trajectory tracking of mobile robots,” Systems Science & Control Engineering, vol. 10, no. 1, pp. 134–141, 2022.

S. X. Zhang et al., “At the height of the storm: Healthcare staff’s health conditions and job satisfaction and their associated predictors during the epidemic peak of COVID-19,” Brain Behav Immun, vol. 87, pp. 144–146, 2020.

A. Esteva et al., “A guide to deep learning in healthcare,” Nat Med, vol. 25, no. 1, pp. 24–29, 2019.

J. He, S. L. Baxter, J. Xu, J. Xu, X. Zhou, and K. Zhang, “The practical implementation of artificial intelligence technologies in medicine,” Nat Med, vol. 25, no. 1, pp. 30–36, 2019.

N. Phuyal, P. K. Jha, P. P. Raturi, and S. Rajbhandary, “Total phenolic, flavonoid contents, and antioxidant activities of fruit, seed, and bark extracts of Zanthoxylum armatum DC,” The Scientific World Journal, vol. 2020, 2020.

A. S. Raja, J. D. Niforatos, N. Anaya, J. Graterol, and R. M. Rodriguez, “Vaccine hesitancy and reasons for refusing the COVID-19 vaccination among the US public: A cross-sectional survey,” MedRxiv, pp. 2021–2022, 2021.

A. Felix and G. D. Rembulan, “Analysis of Key Factors for Improved Customer Experience, Engagement, and Loyalty in the E-Commerce Industry in Indonesia,” Aptisi Transactions on Technopreneurship (ATT), vol. 5, no. 2sp, pp. 196–208, 2023.

V. Meilinda, S. A. Anjani, and M. Ridwan, “A Platform Based Business Revolution Activates Indonesia’s Digital Economy,” Startupreneur Business Digital (SABDA Journal), vol. 2, no. 2, pp. 155–174, 2023.




Cara Mengutip

Godwin, G., Any, B., Delhi, A., Sunarya, P. A., & Nicola, G. (2024). Pengaruh Technology Readiness Dan Satisfaction Terhadap Penerimaan Penggunaan Safe Entry Station: The Influence of Technology Readiness and Satisfaction on Acceptance of Use Safe Entry Station. Technomedia Journal, 8(3 Februari), 479–498.