<![CDATA[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.]]>
Copyrights © 2024
