Analysis Effect of Perceived Ease of use and Perceived Usefulness on Halodoc Application User Satisfaction using the TAM Method

Authors

  • Nur Uswatun Hasanah Universitas Mulia
  • Vanesa Angelica Joceline Universitas Mulia
  • Riski Zulkarnain Universitas Mulia

DOI:

https://doi.org/10.59934/jaiea.v6i1.2611

Keywords:

Halodoc; User Satisfaction; Perceived Ease of Use; Perceived Usefulness; Technology Acceptance Model

Abstract

The development of information technology has encouraged the transformation of healthcare services toward digital systems that are more effective and accessible. One of the most widely used digital healthcare platforms in Indonesia is Halodoc. This study aims to analyze the influence of Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) on user satisfaction with the Halodoc application using the Technology Acceptance Model (TAM) approach. This study employed a descriptive qualitative method involving three active Halodoc users as informants. Data were collected through in-depth interviews, observation, and documentation. The findings indicate that perceived ease of use contributes positively to user satisfaction through a simple interface, intuitive navigation, and uncomplicated usage procedures. Perceived usefulness also influences user satisfaction, as the application helps users save time, facilitates access to healthcare services, and enables them to meet their healthcare needs more conveniently. Furthermore, both variables are interconnected in shaping user satisfaction. The easier and more useful the application is perceived to be, the higher the level of user satisfaction. These findings suggest that continuous improvements in usability and usefulness are necessary to maintain user satisfaction with digital healthcare applications.

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Published

2026-10-15

How to Cite

Nur Uswatun Hasanah, Vanesa Angelica Joceline, & Riski Zulkarnain. (2026). Analysis Effect of Perceived Ease of use and Perceived Usefulness on Halodoc Application User Satisfaction using the TAM Method. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 6(1), 13–17. https://doi.org/10.59934/jaiea.v6i1.2611