Generation Z: How Acceptable Health Application for Us?

Wella, Wella (2024) Generation Z: How Acceptable Health Application for Us? In: 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems (SCIS&ISIS), Himeji, Japan.

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Abstract

Over the course of the last three years, the whole global population has been impacted by a COVID-19 epidemic. As a result of the ongoing pandemic crisis, all human activities have been halted, including remote office work and the closure of crowded locations to further prevent the spread of the virus. The COVID-19 pandemic has led to a significant increase in medical activities, thereby necessitating the employment of digital technology to provide support in managing the situation. One such technology is the Halodoc application, which enables the public to access medical aid without the need for direct contact. This study aims to examine the public's acceptance of the Halodoc application as a result of its usage. The intended participants are those belonging to Generation Z, born between the years 1995 and 2015. Generation Z was selected due to their status as digital natives, meaning they were born into a world where technology is prevalent and constantly evolving. The study utilized the Structural Equation Model (SEM) method to examine the level of acceptance of Generation Z towards the Halodoc application. The Technology Acceptance Model (TAM) was employed as a reference model for this analysis. The analysis will determine whether the model proposed in this study is accepted. This will be done by conducting tests using Structural Equation Modeling (SEM) and presenting graphical results from the questionnaire. By doing these tests, it may be determined whether the Halodoc application is deemed acceptable by Generation Z.

Item Type:	Conference or Workshop Item (Paper)
Creators:	Wella, Wella
Contributors:
Keywords:	Covid, Generation Z, Halodoc, SEM, TAM
Subjects:	000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 004 Computer Science, Data Processing, Hardware
Divisions:	Faculty of Engineering & Informatics > Information System
Date Deposited:	02 Dec 2025 08:10
URI:	https://kc.umn.ac.id/id/eprint/42539

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