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The e-learning-based approach is critical in keeping the wheels of education turning in the face of the COVID-19 epidemic. In this scenario, analyzing the implementation of the e-learning system is required to properly grasp the needs. The purpose of this paper is to demonstrate the relationship between technical system quality, information quality, service quality, educational system quality, support system quality, learner quality, instructor quality, perceived satisfaction, perceived usefulness, e-learning system use and benefits.

This study was carried out by giving online questionnaires to students attending private institutions in Indonesia. A total of 593 students participated in the study and provided responses. The structural equation model, which is supported by the program WarpPLS7.0, is used to analyze the data.

Maintaining the quality of the technological system, the information system, the learners and the educational system can help achieve the goal of increasing perceived utility. In the meanwhile, factors such as inadequate service quality, educational system quality, support system quality and teacher quality can all pose challenges to perceived levels of satisfaction. To get the most out of e-learning apps, users' expectations about how fun, useful and easy to use they are need to be met.

This study was carried out in the midst of the COVID-19 epidemic with a restricted number of participants from Indonesian institutions of higher education. This research has the potential to be expanded into a variety of different types of higher education in the future.

The main thing that will determine whether an e-learning system model works is the quality of the learners.

The institution should think about changing the material offered in the e-learning system to make it easier for students to grasp by describing the current material and providing digital handouts of lecturers' explanations. This study expanded the e-learning system success model and applied it to the evaluation of e-learning deployment in Indonesian higher education. This study will improve student comprehension of the e-learning model and contribute to the body of knowledge about e-learning applications and technology.

This study aims to analyze the effects of performance expectancy, effort expectancy, social influence and facilitating conditions on the behavioral intention of using mobile health applications, especially during and after the COVID-19 pandemic.

A survey was developed using an online survey platform and distributed to Indonesian consumers for three weeks, and 149 usable responses were obtained. The principal component analysis, linear regression and analysis of variance tests were performed to test the validity and reliability of the measurement model and the hypothesized relationships among constructs.

Surprisingly, unlike previous studies on IT adoption, the findings show that social influence has no significant impact on behavioral intention. Facilitating conditions have a very weak to almost no significant impact on behavioral intention to use mobile health applications.

This research is conducted during pandemic COVID-19 where using mobile health apps is a must. In the future this research can be expanded as comparison study after the pandemic COVID-19 stated.

The result implies that digital technologies adoption intention is strongly affected by performance expectancy and effort expectancy, with performance expectancy as the most significant predictor. Nonetheless, the interaction of performance expectancy, effort expectancy, social influence and facilitating conditions influences behavioral intention significantly. Therefore, social influence and facilitating conditions are still important even with very insignificant effects.

To improve consumers’ behavioral intention to use mobile health applications, application providers should promote mobile health applications as useful telemedicine tools by primarily focusing on the application performance and usage experience.