<![CDATA[General Background: E-learning has rapidly expanded worldwide due to the widespread accessibility of the Internet and the increasing availability of digital devices. As a web-based learning ecosystem, e-learning integrates multiple stakeholders, technologies, and processes to facilitate knowledge acquisition. Specific Background: Universities have increasingly adopted e-learning platforms to enhance learning experiences. However, the success of these implementations varies, necessitating a deeper understanding of the factors influencing their effectiveness. Knowledge Gap: While previous studies have explored the technical and pedagogical aspects of e-learning, limited research has examined the indirect effects of information and system quality on user behavior within university settings. Aims: This study aims to evaluate the success factors of the Spada Wimaya e-learning system in a university setting by assessing the relationships between system quality, information quality, perceived usefulness, perceived ease of use, behavioral intention, and actual system use. Results: The findings reveal that information and system quality indirectly influence behavioral intention and actual use through perceived usefulness and perceived ease of use. These results highlight the importance of user perceptions in determining the adoption and sustained utilization of e-learning platforms. Novelty: By adapting the research model from Presetyo et al. (2021), this study provides empirical evidence on the indirect mechanisms through which system and information quality affect user engagement in e-learning. Implications: The insights gained from this research can guide improvements in the Spada Wimaya e-learning system and serve as a reference for other universities aiming to enhance their digital learning environments. Highlights: User Perception Matters – System and information quality impact usage through perceived usefulness and ease of use. Indirect Influence – Quality factors do not directly affect behavior but work through user perceptions. Scalability – The model can be applied to improve e-learning systems in other universities. Keywords: E-Learning, Information System Model, Success Factors]]>
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