<![CDATA[Digitization of police services has become an essential component in improving the quality and responsiveness of public services. However, the adoption rate of the Polri Super App remains suboptimal, indicating challenges in user acceptance that cannot be fully explained by the core constructs of the UMEGA model. This condition highlights the need for an analytical approach that incorporates institutional factors, service quality, and public trust. This study explicitly contributes by expanding the UMEGA model through the integration of institutional capacity, information quality, service quality, and multidimensional trust, offering a more comprehensive framework for understanding digital policing adoption. A quantitative survey was conducted involving 432 respondents who had used the National Police Super App within the last six months. Data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) to assess construct validity, reliability, and structural relationships among variables. The results show that performance expectancy, information quality, service quality, computer self-efficacy, attitude, and trust significantly influence users’ intentions and actual usage behavior, while perceived risk and facilitating conditions show no significant effect. These findings indicate that institutional quality, information accuracy, and public trust play dominant roles in shaping user acceptance. Practically, the results provide guidance for policymakers to strengthen digital policing services through improved service reliability, enhanced data transparency, and targeted user capability support. The study concludes that expanding the UMEGA model offers a more complete understanding of digital policing service adoption and provides an empirical basis for improving the quality and sustainability of technology-based public services.]]>
