<![CDATA[The increasing complexity of software systems and the demand for rapid application development have created significant challenges for software Quality Control (QC) processes. Manual testing often requires extensive time, repetitive effort, and substantial human resources, increasing the risk of inconsistencies and undetected defects. This study aims to evaluate the effectiveness of Robotic Process Automation (RPA) in improving software testing efficiency and quality within the Collection System application at PT ADMF. A quantitative case study approach was employed using a before-and-after comparative analysis of Quality Control activities across eight software modules. Data were collected through documentation analysis, system observation, and Quality Control reports. The RPA solution was developed using the UiPath platform to automate functional testing, regression testing, user interface validation, and data verification activities. The results demonstrate that RPA significantly improved software testing performance. The average Quality Control duration decreased from 26.13 days to 15.25 days, representing a 41.64% reduction. Testing coverage increased by 53.37%, while defect detection capability improved by 36.23%. Furthermore, defects identified during User Acceptance Testing (UAT) and production environments decreased by 58.43% and 71.60%, respectively. The implementation of RPA also enhanced testing consistency, reduced human intervention, and optimized resource utilization. Despite the growing adoption of RPA in business process automation, empirical evidence regarding its effectiveness in software Quality Control environments within Indonesian financial service organizations remains limited; therefore, this study addresses this gap by providing quantitative evidence of RPA's impact on testing efficiency, coverage, and defect management in a real-world financial services context.]]>
