<![CDATA[The development of digital transactions has driven the need for more accurate and easily monitored Electronic Data Capture (EDC) devices to support payment processes in the retail and distribution sectors. However, the manual and unintegrated EDC monitoring mechanism leads to data inconsistencies, delays in operational information, and low device traceability throughout its lifecycle. This research develops a real-time, web-based EDC population monitoring system to improve device management efficiency and operational data quality. The needs analysis was conducted using the PIECES framework, while the development process adopted the Waterfall model, encompassing analysis, design, implementation, and testing. The resulting system supports device registration, distribution monitoring, activation tracking, mutation recording, and device closure. Test results show significant improvements in data accuracy, reporting speed, and monitoring process effectiveness compared to manual methods. These findings contribute to the literature on enterprise digital asset management and demonstrate that a structured development approach can optimize the EDC device monitoring process in large-scale retail networks.]]>
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