This research develops an anomaly detection application for the internet network of the Disaster Recovery Center (DRC) building at the Training Agency of the Indonesian Prosecutor's Office (Badan Diklat Kejaksaan RI), implemented with Security Information and Event Management (SIEM) using the Python programming language. The resulting application aims to assist network administrators at the DRC in monitoring network communication flows and detecting potential threats to the system. The approach involves developing an application that enhances network security through anomaly detection and monitoring devices to protect the network. SIEM technology is used to collect and analyze log data from the network, applications, and hardware. This technology allows for the large-scale collection of log data and the analysis of events from multiple sources. With the implementation of this system, the DRC Kejaksaan RI is expected to gain the ability to monitor internet network traffic and the security devices applied, as well as evaluate the effectiveness of SIEM in protecting information assets. The focus of this research is on improving network security, collecting logs and events related to network traffic, and developing a dashboard application to display monitoring results. The system aims to detect harmful anomalies and provide up-to-date information regarding network conditions, thus facilitating network administrators in performing monitoring tasks and reporting findings to leadership.