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SISTEM PAKAR DIAGNOSIS PENYAKIT MELALUI GENERAL CHECK UP BERBASIS MOBILE APPLICATION ANDROID Salam, Zuhair Mahdi; Trisnawati, Herlina; Tarigan, Sakius Octavianus; Shirlyani, Shirlyani
Jurnal Sistem Informasi dan Informatika (Simika) Vol 7 No 1 (2024): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v7i1.3090

Expert System is a system created by imitating the performance or thought patterns of humans, which is input into an application system with the aim of helping to facilitate human work as done by experts. Android-based Expert System can help users analyze what diseases are present in the body. Expert System for Disease Diagnosis Through General Check Up Based on Android Mobile Application at Bojong Medika Clinic is a mobile-based application system that can be used as a platform for users to record, store medical records, automatically process data from general check-ups, and remind them to do further general check-ups in an effort to make everyone using this application more concerned about their health and avoid various diseases. This application is created using Kodular and supported by Air Table as its database, with additional tools using Firebase. The system development method used is the Waterfall Model, starting from the analysis stage, then followed by design, implementation, and finally testing of the application system.

Web-Based Network Anomaly Detection System for Disaster Recovery Center: A SIEM Implementation at the Indonesian Attorney General Training Agency Issenoro; Trisnawati, Herlina; Tarigan, Sakius Octavianus; Faizah, Novianti M
Journal Innovations Computer Science Vol. 4 No. 1 (2025): May
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i1.217

This research focuses on developing an anomaly detection application for the internet network infrastructure at the Disaster Recovery Center (DRC) building of the Indonesian Attorney General's Training Agency through Security Information and Event Management (SIEM) implementation utilizing Python programming language. The primary objective of this study is to develop a comprehensive application that assists personnel, particularly network administrators at the DRC facility, in monitoring and analyzing internet network communication patterns and traffic flows. The research methodology involves creating a detection system designed to enhance network security capabilities and provide continuous monitoring functionality for network infrastructure protection. The developed application leverages SIEM technology to aggregate and process security-related information extracted from log data across network devices, applications, and hardware components. SIEM technology demonstrates the capability to handle substantial data volumes while correlating and analyzing security events from multiple heterogeneous sources within the network environment. The implementation of this application provides critical visibility into the internal network operations of the DRC facility, enabling proactive threat detection and response capabilities. When security incidents or anomalous activities are identified, the system generates comprehensive reports detailing network conditions and security status, which are subsequently escalated to management for appropriate remedial actions and strategic decision-making.

Web-Based Network Anomaly Detection System for Disaster Recovery Center: A SIEM Implementation at the Indonesian Attorney General Training Agency Issenoro; Trisnawati, Herlina; Tarigan, Sakius Octavianus; Faizah, Novianti M
Journal Innovations Computer Science Vol. 4 No. 1 (2025): May
Publisher : Yayasan Kawanad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56347/jics.v4i1.217

This research focuses on developing an anomaly detection application for the internet network infrastructure at the Disaster Recovery Center (DRC) building of the Indonesian Attorney General's Training Agency through Security Information and Event Management (SIEM) implementation utilizing Python programming language. The primary objective of this study is to develop a comprehensive application that assists personnel, particularly network administrators at the DRC facility, in monitoring and analyzing internet network communication patterns and traffic flows. The research methodology involves creating a detection system designed to enhance network security capabilities and provide continuous monitoring functionality for network infrastructure protection. The developed application leverages SIEM technology to aggregate and process security-related information extracted from log data across network devices, applications, and hardware components. SIEM technology demonstrates the capability to handle substantial data volumes while correlating and analyzing security events from multiple heterogeneous sources within the network environment. The implementation of this application provides critical visibility into the internal network operations of the DRC facility, enabling proactive threat detection and response capabilities. When security incidents or anomalous activities are identified, the system generates comprehensive reports detailing network conditions and security status, which are subsequently escalated to management for appropriate remedial actions and strategic decision-making.

Perancangan dan Pengembangan Aplikasi Deteksi Anomali pada Jaringan Internet Gedung Disaster Recovery Center Badan Diklat Kejaksaan RI dengan Implementasi Sistem Manajemen Informasi dan Keamanan (SIEM) Berbasis Web Issenoro; Trisnawati, Herlina; Tarigan, Sakius Octavianus; Faizah, Novianti Madhona; Veranita
Jurnal Ilmu Komputer dan Teknologi Informasi Vol. 2 No. 1 (2025): Maret
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jikti.v2i1.1341

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.

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