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All Journal Journal of Research and Publication Innovation Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA)
Elang Pramana Putra
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Computer Science & IT Control & Systems Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Analisa Sistem Pakar Diagnosa Penyakit Lambung Menggunakan Metode Forward Chaining Ananda Safitri; Elang Pramana Putra; Muhammad Agung Prasetio; Widya Puspita Cahyani; Perani Rosyani
Buletin Ilmiah Ilmu Komputer dan Multimedia Vol 1 No 1 (2023): Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA) INPRESS
Publisher : Shofanah Media Berkah

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Abstract

Diagnosing gastric disease is a challenge in the medical field because of its often similar symptoms and the complexity associated with other factors that can affect a patient's condition. The expert system has become an interesting approach in diagnosing gastric diseases because of its ability to mimic the intelligence and knowledge of a medical expert. In this study, we conducted an analysis of the Gastric Disease Diagnosis Expert System using the Forward Chaining method with a Systematic Literature Review (SLR) approach. The Forward Chaining method is used for inference based on the rules and facts of the symptoms collected, while the Systematic Literature Review (SLR) is used to analyze the relevant literature to gain a comprehensive understanding of the use of the Forward Chaining method in the diagnosis of gastric diseases. The results of our analysis provide important insights into the implementation, advantages, solution and platfrom of using the Forward Chaining method in an expert system for diagnosing gastric diseases.
IMPLEMENTASI NETWORK MONITORING SYSTEM (NMS) MENGGUNAKAN CACTI DENGAN METODE GENETIKA PADA INFRASTRUKTUR JARINGAN Elang Pramana Putra; Ines Heidiani Ikasari
Journal of Research and Publication Innovation Vol 3 No 4 (2025): OCTOBER
Publisher : Journal of Research and Publication Innovation

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Abstract

This study implements a Network Monitoring System (NMS) based on Cacti with genetic algorithm optimization to improve network monitoring efficiency at SMK PGRI 1 Tangerang. Cacti is used to visualize network performance such as bandwidth, CPU load, and uptime in real-time. The objective of this study is to enhance the efficiency and effectiveness of network monitoring through polling interval optimization so that the system remains efficient without overloading the server. The research methods include literature study, observation, interviews, and system simulation. The results show that the implementation of Cacti with the genetic method can improve network stability, accelerate fault detection, and reduce the Mean Time to Repair (MTTR) by up to 35%, from an average of 90 minutes to 30 minutes per incident, as well as decrease the frequency of failures from 4 times to 2 times per week. The results include graphical visualizations that help technicians and teachers interpret data, such as memory usage and load average. The system has proven effective in improving school network stability with minimal overhead. He implementation of a Network Monitoring System using Cacti with the genetic method has been proven to increase efficiency, stability, and fault detection speed in the network of SMK PGRI 1 Tangerang. This system assists technicians in real-time monitoring and accelerates the troubleshooting process. For future development, the system can be integrated with automatic notifications such as Telegram Bot or Email Alert and expanded to cloud-based monitoring to be more adaptive to modern network needs.Top of Form
Co-Authors Ananda Safitri Ines Heidiani Ikasari Muhammad Agung Prasetio Perani Rosyani Widya Puspita Cahyani