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All Journal INOVTEK Polbeng - Seri Informatika
W purbo, Onno
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Computer Science & IT

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Optimization of Intrusion Detection System with Machine Learning for Detecting Distributed Attacks on Server Yuliswar, Teddy; Elfitri, Ikhwana; W purbo, Onno
INOVTEK Polbeng - Seri Informatika Vol. 10 No. 1 (2025): March
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/vem9da98

Abstract

This study develops an intrusion detection system optimized with machine learning techniques for efficient and effective detection of Distributed Denial-of-Service (DDoS) attacks. Using the Decision Tree algorithm, the system is designed to maximise accuracy in the identification and classification of DDoS attacks. The CIC-DDoS2019 dataset, which consists of various comprehensive simulated attack scenarios, is used as the basis for training and validation, providing the model with robust capabilities in recognizing DDoS attacks with high accuracy. This IDS successfully achieved a 100% detection rate, which is a significant result in the network security environment. The system is integrated into the existing network infrastructure, monitoring data flows in real-time and performing predictive analysis to detect early indications of attacks. Each attack detection immediately triggers a notification sent via a Telegram bot, ensuring that the security team can react quickly to isolate and address the attack. These notifications include details such as the source, type of attack, detection time, and involved protocol information, enabling more informed and strategic response actions. The use of Telegram bots for real-time communication not only enhances the speed of response to threats but also supports system scalability by facilitating adjustments and integration across various operational scenarios. The system's quick detection and response is a big step forward for machine learning-based intrusion detection systems (IDS). It provides opportunities for further research and practical applications that can adapt to various digital security scenarios.
Analysis of Path Loss In 802.11ac Data Communication at 5.8 Ghz Frequency in Padang City YULISWAR, TEDDY; Elfitri, Ikhwana; W purbo, Onno
INOVTEK Polbeng - Seri Informatika Vol. 9 No. 2 (2024): November
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/63fn5597

Abstract

This research aims to analyze path loss in data communication using the 802.11ac standard at a frequency of 5,185 MHz in the city of Padang. We collected data on environmental parameters, including air temperature ranging from 24.44°C to 31.11°C, relative humidity between 77% and 96%, dew point from 24.4°C to 26.11°C, and wind speed, over a period of four consecutive weeks. Additionally, we measured technical network parameters like signal strength, noise, and throughput at a 1.5 km distance between two towers, each measuring 28 meters and 25 meters in height. Environmental conditions, particularly humidity and wind speed, influence path loss, according to the research results. In the measurement, the received signal varies from -44 dBm to -49 dBm, while the noise is in the range of -90 dBm to -92 dBm. The throughput generated also varies between 259.2 Mbps and 295.2 Mbps. We discovered that high humidity and low wind speed lead to an increase in throughput, suggesting that weather conditions influence the quality of data transmission. This research provides important insights into the planning and optimization of 802.11ac wireless networks in urban areas, particularly for improving service quality under various environmental conditions
Co-Authors Ikhwana Elfitri Yuliswar, Teddy