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All Journal Jurnal Transformatika INOVTEK Polbeng - Seri Informatika
Chaerul Umam
Dian Nuswantoro University
Computer Science & IT

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Comparative Analysis of Random Forest and Xgboost Performance for Network Flow-Based Malware Classification Fajar Adji Wicaksana; Chaerul Umam
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 11 No. 1 (2026): February
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/8f891c76

Abstract

The evolving complexity of cyber threats, particularly malware propagation through network infrastructure, necessitates intrusion detection mechanisms that are both precise and computationally efficient. This study presents an in-depth comparative analysis of two ensemble learning algorithms, Random Forest (RF) and Extreme Gradient Boosting (XGBoost), in classifying network traffic anomalies based on network flow features. Empirical validation was conducted using the CSE-CIC-IDS2018 dataset, which comprehensively represents a spectrum of modern attacks. The research methodology systematically includes data preprocessing, handling class imbalance via weighting techniques, and performance evaluation based on accuracy, F1-score, and inference time metrics. Experimental results indicate that both models achieved high performance convergence with perfect Area Under Curve (AUC) scores. However, XGBoost demonstrated technical superiority with an accuracy of 99.8%, slightly surpassing Random Forest at 99.4%. The most significant finding of this study lies in computational efficiency, where XGBoost proved to be 14% faster (6.36 seconds) in prediction compared to Random Forest (7.42 seconds) on a large-scale test set. This fact confirms that the boosting architecture in XGBoost offers an optimal balance between detection sensitivity and system latency. Based on this evidence, XGBoost is recommended as the best classification model for real-time intrusion detection system implementations that prioritize rapid threat response.  
Purwarupa Sistem Pemilihan Umum Elektronik dengan Pemanfaatan Protokol Ethereum pada Teknologi Blockchain Eko Arianto; Chaerul Umam; L Budi Handoko
Jurnal Transformatika Vol. 19 No. 1 (2021): July 2021
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i1.2746

Abstract

The development of information technology has penetrated various areas. This is driven by improved service, rapid increase in information needs and decision making. General elections that are held every time always leave problems about securities and speed of recapitulation. This is because the process is done in the traditional way. This research tries to apply blockchain technology to the e-Voting system security engineering process so that it creates a votes recapitulation process that is fast, accurate and accompanied by transparency values to maintain the reliability of the existing vote and maintain the confidentiality of the vote data being transacted. Transparency and confidentiality of voter data is a fundamental value in general elections or voting that must exist. Seeing this, blockchain technology deserves to be applied because the principles that needed can be met by applying this technology to the e-Voting system.
Co-Authors Eko Arianto Fajar Adji Wicaksana L. Budi Handoko