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Journal : Jurnal Komputer

Hybrid Learning Approach For Intrusion Detection In Network Security Using Ensemble Methods Tarigan, Heskyel Pranata
Jurnal Komputer Vol 2 No 2 (2024): Januari-Juni
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v2i2.100

Abstract

The increasing frequency and sophistication of cyberattacks have led to a pressing need for advanced network security systems, particularly Intrusion Detection Systems (IDS). While traditional IDS models provide a baseline of protection, they often fall short in detecting novel and complex threats. This research proposes a hybrid learning approach for IDS, leveraging the strengths of ensemble machine learning methods such as Random Forest, Gradient Boosting, and Voting Classifier. The proposed system aims to enhance detection accuracy and reduce false positives by combining multiple classifiers into a cohesive model. Using the NSL-KDD dataset, the model was trained and tested, showing superior performance compared to individual learning algorithms. This paper discusses the design, implementation, and performance evaluation of the hybrid IDS model.
Integrasi Chatbot Berbasis NLP pada Sistem Layanan Akademik Universitas Tarigan, Heskyel Pranata
Jurnal Komputer Vol 3 No 1 (2024): Juli-Desember
Publisher : CV. Generasi Insan Rafflesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jk.v3i1.110

Abstract

The advancement of digital technology has driven transformation in the delivery of information services in higher education institutions. One innovation that is being increasingly adopted is the use of Natural Language Processing (NLP)-based chatbots in academic service systems. This chatbot enables natural conversation-based interactions between users and systems, facilitating students in accessing information quickly and efficiently. This paper discusses the basic concepts, benefits, system architecture, and challenges faced in integrating NLP-based chatbots into academic service systems. By adopting this approach, universities can enhance service quality, reduce administrative burdens, and promote the digitalization of academic processes in a comprehensive manner.