https://ijicom.respati.ac.id/index.php/ijicom <p><strong>p-ISSN: 2685-8711&nbsp;<br><strong>e-ISSN:&nbsp;2714-5263</strong><br>Aims</strong></p> <p>International Journal of Informatics and Computation (IJICOM) is an international, peer-reviewed, open-access journal, which publishes original theoretical and empirical work on the science of informatics and its application in multiple fields. Our concept of Informatics includes technologies of information and communication as well as the social, linguistic and cultural changes that initiate, accompany and complicate their development.</p> <p>IJICOM aims to be an international platform to exchange novel research results in simulation-based science across all scientific disciplines. It publishes advanced innovative, interdisciplinary research where complex multi-scale, multi-domain problems in science and engineering are solved, integrating sophisticated numerical methods, computation, data, networks, and novel devices.</p> <p>The recent advances in experimental such as IoT, 5G, Artificial Intelligence,&nbsp; sensor networks, and high-resolution imaging techniques. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods.</p> <p><strong>Scope</strong></p> <ul> <li class="show">mobile computing</li> <li class="show">security &amp; privacy</li> <li class="show">pattern recognition</li> <li class="show">human-computer interaction</li> <li class="show">media arts and sciences</li> <li class="show">medical informatics</li> <li class="show">health informatics</li> <li class="show">social informatics</li> <li class="show">business informatics</li> <li class="show">Modeling, Algorithms, and Simulations (e.g. numerical and non-numerical, discrete and continuous);</li> <li class="show">Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems;&nbsp;</li> </ul> <p>The journal welcomes original, unpublished contributions in the field of computational science at large, addressing one or more of the aforementioned elements.</p> <h2>Editorial Office</h2> <div class="editor_div"><em><strong>Dept. Informatics Engineering, University of Respati Yogyakarta, Indonesia, Phone: 0274-488781<br></strong>Email:&nbsp;[email protected]</em></div> <p><em><strong>For further IJICOM&nbsp;contacts, see&nbsp;<a href="http://ijicom.respati.ac.id" target="_blank" rel="noopener">here</a>.</strong></em></p> <p>&nbsp;</p> University of Respati Yogyakarta, Indonesia en-US International Journal of Informatics and Computation 2685-8711 https://ijicom.respati.ac.id/index.php/ijicom/article/view/261 <p>Distributed Denial of Service attacks remain a major network-security threat because they can overwhelm computing resources, disrupt digital services, and cause substantial operational losses. The emergence of Generative Artificial Intelligence has further increased the urgency of adaptive and efficient traffic-based detection because intelligent systems may support defensive analysis while also enabling increasingly automated attack strategies. This study compared Random Forest, Multilayer Perceptron Classifier, and Extreme Gradient Boosting for detecting DDoS traffic using the CICDDoS2019 dataset. The dataset was processed through duplicate removal, missing-value checking, feature filtering, label encoding, feature scaling, and data splitting. The models were evaluated using accuracy, precision, recall, F1-score, Receiver Operating Characteristic Area Under the Curve, and cross-validation score. Random Forest achieved the highest accuracy of 0.992770 and cross-validation score of 0.992684, whereas Extreme Gradient Boosting achieved the highest ROC AUC of 0.993765. The results demonstrate that Random Forest provided the most stable overall performance, while Extreme Gradient Boosting offered the strongest class-discrimination capability.</p> Fahrezi Tresno Nurwanto Agung Nugroho Ismasari Nawangsih Copyright (c) 2026 https://creativecommons.org/licenses/by-sa/4.0 2026-07-05 2026-07-05 8 2 605 617 10.35842/ijicom.v8i2.261