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Lauwl, Christoper Michael
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Computer Science & IT Decision Sciences, Operations Research & Management

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Komparasi Metode Random Forest Dan Support Vector Machine (SVM) Untuk Pemodelan Klasifikasi Serangan DDos Lauwl, Christoper Michael; Husain, Husain; Nuzululnisa, Baiq Nadila; Wijaya, Hartono
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6684

Abstract

The Distributed Denial of Service (DDoS) attack is a type of cyberattack that aims to render a service, network, or website inaccessible to legitimate users. This attack not only disrupts services but also causes server crashes by repeatedly sending data packets, commonly referred to as spam. DDoS attacks can be identified as traffic anomalies. The National Cyber and Crypto Agency (BSSN) recorded 403,990,813 traffic anomalies with 347 cases specifically attributed to DDoS attacks. Based on this issue, a model capable of classifying DDoS attacks is necessary. This study employs the Random Forest and Support Vector Machine (SVM) methods through the steps of data collection, dataset loading, data preprocessing, classification modeling, and performance evaluation. In the final stage, the best method between Random Forest and Support Vector Machine is determined. The results indicate that Random Forest achieved an accuracy of 99.9%, whereas Support Vector Machine obtained an accuracy of 97.0%. Therefore, it can be concluded that Random Forest demonstrates better accuracy in classifying DDoS attacks.
Sistem Otentifikasi Otomatis Kendala Perangkat Jaringan Menggunakan NDLC Hadi, Muhammad Fawazi; Vidiasari, Viviana Herlita; Lauwl, Christoper Michael; Husain, Husain; Amin, Farda Milanda
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6685

Abstract

The authentication system is a monitoring system where if there is a network problem, it can provide information quickly. The research was conducted at Bumigora University, using 3 buildings as research materials implemented in the form of topology design. The monitoring is carried out to anticipate lost connections or network disconnections caused by certain factors. The Network Development Life Cycle (NDLC) method is the appropriate method for conducting this analysis, because it focuses on parameters such as network reliability and the ability to secure data transmission. The stages of the NDLC method consist of analysis, design, simulation prototype, implementation, monitoring and management, but in this study the author only used 3 stages, namely analysis, design, simulation prototype and implementation. The NDLC method has been proven to increase network security and reliability, as well as minimize downtime due to device failure or disconnection of data transmission. Automatic authentication implemented through NDLC allows real-time device monitoring, by connecting the API with telegram. Telegram will provide notifications in the form of network condition statuses that are experiencing problems. So that the IT team can control the condition of network devices through telegram notifications. This can facilitate network management and efficiency of checking time in maintaining the stability and performance of the network as a whole.
Co-Authors Amin, Farda Milanda Hadi, Muhammad Fawazi Hartono Wijaya Husain Husain Nuzululnisa, Baiq Nadila Vidiasari, Viviana Herlita