Perbandingan Pengelompokan Metode PSO K-Means Dan Tanpa PSO Dalam Pengelompokan Data Alert

  • I Gede Made Sankhya Saiyoga Krisna Universitas Udayana
  • I Wayan Supriana
  • I Dewa Made Bayu Atmaja Darmawan
  • Agus Muliantara
  • Ngurah Agus Sanjaya ER
  • Luh Gede Astuti

Abstract

With increasing knowledge and increasing internet crime, an Intrusion Detection System (IDS) is needed, one of which is Snort which can detect attacks. An attack notification is needed to let administrators know if an attack has occurred. The grouping of alerts uses the PSO method on K-Means and continues with the calculation of the risk value to label the threat level, namely low, medium, high in each group. The Whatsapp bot will send groups of alerts that have high and medium labels only. A notification will appear on the Whatsapp application. The results obtained in this study by grouping the attack data, namely, the accuracy obtained by the system using the Particle Swarm Optimization method on K-Means obtained better results than only using the K-Means method.

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Published
2022-07-08
How to Cite
KRISNA, I Gede Made Sankhya Saiyoga et al. Perbandingan Pengelompokan Metode PSO K-Means Dan Tanpa PSO Dalam Pengelompokan Data Alert. JELIKU (Jurnal Elektronik Ilmu Komputer Udayana), [S.l.], v. 11, n. 2, p. 283-290, july 2022. ISSN 2654-5101. Available at: <https://ojs.unud.ac.id/index.php/jlk/article/view/88060>. Date accessed: 06 dec. 2024. doi: https://doi.org/10.24843/JLK.2022.v11.i02.p07.

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