Jurnal Khatulistiwa Informatika
Vol 2, No 1 (2014): Periode Juni 2014

K-NEARST NEIGBOUR (KNN) UNTUK MENDETEKSI GANGGUAN JARINGAN KOMPUTER PADA INTRUSION DETECTION DATASET

Bekti Maryuni Susanto (Program Studi Manajemen Informatika, AMIK BSI Yogyakarta)



Article Info

Publish Date
01 Jun 2014

Abstract

Internet increasing is also exponentially increasing intrusion or attacks by crackers exploit vulnerabilitiesin Internet protocols, operating systems and software applications. Intrusion or attacks against computernet works, especially the Internet has increased from year to year. Intrusion detection systems into the main stream in the information security. The main purpose of intrusion detection system is a computer system to help deal with the attack. This study presents k-nearest neigbour algorithm to detect computer network intrusions. Performance is measured based on the level of accuracy, sensitivity, precision and spesificity. Dataset used in this study is a dataset KDD99 intrusion detection system. Dataset is composed of two training data and testing data. From the experimental results obtained by the accuracy of k-nearest neigbour algoritm is about 79,36%.Keyword: k-nearest neigbour, intrusion detection

Copyrights © 2014






Journal Info

Abbrev

khatulistiwa

Publisher

Subject

Computer Science & IT

Description

Jurnal Khatulistiwa Informatika (JKI) Merupakan Jurnal Ilmu Komputer yang dikelola oleh LPPM Universitas Bina Sarana Informatika Unit Kampus Kota Pontianak. Jurnal ini di publikasikan secara nasional dengan menggunakan Open Journal System (OJS). Jurnal Khatulistiwa Informatika (JKI) menggunakan ...