K-NEARST NEIGBOUR (KNN) UNTUK MENDETEKSI GANGGUAN JARINGAN KOMPUTER PADA INTRUSION DETECTION DATASET
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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
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DOI: https://doi.org/10.31294/jki.v2i1.1624
DOI (PDF (English)): https://doi.org/10.31294/jki.v2i1.1624.g1181
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