Data Mining Untuk Klasifikasi Serangan Jaringan Menggunakan Metode Naive Bayes

Pranata, Sadela (2020) Data Mining Untuk Klasifikasi Serangan Jaringan Menggunakan Metode Naive Bayes. Other thesis, Universitas Islam Riau.

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Abstract

This study aims to design and build network attack classification applications and determine the level of accuracy of the Algorithm method Naïve Bayes in network classification. The benefit of this research is to help classify networks in order to minimize network attacks by handling based on the resulting classification so that it is easier to handle. Provide knowledge to the author about the use of the Naive Bayes method for network classification. Qualitative descriptive research method with data collection techniques, namely conducting interviews with one of the employees of the internet provider wanxp, the research location at jl. Ir. H. Juanda. The results of this study reached a value of 82%, the level of data similarity between the data from NSL KDD and the system so that it has a good performance by sharing training data as much as 70%, namely 46873 and testing data 30%, namely 18661.

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