Skripsi

OPTIMASI NAIVE BAYES UNTUK KLASIFIKASI SERANGAN DDOS DENGAN GENETIC ALGORITHM

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Penilaian

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DDoS is one type of internet attack that can threaten internet users, especially web application users, DDoS attacks can cause a server to malfunction on a network, which is caused by the large amount of bandwidth traffic that is launched by an attacker through DDoS. Therefore, we need a way to identify a network traffic, that is by carrying out a classification process on a network traffic data to find out whether it is an attack or not. because the amount of network traffic data is very much per second, a classification algorithm is used to overcome this problem. One classification algorithm that is able to handle a lot of data at once is the Naïve Bayes algorithm. One of the weaknesses of Naïve Bayes is the dependency of the results of accuracy generated based on many attributes used, therefore Genetic Algorithm (GA) is used as an optimization algorithm to reduce the use of attributes and increase the accuracy of the Naïve Bayes algorithm. The accuracy of Naïve Bayes was 91.55% and Naïve Bayes was optimized with Genetic Algorithm98.56% Obtained increased accuracy obtained by 5.4%

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2007000863	T33061	T330612020	Central Library (REFERENSI)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T330612020

Publisher

Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2020

Collation

xviii, VI-2 hlm.; ilus., tab.:28 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Naïve Bayes
Teknik Informatika
Ilmu Komputer

Specific Detail Info

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Statement of Responsibility

EM

Other version/related

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