PENERAPAN RANDOM FOREST CLASSIFIER FEATURE PADA METODE NAÏVE BAYES UNTUK MENGENALI POLA-POLA SERANGAN PADA LAYANAN WEB

UTAMA, ADI KESUMA JAYA and Heryanto, Ahmad (2023) PENERAPAN RANDOM FOREST CLASSIFIER FEATURE PADA METODE NAÏVE BAYES UNTUK MENGENALI POLA-POLA SERANGAN PADA LAYANAN WEB. Undergraduate thesis, Sriwijaya University.

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Abstract

SQL Injection is a hacking attack that is carried out by abusing the security gaps in the SQL layer on a data-based application, Sql Injections is a serious threat to the security of a website. The data set used in this study is CIC-IDS2018 from the Canadian Institute of Cybersecurity. This study discussed the application of the Random forest classifier on the Naive Bayes method to recognize patterns of attacks on the web. Then the researchers compared the results between hyperparameter on the naive bayes method, from the results carried out by researchers, that GaussianNB was excellent with an average of 96.33%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Sql Injection, Random forest Classifer, GaussianNB, MultinomialNB, ComplementNB
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Adi Kesuma Jaya Utama
Date Deposited:	13 Sep 2023 03:49
Last Modified:	13 Sep 2023 03:49
URI:	http://repository.unsri.ac.id/id/eprint/128388

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