VISUALISASI SERANGAN PADA MALWARE SPYWARE MENGGUNAKAN METODE NAIVE BAYES CLASSIFIER

SARTIKA, SARTIKA and Stiawan, Deris (2023) VISUALISASI SERANGAN PADA MALWARE SPYWARE MENGGUNAKAN METODE NAIVE BAYES CLASSIFIER. Undergraduate thesis, Sriwijaya University.

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Abstract

The amount of Malware is constantly increasing. Most Malware is a modification of previous Malware data. The datasets used from CIC-MalMem-2022 are Benign and Spyware-CWS. This study used the Naïve Bayes Classifier algorithm. Naïve Bayes is one of the classification algorithms that has accuracy in making predictions and has a good reputation in classification, especially in learning speed compared to other Machine Learning classification algorithms. To get the best accuracy results, there are five features with the highest value for training using K-fold 3 which are calculated using the Confusion Matrix. The results showed that the Naïve Bayes Classifier method can analyze the accuracy level using K-Fold 3 with an Accuracy of 94.11%. The tie of the results of the study stated that visualization of attacks on Spyware Malware using the Naïve Bayes Classifier method obtained efficient and accurate results. Keywords: Malware, Spyware, Visualization, Naïve Bayes Classifier,K-Fold, Machine Learning.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Malware, Spyware, Visualisasi, Naïve Bayes Classifier, K-Fold, Machine Learning.
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Sartika Sartika
Date Deposited:	19 Jun 2023 07:49
Last Modified:	19 Jun 2023 07:49
URI:	http://repository.unsri.ac.id/id/eprint/112081

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