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VISUALISASI SERANGAN PADA MALWARE SPYWARE MENGGUNAKAN METODE NAIVE BAYES CLASSIFIER

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Penilaian

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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.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307002239	T112081	T1120812023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1120812023

Publisher

Inderalaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer., 2023

Collation

xiv, 52 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.840 7

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)

Jurusan Sistem Komputer
Malware

Specific Detail Info

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Statement of Responsibility

SEPTA

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