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VISUALISASI DATA SERANGAN UDP FLOOD PADA JARINGAN INTERNET OF THINGS (IOT) MENGGUNAKAN ALGORITMA NAIVE BAYES CLASSIFIER

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Penilaian

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This study focuses on visualize the UDP Flood Attack Pattern on Internet of Things Network Dataset ( doi.org/10.528 /zenodo.4436127). The purpose of this study is to obtain a visual form of the dataset classification results using the Naive Bayes Classifier algorithm which shows the difference between UDP Flood attack data and normal data. The method used in this study is the Naive Bayes Classifier as a classifier that applied to datasets. The results from this study showed that the classification carried out using the Naive Bayes Classifier algorithm obtained a classification accuracy rate of 99.80% using the Multinominal Naive Bayes model which applied to the dataset. The classification results are visualized in the form of parallel coordinate graphs which conclude the difference between UDP Flood attack data and normal data is clearly obtained and marked by differences in line colors in the graph produced within this study.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307000602	T86217	T862172023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T862172023

Publisher

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

Collation

xii, 48 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.660 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)

Metode Transmisi Data
Jurusan Sistem Komputer

Specific Detail Info

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Statement of Responsibility

SEPTA

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