Record Details

Klasifikasi Berita Hoax Dengan Menggunakan Metode Naive Bayes

Walisongo Journal of Information Technology

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Field Value
 
Title Klasifikasi Berita Hoax Dengan Menggunakan Metode Naive Bayes
 
Creator Mustofa, Hery
Mahfudh, Adzhal Arwani
 
Subject data mining
hoax, klasifikasi, naive bayes, text minning
 
Description Hoaxes contain false news or non-sourced news. Today, hoaxes are very widely spread through internet media. The development of information technology that has so quickly triggered the spread of hoax information through the internet has become uncontrolled. So we need an intelligent system that can classify hoax news content that is spread through internet media. The hoax classification process can be done through the preprocessing stage then weighting the word and classification using naive bayes. Measurements were made using the 10-ford cross validation method. The results obtained from these measurements, it is known that the value of fold 6 has the highest accuracy, which is equal to 85.28% which is classified as relevant documents as much as 307 and irrelevant as much as 53 or an error rate of 14.72%. While the average value based on hoax news and true news value precision 0.896 and recall 0.853
 
Publisher Universitas Islam Negeri Walisongo Semarang
 
Contributor —
 
Date 2019-11-08
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Naive Bayes
 
Format application/pdf
 
Identifier https://journal.walisongo.ac.id/index.php/jit/article/view/3915
10.21580/wjit.2019.1.1.3915
 
Source Walisongo Journal of Information Technology; Vol 1, No 1 (2019): Walisongo Journal of Information Technology; 1-12
2715-0143
2714-9048
 
Language eng
 
Relation https://journal.walisongo.ac.id/index.php/jit/article/view/3915/2197
 
Rights Copyright (c) 2019 Walisongo Journal of Information Technology
http://creativecommons.org/licenses/by-nc-sa/4.0