Klasifikasi Berita Hoax Dengan Menggunakan Metode Naive Bayes

Hery Mustofa*  -  Fakultas Sains dan Teknologi UIN Walisongo Semarang, Indonesia
Adzhal Arwani Mahfudh  -  , Indonesia

(*) Corresponding Author

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

Keywords: hoax, klasifikasi, naive bayes, text minning

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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Walisongo Journal of Information Technology
Published by Department Information Technology
Faculty of Science and Technology UIN Walisongo Semarang

Jl Prof. Dr. Hamka Kampus III Ngaliyan Semarang 50185
Phone: 024-76433366
Website: https://fst.walisongo.ac.id/
Email: ti@walisongo.ac.id

ISSN 2715-0143 (media online)
ISSN 2714-9048 (media cetak)


ISSN: 2714-9048 (Print)
ISSN: 2715-0143 (Online)
DOI : 10.21580/wjit

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License

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