JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 6, No 3 (2022): Juli 2022

Optimasi Naive Bayes dan Cosine Similarity Menggunakan Particle Swarm Optimization Pada Klasifikasi Hoax Berbahasa Indonesia

Arfan Yoga Aji Nugraha (Universitas AMIKOM Yogyakarta, Yogyakarta)
Ferian Fauzi Abdulloh (Universitas AMIKOM Yogyakarta, Yogyakarta)

Article Info

Publish Date
25 Jul 2022

Abstract

The widespread circulation of hoax news in the information technology era is increasingly troubling, therefore in this era an algorithm to classify hoax news is necessary, in this study researchers focused on optimizing the accuracy of hoax news classification in text documents. The algorithm that will be used is Naive Bayes and cosine Similarity which previously has been applied with particle swarm optimization algorithm. In this study, it was concluded that after feature selection using PSO in the Naive Bayes algorithm the accuracy obtained increased from 0.91 to 0.93 while in the cosine similarity algorithm the accuracy increased from 0.62 to 0.73 after feature selection using PSO

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Journal Info
JURNAL MEDIA INFORMATIKA BUDIDARMA
Website

Abbrev

mib

Publisher

Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer ...