Covid-19 Hoax Detection Using KNN in Jaccard Space
| Main Authors: | Utami, Ema, Iskandar, Ahmad Fikri, Hidayat, Wahyu, Prasetyo, Agung Budi, Hartanto, Anggit Dwi |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia
, 2021
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| Subjects: | |
| Online Access: |
https://journal.ugm.ac.id/ijccs/article/view/67392 https://journal.ugm.ac.id/ijccs/article/view/67392/31839 |
Daftar Isi:
- Social media has become a communication key to spark thinking, dialogue and action around social issues. Hoax is information that added or subtracted from the content of the actual news. The spread of unconfirmed Covid-19 news can cause public concern. The purpose of this research was to modify KNN with Jaccard Space in the classification of hoax news related to Covid-19. The data used from Jabar Saber Hoaks and Jala Hoaks. The classification results with KNN with Jaccard Space and stemming Nazief & Adriani get the highest accuracy than other models in this research. The accuracy of the KNN model on the Jaccard Space with stemming Nazief & Adriani and K = 5 was 75.89%, while for Naïve Bayes was 65.18%.