English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Hoax or fake news spreads very fast on social media. The news can influence readers and poisoning their mind. It is important to identify the hoax news broadcasted on social media. Some methods to predict hoax are to use Support Vector Classifier, Logistic Regression, and MultinomialNaiveBayes. In this study, we applied Long Short-Term Memory to identify the hoaxes. System performance was measured based on the precision, recall, accuracy, and F-Measure scores. The experimental results, conducted on the hoaxes data obtained the average value of precision, recall, accuracy, and F-Measure of 0.94, 0.96, 0.95, and 0.95 respectively. The results shows that the proposed Long Short-Term Memory has better performance compared to the latest method.

Implementasi Long Short-Term Memory untuk Identifikasi Berita Hoax Berbahasa Inggris pada Media Sosial