Analisis Big Data untuk Deteksi Hoaks dan Disinformasi di Platform Berita Online - Mitranikasih Laia; Ayuliana; Wasiran; Muhammad Lukman Hakim; Dikky Suryadi (Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), 2025)
In the digital era, the spread of hoaxes and disinformation on online news platforms is a serious challenge that can affect public opinion and social stability. This research aims to analyze the application of Big Data technology in automatically detecting hoaxes and disinformation. The methods used include data collection from various online news sources, text processing using Natural Language Processing (NLP), and the application of machine learning algorithms to classify news based on their level of credibility. The dataset used includes news from various categories, which are validated with trusted sources. The results show that the combination of Big Data, NLP, and machine learning techniques can improve the accuracy of hoax detection with a high success rate. This study is expected to contribute to the development of a fake news detection system that is more effective and adaptive to the trend of information dissemination in the digital world.