Indonesia's News Topic Discussion about Covid-19 Outbreak using Latent Dirichlet Allocation

摘要

News related to Covid-19 or Corona dominates the news in several media. From various perspectives, a number of news have been produced regarding the corona outbreak. The purpose of this research is to look at various news topics related to corona, both in national online media and in local online media. This study uses the Latent Dirichlet Allocation (LDA) algorithm to find out news topics related to corona. Preprocessing was carried out on existing articles such as removing punctuation marks, numbers, and removing stopwords. This process is preceded by lowering the text to get unique words. The number of articles collected was 12.883 news titles from the national online media RMOL and the Aceh Tribunnews regional online media in the period January to May 2020. The news items came from various news categories such as politics, law, health, economy, sports and others. Based on this research, by using the LDA algorithm, evaluate using coherence value and visualize the topics, will have the best perspective of how many topics can be created. RMOL news articles have 12 topics discussion with the coherence value is 0.538795. Aceh Tribunnews has 8 topics with the coherence value of 0.522946.