Pemodelan Topik pada Cuitan tentang Penyakit Tropis di Indonesia dengan Metode Latent Dirichlet Allocation

Abstract

Indonesia has a wide area and society. Therefore, a lot of information appear through social media, especially Twitter. This study aims to find out about conversation topics discussed by Indonesian people related to tropical diseases especially leprosy, malaria, and dengue fever. To find out the discussion topics, it can use the modeling topics analysis. One of the methods in topic modeling is Latent Dirichlet Allocation (LDA). Tweet data on tropical diseases in Indonesia was analyzed through this method. The study results showed that LDA was succeed in modeling the trend of Indonesian people's conversation topics related to tropical diseases. It obtained as many as 5 topics with a coherence value of 0.576453. Based on the results of the topic modeling, it can be concluded that the topics are such as the used funds to eradicate malaria and dengue fever, covid-19, blindness and leprosy, and its treatments and preventions.