Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/115326
Title: Analisis Topik Pengguna Twitter terhadap Vaksinasi Covid-19 di Indonesia Menggunakan Latent Dirichlet Allocation
Other Titles: Topic Analysis of Twitter User About Covid-19 Vaccination in Indonesia Using Latent Dirichlet Allocation
Authors: Hardhienata, Medria Kusuma Dewi
Herdiyeni, Yeni
Elhan, Amin
Issue Date: 2022
Publisher: IPB University
Abstract: Pandemi Covid-19 mendorong banyak pihak agar mampu beradaptasi dengan kondisi terkini. Salah satu program yang diluncurkan pemerintah agar dapat mengatasi penyebaran Covid-19 adalah dengan menjalankan progam vaksinasi. Agar dapat mengetahui animo masyarakat terkait program vaksinasi Covid-19 yang diluncurkan, perlu dilakukan analisis topik. Tujuan penelitian ini adalah mengetahui topik-topik terkait vaksin Covid-19 yang dibicarakan masyarakat di Twitter dan melakukan analisis sentimen pengguna Twitter terhadap vaksinasi corona. Untuk mendapatkan topik-topik pembicaraan terkait vaksin Covid-19 digunakan metode Latent Dirichlet Allocation (LDA). Metode penelitian yang dilakukan meliputi praproses data, pelabelan sentimen, penentuan jumlah, pemodelan topik, dan analisis topik. Hasil dari penelitian yang yang dilakukan adalah berupa topik-topik terkait vaksinasi Covid-19 yang sedang diperbincangkan di media Twitter di Indonesia. Tiga topik besar yang dibicarakan yaitu mengenai vaksinasi gratis oleh pemerintah Indonesia, sebab akibat mengikuti vaksinasi, dan varian vaksinasi.
The Covid-19 pandemic has pushed many stakeholders to be able to adapt to the current conditions. One of the programs launched by the government to overcome the spread of Covid-19 is to run a vaccination program. To know the public's interest regarding the Covid-19 vaccination program that was launched, it is necessary to conduct a topic analysis. The purpose of this study was to find out the topics related to the Covid-19 vaccine that were discussed by the public on Twitter and to analyze the sentiments of Twitter users towards corona vaccination. To get topics of discussion related to the Covid-19 vaccine, Latent Dirichlet Allocation (LDA) method is used, while the Random Forest algorithm is used to carry out sentiment analysis. The research methods include data preprocessing, sentiment labeling, number determination, topic modeling, and topic analysis. The results of the research carried out are in the form of topics related to Covid-19 vaccination which are being discussed on Twitter media in Indonesia. The three major topics discussed were about free vaccination by the Indonesian government, the causes and effects of following vaccination, and vaccination variants.
URI: http://repository.ipb.ac.id/handle/123456789/115326
Appears in Collections:UT - Computer Science

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