Vaccine opinion clustering in Indonesia using K-means algorithm and elbow method.

During the pandemic, apart from maintaining social distance, people are encouraged to vaccinate. Vaccination is a step to make the body's immune stronger against COVID-19. Several types of vaccines circulating in Indonesia are Sinovac, AstraZeneca, Sinopharm, Moderna and Pfizer. Nowadays people often share opinions on social media regarding many things. One of them is about the vaccination program. Many people talk about experiences with vaccines, types of vaccines, vaccine resistance and other things related to vaccines. To succeed in vaccination program, the government needs to monitor and analyze public opinion related to vaccines to make better vaccination policies. This research proposes to cluster public opinion from social media using the K-Means algorithm with the Elbow method to get the optimal number of clusters. Each cluster will be grouped based on the similarity of one record to another. From the result of the experiments, it was found that 3 is the best number of clusters. Cluster 1 is the largest cluster with a discussion pattern about the experience of having been vaccinated and post-vaccinated. Cluster 0 contains the relationship between Israel and Palestine related to vaccines and cluster 2 talks vaccines related to schools. [ABSTRACT FROM AUTHOR]