Implementation of K-means Clustering Algorithm to Analyze the Familial Sentiments Towards COVID-19 Vaccination For Elementary School Students in Kalawat District

Abstract

Due to the Ministry of Health's policy, the Indonesian government mandates the public to receive the COVID-19 vaccination as a form of immunity against the coronavirus. This vaccination is not only for adults but also for children of a certain age. Regarding the provision of vaccination for elementary school students aged between 6 to 11 years, the families' responses to this predicament can cause significant barriers to those students being fully vaccinated. Thus, this research developed a web-based application that incorporated the K-means clustering method to group the sentiments of the families into three clusters, namely positive, neutral, and negative. The results showed that the application can identify and cluster the different familial responses from 279 respondents in Kalawat District toward the administration of COVID-19 vaccination to their underage children. The most dominant familial sentiment is positive followed by neutral and negative sentiments with the number of respondents as many as 120 respondents (43%), 113 respondents (41%), and 46 respondents (16%) respectively. This research can help the Health Office in North Minahasa Regency to evaluate public sentiments about vaccination for elementary school students as well as look for better ways to encourage vaccine trust and confidence in this district.