Data Science-Based Statistical Modeling in Revealing Community Intentions and Behaviors for the Covid-19 Vaccine
Adji Achmad Rinaldo Fernandes1, *, Solimun Solimun2, Intan Rahmawati3
Abstract
At the beginning of 2020, the world community was shocked by the emergence of Covid-19 or better known as the coronavirus. Covid-19 is a new type of virus that at the beginning of its appearance no vaccine could overcome this virus. After this virus emerged, many researchers tried to create a vaccine to overcome this virus. Vaccination is one of the most effective efforts in tackling Covid-19. This study wants to examine the effect of Benefits of Vaccines and Ease of Getting Vaccines on Intention to get vaccinated with Covid-19 and Covid-19 Vaccinated Behavior. The approach used in this research is descriptive, exploratory, and explanatory using a mixed method. This study uses several analytical methods, namely, DNA used to compose the questionnaire, cluster analysis is used to group several data sets that have been obtained, and path analysis is used to model intention and Covid-19 Vaccinated Behavior. The sampling technique used is simple random sampling. variables Attitude, Subjective Norms, Perceived Behavioral Control, benefits of vaccines, and ease of Getting Vaccines were able to explain the diversity of the Intention to get vaccinated with Covid-19 variables by 41.2%, while the other 58.8% were influenced by variables outside the model. The originality of the theory in this study lies in the use of variables based on DNA analysis (Discourse Network Analysis). While originality in terms of application lies in the analysis of Intention and Covid-19 Vaccinated Behavior.
* Address correspondence to this author at the Statisctics, Brawijaya University, Indonesia; E-mail: fernandes@staff.ub.ac.id
