Rough Set : Utilizing Machine Learning for the Covid-19 Vaccine

Andini, Silfia and Arminarahmah, Nur and Daengs, Achmad and Surya, Sara (2021) Rough Set : Utilizing Machine Learning for the Covid-19 Vaccine. In: 2021 4th International Symposium on Power Electronics and Control Engineering.

Text 20221-012011-Proceding Silfia Andini Jurnal of Physics Conference Series, 2022, 2394(1), 012011, Volume 2394, 2022.pdf Download (1MB)

Abstract

Rough Set is a machine learning algorithm that analyses and determines important attributes based on an uncertain data set. The purpose of this study is to classify public interest in the Covid-19 vaccine. Vaccination is one of the solutions from the government that is considered the most appropriate to reduce the number of Covid-19 cases. Data collection was taken through a questionnaire distributed to the village community in Air Manik Village, Padang-West Sumatra, randomly as many as 100 respondents. The assessment attributes in this study are Vaccine Understanding (1), Environment (2), Community Education (3), Vaccine Confidence (4), and Cost (5), while the target attribute is the result that contains the community's interest or not to participate in vaccination. The analysis process is assisted using the Rosetta application. This study resulted in 3 reductions with 58 rules based on 100 respondents. This study concludes that the Rough Set algorithmcan be used to classify public interest in the Covid-19 vaccine. Based on this research, it is hoped that it can provide information and input for local governments to be more aggressive in urging and encouraging the public to be vaccinated.

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