C4.5 Algorithm Implementation For Public Sentyment Analysis Covid-19 Vaccine - Devi Astri Nawangnugraeni; Abdillah, M. Zakki; Suseno, Akrim Teguh (Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning, 2022)
Corona virus disease is one of the dangerous diseases and has been prevented by giving vaccinations. In an effort to prevent, there must be a positive or negative public response. One of the media facilities used to convey public responses is Twitter. The public's reaction can be analyzed using public sentiment analysis using C4.5 algorithm. The purpose of paper for determine public's response to the administration of moderna and pfizer vaccinations. The implemented methodology starts from collecting data taken from tweets, pre-processing, classification using the C4.5 algorithm and validation using k-fold cross validation. Based on the results of the moderna keyword analysis, the positive sentiment response was 6% and negative sentiment was 94%, while the pfizer keyword positive sentiment was 12.4% and negative sentiment was 87.6%. The results of test iteration that have been carried out 3 times, the average error value is 38%.