Sentiment Analysis of Covid-19 Handling in Indonesia Based on Lexicon Weighting

Covid-19, a contagious disease, has been classified as global pandemic. Indonesia, one of the ASEAN countries, taken various measures to combat spread this disease. One government's initiatives tackle pandemic is PeduliLindungi application, through which public provides feedback on government policies. However, analyzing and comprehending opinions in non-subjective manner poses challenge objectively evaluating services. This study aims address issue by conducting sentiment analysis Covid-19 handling using lexicon-based weighting system that includes SentiStrengthID InSet. The decision tree (DT) machine learning algorithm utilized evaluate polarity results provided lexicon. indicate towards Indonesia negative based both InSet weights. Evaluating performance with lexicon, DT-entropy DT-gini models achieved an accuracy 82% 83%, respectively. Similarly, 81% 82%,