  Covid-19 has grown rapidly in all parts of the world and is considered an
international disaster because of its wide-reaching impact. The impact of
Covid-19 has spread to Indonesia, especially in the slowdown in economic
growth. This was influenced by the implementation of Community Activity
Restrictions (PPKM) which limited community economic activities. This study
aims to analyze the mapping of public sentiment towards PPKM policies in
Indonesia during the pandemic based on Twitter data. Knowing the mapping of
public sentiment regarding PPKM is expected to help stakeholders in the policy
evaluation process for each region. The method used is BERT with IndoBERT
specific model. The results showed the evaluation value of IndoBERT f-1 score
reached 84%, precision 86%, and recall 84%. Meanwhile for the evaluation of the
use of SVM f-1 score 70%, 72% precision, and 70% recall. Multinominal Na\"ive
Bayes evaluation shows f-1 score 83%, precision 78%, and recall 80%. As a
conclusion, BERT method with the IndoBERT model is proven to be higher than
classical methods such as SVM and Multinominal Na\"ive Bayes.
