Abstract:
The spread of the COVID-19 virus has now become a pandemic because it has spread
throughout the world, including Indonesia. The prositive case rate and the increasing
death rate led the Indonesian government to make a regulation limiting community
activities to break the chain of spread of COVID-19 in Indonesia. This regulation is a
Large-Scale Social Restriction (PSBB. This becomes a polemic for some Indonesian
people, especially those who do not have a fixed income. Many social media users discuss
the implementation of PSBB in Indonesia. This study aims to find out how public’s
sentiment towards the implementation of PSBB in Indonesia during the new normal
period through tweets on social media Twitter using the Support Vector Machine (SVM)
method. The data obtained for the implementation of the PSBB before the new normal
was 322 tweet data that had been labeled while the tweet data for after the new normal
was 653 data that had been labeled. The results obtained using the k-fold cross validation
and confusion matrix method on the model created results in the highest accuracy rate is
81% with the distribution of data 90% : 10% for data before the new normal and for the
data after the new normal, the highest accuracy value is 71% with the distribution of data
80% : 20%. The use of k-fold cross validation produces the highest accuracy value of
78% with fold value = 8 for data before new normal, while for data after new normal, the
highest accuracy values is 73% with fold value = 1.
