Abstract :
Twitter is a social media platform that provides services for users to
communicate online or see various things that are currently happening. Public
figures both among celebrities, artists and politics are often discussed and trending
topics. The impact is that the pros and cons among users of the accounts of public
figures being discussed cause a lot of sentiment, either positive or negative.
Therefore, we need a system that can classify each user's reply to the account of a
public figure as a consideration for changing communication patterns for the
better. The classification system that will be made is based on 1500 datasets that
have been previously labeled and divided into 80% training data, 20% test data.
The results of the confusion matrix testing process obtained the highest accuracy
of 79% with a comparison of training data and test data of 8: 2, 76% with a data
comparison of 9: 1, 77% with a data comparison of 7:3 and 74% with a data
comparison of 6:4.