Sentiment Analysis of Technology Utilization by PekanbaruCity Government Based on Community Interaction in SocialMedia

Abstract

Government services for the public are currently utilizing
technology, especially in the city of Pekanbaru. The
government has currently centralized all services for the
public, both online and offline, in public service malls. The
type of service that uses technology, especially for online
services, has received criticism from the netizen in online
media such as Twitter. In an effort to improve services for
the public, the government must listen to the wishes of the
people. To resolve that issue, this study will use sentiment
analysis to see positive, negative, and neutral comments. The
method used is to see the accuracy generated using the Naïve
Bayes Classifier (NBC) method. Bayes Classifier is a
statistical classifier, where the classifier can predict the
probability of class membership of a data tuple that will fall
into a certain class, according to the probability calculation.
Accuracy results are obtained by dividing training data and
testing data with a comparison of 70%:30% with an accuracy
value of 55.56%, Precision 64%, recall 80%, f-score 71.2%.