Keywords
deep learning
sentiment analysis
prakerja card
How to Cite
Abstract
The Indonesian government launched the Prakerja (pre-employment) card in the midst of the COVID-19 pandemic, and
the local citizens have voiced their opinions about this controversial program through social media such as Twitter. People’s
comments on it can be useful information, and this research tries to analyze the sentiment regarding the Prakerja Card program
using the Convolutional Neural Network and Naive Bayes methods. The main task in this sentiment analysis is analyzing the data
and then classifying them into one of the following classes: positive, negative or neutral. Naive Bayes is an algorithm that is often used
in sentiment analysis research, and the results have been very good. Convolutional neural network (CNN) is a deep learning algorithm
that uses one or more layers commonly used for pattern recognition and image recognition. Having applied these methods, this
research found that the CNN model with the GlobalMaxPooling layer is the best model of the other two CNN models. Sentiment
analysis has the best accuracy of 78.5% on the CNN method, and NBC of 76.2% accuracy. The best accuracy result in K-fold with
five classes is 85.4% on the CNN model with a learning rate optimization of 0.00158. While the average accuracy on NBC only reached
75.3%
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