IMPLEMENTASI JARINGAN SARAF KONVOLUSI TERHADAP ANALISIS SENTIMEN TENTANG KULIAH ONLINE PADA MASA COVID-19
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Date
2022-03
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Publisher
Elfitra
Abstract
This paper discusses online course that use the internet network to stay connected during
the activity. This study aims to see the impact of online course based on someone's
opinion. One of the appropriate methods for this research is sentiment analysis. For this
reason, there are 7000 tweets is analyzed from media social twitter April 2020–April 2021
which convey opinions about online course. Sentiment analysis uses a convolution neural
network (one directional convolution) which classifies data in the form of text documents.
Convolutional neural network is trained using keras programming with 100 epoch. The
convolutional neural network trains using 5600 tweets and predicts 1400 different tweets.
The training results from the convolution neural network give a neutral sentiment as the
most dominant sentiment with amount 76.5% accuracy level.
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Keywords
Online course, Online course, sentiment analysis, convolutional neural network, twitter
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