CD Skripsi

Implementasi Jaringan Saraf Konvolusi Terhadap Analisis Sentimen Tentang Kuliah Online Pada Masa Covid-19

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ABSTRACT
Study that was face-to-face made students has high social interaction. Since the
COVID-19 virus infected Indonesia in 2020, study meetings have been changed to
an online study system that uses the internet 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.
Keywords: Online course, sentiment analysis, convolutional neural network,
twitter

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1703122411

Penerbit

Pekanbaru : Universitas Riau - FMIPA - STATISTIKA., 2022

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1703122411

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

STATISTIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

Deti

Versi lain/terkait

Lampiran Berkas

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