THE PREDICTION OF RETWEET USING LONG SHORT-TERM MEMORY METHOD WITH THE TOPIC OF COVID-19 VACCINATION

ZAHRA FADIAH PUTRI

Informasi Dasar

49 kali
23.04.2598
006.35
Karya Ilmiah - Skripsi (S1) - Reference

In last 2019, the Covid-19 outbreak was first reported, infecting at least 20.1 million people and killing more than 737,000 people worldwide and still counting. In Indonesia, the government announced that the Covid-19 vaccination is an obligation for everyone. The rapid development of technology has made social media a platform of spreading news. One of the social media that plays an important role is Twitter. The tweets can be shared with other users by re-tweeting process.The greater the number of retweets, the wider the existing information. Therefore, the retweet feature plays a crucial role in spreading information. This study discusses retweet predictions about Covid-19 vaccination using the Long Short-Term Memory (LSTM) method with the application of hyperparameter tuning to obtain the best result and get an accuracy or closeness values (98%),a precision or closeness value (74%), a recall value (91%), and an f-1 score value or a comparison value (93%).

Subjek

NATURAL LANGUAGE PROCESSING
Memory and learning,

Katalog

THE PREDICTION OF RETWEET USING LONG SHORT-TERM MEMORY METHOD WITH THE TOPIC OF COVID-19 VACCINATION
 
 
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Pengarang

ZAHRA FADIAH PUTRI
Perorangan
Jondri, Indwiarti
 

Penerbit

Universitas Telkom, S1 Informatika
Bandung
2023

Koleksi

Kompetensi

 

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