Sentiment Analysis on 2024 Regional Elections using Hybrid CNN-SVM with Semantic Features and Word2Vec - Dalam bentuk buku karya ilmiah

SYAHBILLA PUTRI ANDINNY

Informasi Dasar

85 kali
25.04.387
000
Karya Ilmiah - Skripsi (S1) - Reference

Regional Head Election is a political agenda held
every five years. Everyone has their point of view on assessing
the candidates. These political conversations often appear on
platform X, a social media to exchange information, responses,
comments, and even emotions. These public expressions can be
classified into positive, negative, and neutral sentiments. This
political phenomenon is the object of research to understand a
hybrid deep learning model that combines Convolutional
Neural Network (CNN) and Support Vector Machine (SVM),
enhanced with TF-IDF extraction features, IndoBERT
semantics to understand the deeper context of Indonesian text
and Word2Vec that represents words in the form of vectors with
similar meanings against testing on three corpus X, IndoNews,
and X+IndoNews. This research analyzes the perspectives of
Indonesian social media users surrounding the 2024 Regional
Elections using 60,000 Indonesian tweet

Subjek

DATA SCIENCE
 

Katalog

Sentiment Analysis on 2024 Regional Elections using Hybrid CNN-SVM with Semantic Features and Word2Vec - Dalam bentuk buku karya ilmiah
 
v, 8p.: il,; pdf file
 

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Pengarang

SYAHBILLA PUTRI ANDINNY
Perorangan
Erwin Budi Setiawan
 

Penerbit

Universitas Telkom, S1 Informatika
Bandung
2025

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Kompetensi

 

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