Twitter, Instagram, Youtube Speak: Understanding Sentiments on LRT Jabodebek Services via Inset Lexicon, IndoBERT and BERTopic Approaches - Dalam bentuk buku karya ilmiah

IBADURROHMAN IRFAN FATANI

Informasi Dasar

238 kali
24.04.1951
000
Karya Ilmiah - Skripsi (S1) - Reference

Rapid urbanization in the Jabodetabek region has led to an increased demand for public transportation. Responding to this need, the government has initiated the development of a new public transportation mode, namely the LRT Jabodebek. However, as a new public transportation mode, the LRT Jabodebek has both strengths and weaknesses in serving the community. Various public comments are expressed through social media platforms. To enhance service quality, it is crucial to pay attention to public comments. Therefore, a sentiment analysis is required to identify and delve into both positive and negative sentiments regarding the LRT Jabodebek service through comments on Twitter, Instagram, and Youtube. The methodology involves a combination of Lexicon-based, IndoBERT model, and BERTopic approaches to gain a deeper understanding of the Jabodebek LRT service trends. The study reveals that 55.9% of the 8,523 comments carry a negative sentiment, and the IndoBERT model achieves an accuracy of 85.97% in sentiment classification.

Subjek

BIG DATA
 

Katalog

Twitter, Instagram, Youtube Speak: Understanding Sentiments on LRT Jabodebek Services via Inset Lexicon, IndoBERT and BERTopic Approaches - Dalam bentuk buku karya ilmiah
 
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Sirkulasi

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Pengarang

IBADURROHMAN IRFAN FATANI
Perorangan
Herry Irawan
 

Penerbit

Universitas Telkom, S1 Manajemen (Manajemen Bisnis Telekomunikasi & Informatika)
Bandung
2024

Koleksi

Kompetensi

  • EBI3B4 - BIG DATA AND DATA ANALYTICS

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