Skripsi

ANALISIS SENTIMEN MASYARAKAT TERKAIT PEMBANGUNAN IBU KOTA NUSANTARA (IKN) MENGGUNAKAN FINE-TUNING INDOBERT.

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The development of Ibu Kota Nusantara (IKN) has become a topic of public interest, generating various opinions reflecting societal sentiment. This study aims to analyze public sentiment toward the development of IKN using a fine-tuned IndoBERT-based deep learning model. The dataset was collected from platform X, consisting of 18,264 training data, 2,283 validation data, and 2,283 test data, with sentiments categorized as positive, neutral, and negative. The model training was conducted using four different configurations of learning rates and epochs. The results indicate that the configuration with a learning rate of 5e-7 and 10 epochs achieved the best performance, with an accuracy of 89% and precision, recall, and F1-score values of 0.88 each. Other configurations yielded lower results, with a learning rate of 5e-5 experiencing overfitting on the training data. This study demonstrates that the IndoBERT model can be effectively used for sentiment analysis in the Indonesian language, with outcomes varying based on the training configurations applied.

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Availability

Detail Information

Series Title

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Call Number

T1628622024

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024

Collation

xix, 82 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

unmediated

Carrier Type

other (computer)

Edition

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Subject(s)

Pemrosesan data
Prodi Teknik Informatika

Specific Detail Info

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Statement of Responsibility

MURZ

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