Analisis Sentimen Berita Keuangan Menggunakan Jaringan RNN-LSTM

ICORIS : 2022 4th International Conference on Cybernetics and Intelligent System
4 Maret 2023 oleh
Analisis Sentimen Berita Keuangan Menggunakan Jaringan RNN-LSTM
kelvin leonardi

Abstrak


Identifying financial sector sentiment, primarily through the financial news, is crucial in financial investment decisions. Financial Sentiment Analysis (FSA) significantly affects the secondary market and provides a significant contribution. Long Short-Term Memory (LSTM) is a deep learning model, especially Recurrent Neural Network (RNN), a reasonably popular model designed for long-term​ constraints. Various methods have been proposed in previous studies, but the performance generated by the model in previous studies is still below 90%, so it has the opportunity to be improved. This study aims to present a sentiment analysis model by implementing the RNN-LSTM. The results showed that the model used for sentiment analysis of financial news reached 92.23% precision, 91.54% accuracy, 90.99% recall, and an f1 score of 91.61%. The model we built is helpful for understanding trends and opinions for making financial and other investment decisions.

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Kelvin Leonardi Kohsasih

Universitas Potensi Utama

B. Herawan Hayadi

Universitas Potensi Utama

Robet

STMIK TIME

Carles Juliandy

STMIK TIME

Octara Pribadi

STMIK TIME

Andi

STMIK TIME 

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Citation:

K. L. Kohsasih, B. H. Hayadi, Robet, C. Juliandy, O. Pribadi and Andi, "Sentiment Analysis for Financial News Using RNN-LSTM Network," 2022 4th International Conference on Cybernetics and Intelligent System (ICORIS), Prapat, Indonesia, 2022, pp. 1-6, doi: 10.1109/ICORIS56080.2022.10031595.

Publication:
2022 4th International Conference on Cybernetics and Intelligent System (ICORIS)
DOI:
10.1109/ICORIS56080.2022.10031595

Copyright:

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Analisis Sentimen Berita Keuangan Menggunakan Jaringan RNN-LSTM
kelvin leonardi 4 Maret 2023
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