Sentiment-Driven Stock Market Analysis: Predicting LQ45 Stock Index Based on Indonesian Financial News - Dalam bentuk buku karya ilmiah

FADLAN AKMAL RAMADHAN

Informasi Dasar

47 kali
25.05.355
000
Karya Ilmiah - Thesis (S2) - Reference

Stock market fluctuations are influenced not only by numerical indicators but also by investor sentiment and perceptions shaped by economic behavior. However, the integration of news sentiment through sentiment analysis features into stock forecasting remains limited, with the use of sentiment probabilities particularly underexplored despite their potential to enhance prediction performance. To develop a more robust and precise forecasting framework, this study integrates sentiment probabilities from Indonesian financial news titles into deep learning models, focusing on the LQ45 stock index from 1 January 2024 to 31 March 2025, covering 297 open market days.  Sentiment features such as probabilities for positive, negative, and neutral classes as well as their corresponding hard labels were extracted from 158,514 Indonesian financial news titles using a fine-tuned IndoBERT model. These sentiment features were combined with the historical close index of LQ45 and configured with lag and time step settings to form the input of the LSTM forecasting model. Two sentiment integration methods were compared: direct input of sentiment probabilities from IndoBERT's softmax output and aggregated sentiment scores derived from either probability or hard labels. The results show that integrating sentiment features improves the model’s predictive performance. Notably, Scenario 5, which used aggregated sentiment scores based on probabilities, achieved the best results with an MAE of 14.16, RMSE of 17.95, and MAPE of 1.88\%. This also significantly outperformed the aggregated sentiment score derived from hard labels.
 

Subjek

DATA SCIENCE
 

Katalog

Sentiment-Driven Stock Market Analysis: Predicting LQ45 Stock Index Based on Indonesian Financial News - Dalam bentuk buku karya ilmiah
 
 
 

Sirkulasi

Rp. 0
Rp. 0
Tidak

Pengarang

FADLAN AKMAL RAMADHAN
Perorangan
Putu Harry Gunawan
 

Penerbit

Universitas Telkom, S2 Informatika
Bandung
2025

Koleksi

Kompetensi

 

Download / Flippingbook

 

Ulasan

Belum ada ulasan yang diberikan
anda harus sign-in untuk memberikan ulasan ke katalog ini