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All Journal Jurnal Teknimedia: Teknologi Informasi dan Multimedia
Suryati Suryati
Universitas Bumigora
Computer Science & IT Control & Systems Engineering Engineering

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ANALISIS SENTIMENT KEUANGAN MENGGUNAKAN FINE-TUNED FINBERT Heroe Santoso; Raisul Azhar; Suryati Suryati; Melati Rosanensi; I Made Yadi Dharma; Husain Husain; Ahmat Adil; Muhamad Azwar; I Putu Hariyadi
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2025): Desember 2025
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v6i2.316

Abstract

Financial information is a critical type of data for analysis. However, because much of it is unstructured and widely dispersed, an appropriate analytical method is required, one of which is sentiment analysis. In the financial context, sentiment analysis is employed by the industry to assess public perceptions of companies or market conditions. This study implements a fine-tuned FinBERT model to perform sentiment analysis in the financial sector. The dataset used is a combination of FiQA (Financial Question Answering) and The Financial PhraseBank, consisting of English sentences labeled with negative, neutral, and positive sentiments. The research process involved data preprocessing, tokenization, data splitting, model training, and evaluation using accuracy, precision, recall, F1-score, and confusion matrix metrics. The results show that the model achieved 82% accuracy, with its best performance in the positive class (F1-score 0.88) and the neutral class (F1-score 0.85), but weaker performance in detecting the negative class (F1-score 0.49). These findings indicate that the fine-tuned FinBERT is effective for financial sentiment analysis, particularly for positive and neutral sentiments, though improvements are needed in negative sentiment detection, potentially through expanding training data diversity or applying data augmentation techniques
Co-Authors Ahmat Adil Azhar, Raisul Husain Husain I Made Yadi Dharma I Putu Hariyadi Melati Rosanensi Muhamad Azwar Santoso, Heroe