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All Journal Journal Technology Information and Data Analytic
Alfian Rusydi
Universitas Darma Persada
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science Other

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Public Sentiment Analysis on Instagram and X toward the Cancellation of Fuel Purchases from Pertamina by Private Fuel Stations Using the BERT Method Alfian Rusydi; Timor Setiyaningsih
Journal TIFDA (Technology Information and Data Analytic) Vol 3 No 1 (2026): Journal Technology Information and Data Analytic
Publisher : Prodi Teknologi Informasi Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70491/tifda.v3i1.134

Abstract

This study aims to analyze public sentiment toward the cancellation of fuel purchases from Pertamina by private fuel stations based on comments collected from Instagram and X (Twitter). Sentiment analysis was conducted using the Bidirectional Encoder Representations from Transformers (BERT) model, which is capable of capturing contextual semantic information in text more effectively than traditional machine learning approaches.The research stages include data collection through web scraping, text preprocessing, sentiment labeling into positive, neutral, and negative categories, fine-tuning a pretrained Indonesian BERT model, and model evaluation using accuracy, macro recall, and F1-score. The experimental results indicate that the BERTbased model is able to classify public sentiment effectively. Negative sentiment dominates the dataset and is characterized by expressions of dissatisfaction and criticism toward the policy. Neutral sentiment mainly contains descriptive and informational statements, while positive sentiment appears in a considerably smaller proportion. The findings provide insights into public perceptions of the policy related to Pertamina and private fuel stations and demonstrate the potential of BERT-based sentiment analysis as a decision-support tool for monitoring public opinion on social media.
Co-Authors Timor Setiyaningsih