Public Sentiment Analysis of Non-Subsidized Fuel Price Increases Due to the Closure of the Strait of Hormuz Using IndoBERT
DOI:
https://doi.org/10.58466/kx4xgz78Keywords:
Sentiment Analysis, Non-Subsidized Fuel, Deep Learning, IndoBERT, Natural Language Processing, Strait of Hormuz, XAbstract
Public discussions regarding the potential increase in non-subsidized fuel prices resulting from the closure of the Strait of Hormuz on the X platform between January 1, 2026, and May 17, 2026, were highly intensive and generated diverse public responses to the global economic impacts triggered by the geopolitical conflict between Iran and Israel. The primary issue addressed in this study is the growing public concern over the possibility of rising non-subsidized fuel prices, which may affect transportation costs, logistics distribution, and daily living expenses. This study aims to analyze public sentiment toward this issue using the IndoBERT deep learning model to obtain a more accurate understanding of public opinion trends. Data were collected through a scraping process on the X platform using keywords related to non-subsidized fuel and the Strait of Hormuz. The collected data were then processed through several preprocessing stages, including case folding, noise removal, tokenization, stopword removal, and stemming, before being classified into positive, neutral, and negative sentiment categories. Out of 412 analyzed tweets, negative sentiment emerged as the dominant category at 49.8%, followed by neutral sentiment at 48.5%, while positive sentiment accounted for only 1.7%. The findings indicate that the majority of the public expressed concern regarding the potential increase in non-subsidized fuel prices and its impact on economic conditions and household expenditures.
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