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All Journal Dinasti International Journal of Education Management and Social Science Eduvest - Journal of Universal Studies
Angelo, Michael David
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Aerospace Engineering Computer Science & IT Education Health Professions Neuroscience Social Sciences

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Sentiment Analysis and Topic Modeling of Public Opinion on Indonesia New Capital City Development Policies Angelo, Michael David; Harwenda, Reyhan Widyatna; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
Eduvest - Journal of Universal Studies Vol. 5 No. 5 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i5.51234

Abstract

This study investigates public sentiment dynamics and dominant thematic concerns related to Indonesia’s new capital city development project (Ibu Kota Nusantara–IKN), particularly in the context of the political leadership transition from President Joko Widodo to President-elect Prabowo Subianto. Utilizing a dataset comprising 9,451 tweets collected from 2017 to 2025, sentiment analysis and topic modeling were applied to classify sentiment polarity and identify prevailing public discourse themes. Various traditional machine learning models—including Naïve Bayes, Support Vector Machine (SVM), AdaBoost, XGBoost, and LightGBM—were systematically compared with transformer-based deep learning models, specifically IndoBERT, to determine their effectiveness in sentiment classification. Results demonstrated that the IndoBERT model outperformed all traditional classifiers, achieving the highest accuracy, precision, recall, and F1 score, highlighting its superior capability in capturing nuanced linguistic patterns within informal social media texts. Independent samples t-tests revealed statistically significant sentiment shifts between the two political phases, emphasizing the impact of leadership transitions on public sentiment. Topic modeling further identified critical themes such as environmental sustainability, socio-economic implications, transparency, governance, and infrastructure development as central concerns driving public discussions. These findings provide actionable insights for policymakers and stakeholders, underscoring the importance of strategic communication and responsiveness to public sentiment in large-scale government initiatives.
Sentiment Analysis on Government Public Policies: A Systematic Literature Review Harwenda, Reyhan Widyatna; Angelo, Michael David; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
Dinasti International Journal of Education Management And Social Science Vol. 6 No. 5 (2025): Dinasti International Journal of Education Management and Social Science (June
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v6i5.4699

Abstract

In the digital era, public discourse on government policies has shifted significantly to online platforms. This presents valuable opportunities for governments to assess real-time public sentiment. However, prior studies on sentiment analysis in public policy remain fragmented, often lacking methodological consistency and domain-wide synthesis. This study conducts a Systematic Literature Review (SLR) to consolidate insights on the techniques, datasets, and trends involved in sentiment analysis applied to government development policies. The review identifies SVM, BERT, and Naive Bayes as the most frequently used and effective methods, with SVM excelling in structured data and simpler tasks, and BERT demonstrating superior performance in handling nuanced textual data. Lexicon based tools such as VADER are also used for quick sentiment classification. Social media platforms, particularly Twitter, emerge as the dominant data sources due to their high volume and real-time nature, while evaluation metrics such as precision, recall, F1-score, and confusion matrix are commonly applied to assess model performance. The findings also reveal evolving research interests from early focus on health policies to recent interest in infrastructure, environmental, and technology-related policies. Public sentiment across these areas varies, with health and environmental policies often eliciting negative responses, while technology policies show more neutral to positive sentiment. By synthesizing methods, datasets, evaluation strategies, and policy domains, this review provides a structured foundation to future research and supports policymakers in designing strategies.
Co-Authors Budi, Indra Harwenda, Reyhan Widyatna Prabu Kresna Putra, Prabu Kresna Santoso, Aris Budi