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All Journal Eduvest - Journal of Universal Studies Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC)
Indra Budi
Faculty of Computer Science, Universitas Indonesia
Aerospace Engineering Computer Science & IT Health Professions Neuroscience Social Sciences

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Sentiment Analysis on Jurassic Park Development in the Komodo Conservation Area Annisa Septiana Sani; Indra Budi
Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Vol. 1 No. 1 (2022): Proceeding of International Conference on Information Science and Technology In
Publisher : Universitas Respati Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35842/icostec.v1i1.5

Abstract

Rinca Island is included in one of the islands in NTT Province, which is used as a National Park to protect Komodo dragons. According to the government's agenda, in June 2021, Rinca Island will build a world-class premium tourist destination project for tourists who want to see Komodo, which is called Jurassic Park Komodo. The existence of tourism is expected to be able to attract tourists and investment. However, the news about project development that is not in accordance with the conservation value has created public sentiment towards the project development process. The purpose of this study is to analyze public sentiment related to the classification of support & against the development of Jurassic Park in the Komodo Conservation Area and to measure the accuracy using two methods, namely Naïve Bayes and Decision Tree.
Sentiment Analysis and Topic Modeling of Public Opinion on Indonesia New Capital City Development Policies Michael David Angelo; Reyhan Widyatna Harwenda; Indra Budi; Aris Budi Santoso; Prabu Kresna Putra
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.
Co-Authors Annisa Septiana Sani Aris Budi Santoso Michael David Angelo Prabu Kresna Putra Reyhan Widyatna Harwenda