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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang Variance : Journal of Statistics and Its Applications Buletin Ilmiah Sarjana Teknik Elektro Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Statistika dan Aplikasinya Journal Of Human And Education (JAHE) Journal of Data Insights Scientific Journal of Computer Science
Ariska Fitriyana Ningrum
Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Public Health Social Sciences Other

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Identification of Dominant Topics in Public Discussions on IKN using Latent Dirichlet Allocation (LDA) and BERTopic Ariska Fitriyana Ningrum; Florence Jean B. Talirongan; Diana May Glaiza G. Tangaro
Scientific Journal of Computer Science Vol. 1 No. 1 (2025): January
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjcs.v1i1.2025.19

Abstract

This study aims to analyze public opinion related to the relocation of Indonesia's National Capital City (IKN) through topic modeling on Twitter data. The two main approaches used are Latent Dirichlet Allocation (LDA) based on Bag of Words and BERTopic based on Transformer language model. LDA was chosen for its ability to identify topic distribution in large text collections, while BERTopic was used to overcome the limitations of LDA in capturing semantic meaning in short and informal texts such as tweets. The analysis was conducted on a collection of tweets discussing the relocation of IKN, with the aim of uncovering the main themes and public perceptions. The result of LDA showed three main topics in the public discussion, namely (1) political debate and nationalism related to the relocation, (2) policy implementation and project execution, and (3) economic justification and challenges facing Jakarta. Mean-while, BERTopic identified topics with more contextual representations, including aspects of investment, economic impact construction progress, and public perception. Dominant topics include urban relocation, investment in IKN, and socio-economic impacts. The novelty of study lies in the comparison of two topic modeling approaches in the context of social media sentiment analysis related to major public policy issues. These findings not only enrich the understanding of the narratives that develop in society, but also provide important insights for policy makers in responding to public opinion more appropriately and contextually.
Co-Authors Alfian Ma’arif Alwan Fadlurohman Amri, Saeful Anggun Lestari, Febi Asno Azzawagama Firdaus Aura Hisani, Zahra Dannu Purwanto Dhani, Oktaviana Rahma Diana May Glaiza G. Tangaro Florence Jean B. Talirongan Furizal, Furizal Ihsan Fathoni Amri Kariyamin, Kariyamin Kusuma Wardani, Amelia M. Al Haris Musa, Fitri Diana Nakib, Arman Mohammad Prizka Rismawati Arum Rahma Dhani, Oktaviana Rohim, Febrian Hikmah Nur Sitti Sahara Wardani, Amelia Kusuma Wijaya, Setiawan Ardi Yunanita, Novia Yusrin, Yusrin Zahra Aura Hisani