Sentiment Analysis on X, TikTok, and Instagram on Indonesian Capital relocation using Support Vector Machine
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Syawalian Rais Dwi Jayanto
*
Satya Wacana Christian University, Salatiga,
Indonesia
- Suprihadi Suprihadi Satya Wacana Christian University, Salatiga, Indonesia (*) Corresponding Author
Abstract
This study examines public sentiment toward Indonesia’s new capital city, Ibu Kota Nusantara (IKN), across three major social media platforms: X, TikTok, and Instagram. The research aims to identify how public perceptions differ across platforms and to understand their implications for policy communication. A total of approximately 6,000 user comments collected up to March 2025 were processed through standard text-mining procedures, including cleaning, tokenization, stop-word removal, and stemming. The text data were converted into numerical features using the Term Frequency–Inverse Document Frequency (TF-IDF) technique and classified using a linear Support Vector Machine (SVM) model. Model evaluation with a 20% hold-out test set yielded an accuracy of 90.23% and a macro F1-score of 0.8905. The analysis shows that overall sentiment toward IKN is predominantly positive, with Instagram and TikTok generating more supportive narratives, while X displays a higher concentration of critical or negative comments. These findings highlight significant platform-specific differences that can inform more effective public communication strategies regarding the IKN project.
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References
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