Nusantara capital city sentiment analysis using support vector machine and logistic regression

The decision to move position the capital city of Indonesia to East Kalimantan has drawn people’s opinions, both pro and con, among the public, especially ahead of the presidential and vice-presidential elections. Discussions relevant to the relocation and construction of the capital city are increasingly crowded on social media, especially Twitter or X. This research aims to determine public sentiment regarding the development of the national capital to help the government and policymakers improve communication strategies, evaluate existing policies, and make more informed decisions based on public feedback. Public sentiment related to developing the Capital city of the Nusantara, including the presidential palace, toll road, and government offices, is analyzed. Support vector machine (SVM) and logistic regression (LR) algorithms are utilized for the sentiment classification. The results reveal that the SVM performs better in classifying sentiments in X data relevant to developing the Capital city of Nusantara, achieving an average accuracy of 91.97%.

Authors

Publication Details

Journal
Indonesian Journal of Electrical Engineering and Computer Science
Published
2025-05-07
DOI
https://doi.org/10.11591/ijeecs.v38.i3.pp1708-1721
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Nusantara capital city sentiment analysis using support vector machine and logistic regression

Raymond Sunardi Oetama, Valencia Eurelia Angelie Tania
Indonesian Journal of Electrical Engineering and Computer Science
Data Mining and Machine Learning Applications
article

Nusantara capital city sentiment analysis using support vector machine and logistic regression

Raymond Sunardi Oetama, Valencia Eurelia Angelie Tania
article en

Abstract

The decision to move position the capital city of Indonesia to East Kalimantan has drawn people’s opinions, both pro and con, among the public, especially ahead of the presidential and vice-presidential elections. Discussions relevant to the relocation and construction of the capital city are increasingly crowded on social media, especially Twitter or X. This research aims to determine public sentiment regarding the development of the national capital to help the government and policymakers improve communication strategies, evaluate existing policies, and make more informed decisions based on public feedback. Public sentiment related to developing the Capital city of the Nusantara, including the presidential palace, toll road, and government offices, is analyzed. Support vector machine (SVM) and logistic regression (LR) algorithms are utilized for the sentiment classification. The results reveal that the SVM performs better in classifying sentiments in X data relevant to developing the Capital city of Nusantara, achieving an average accuracy of 91.97%.

Indonesian Journal of Electrical Engineering and Computer ScienceVol. 38(3)
Openalex Percentile: Top 87%
Data Mining and Machine Learning Applications
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