Analisis Sentimen Masyarakat Terhadap Kebijakan Ekspor Pasir Laut Berdasarkan Ulasan Twitter Menggunakan Algoritma Naive Bayes dan Support Vector Machine
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Zarqani Zarqani
*
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru,
Indonesia
- M Afdal Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia
- Rice Novita Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia
- Megawati Megawati Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, Indonesia (*) Corresponding Author
Abstract
The export of sea sand has been banned since 2003 through a Decree of the Minister of Industry and Trade. However, on May 15, 2023, President Joko Widodo once again allowed the export of sea sand through Government Regulation No. 26 of 2023. This policy sparked controversy and went viral on social media, including on Twitter. This study aims to analyze public sentiment toward the policy based on reviews on Twitter using the Naïve Bayes and Support Vector Machine (SVM) algorithms. Data was collected through crawling techniques, then processed using text preprocessing methods, word weighting using TF-IDF, and random oversampling to balance the data. The data was then categorized into four thematic variables—economy, environment, social, and geological policy—to examine a more focused distribution of sentiment. Analysis of 2,765 data points revealed that the majority of sentiment was negative (55%), indicating public opposition to the sea sand export policy, followed by neutral sentiment (30%) and positive sentiment (15%). Performance evaluation shows that SVM excels in the Economy category with nearly 95% accuracy, while in other categories the difference with Naïve Bayes is relatively small. This study is expected to provide insights into the Indonesian public's perception of the sea sand export policy and its implications across various sectors.
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Copyright (c) 2025 Zarqani Zarqani, M Afdal, Rice Novita, Megawati Megawati
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