Analisis Sentimen Pada Media Sosial X Terhadap Dampak Perpindahan Ibu Kota Negara Ke IKN Nusantara Disektor Pendidikan Dan Kebudayaan Dengan Metode Support Vector Machine (SVM)

Sholihin, Faisal Oktabrian (2025) Analisis Sentimen Pada Media Sosial X Terhadap Dampak Perpindahan Ibu Kota Negara Ke IKN Nusantara Disektor Pendidikan Dan Kebudayaan Dengan Metode Support Vector Machine (SVM). Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

The relocation of the National Capital (IKN) is a strategic policy that impacts various sectors, including education and culture. Social media platform X serves as a medium for the public to express their opinions regarding this policy. This study aims to analyze public sentiment toward the relocation of IKN in the education and cultural sectors using the Support Vector Machine (SVM) method. The dataset consists of 1,380 data points, divided into training and testing data with an optimal ratio of 90% to 10%, resulting in an accuracy of 83%. The findings indicate that public opinions can be categorized into positive, negative, and neutral sentiments, with a tendency for uncertainty in assessing the impact of IKN relocation. The model's accuracy depends on the quality of the dataset and data partitioning, highlighting the significant influence of data processing precision on sentiment analysis performance.

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