Analisis Sentimen Masyarakat Indonesia terhadap Pemindahan Ibu Kota Negara Indonesia pada Twitter
The relocation state capital of Indonesia raises various responses, especially from the Indonesian people. The discussion related to these issues is very interesting to study, how are the positive and negative sentiments of the Indonesian towards the government's decision. This study aims to a...
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| Format: | Article |
| Language: | Indonesian |
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Program Studi Sistem Informasi, Universitas Islam Negeri Raden Fatah Palembang
2022-06-01
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| Series: | Jurnal Sistem Informasi |
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| Online Access: | https://jurnal.radenfatah.ac.id/index.php/jusifo/article/view/12116 |
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| author | Sri Lestari Mupaat Mupaat Adhitia Erfina |
| author_facet | Sri Lestari Mupaat Mupaat Adhitia Erfina |
| author_sort | Sri Lestari |
| collection | DOAJ |
| description | The relocation state capital of Indonesia raises various responses, especially from the Indonesian people. The discussion related to these issues is very interesting to study, how are the positive and negative sentiments of the Indonesian towards the government's decision. This study aims to analyze the sentiments of the Indonesian people regarding the relocation state capital of Indonesia, including the chosen name of Nusantara on Twitter. In this study, a comparison of 3 algorithms is used, namely the Support Vector Machine (SVM), Naïve Bayes, and K-Nearest Neighbor (KNN) algorithms. From this study, the results obtained are 1,141 positive comments, while negative sentiments are 591 comments. This shows that the Indonesian people have a positive opinion towards the new capital city of Indonesia. In the classification and model testing phase, 10-fold cross validation is used. From these tests, the SVM algorithm obtained an accuracy value of 85.71%, the Naïve Bayes algorithm obtained an accuracy value of 76.70%, the KNN algorithm obtained an accuracy value of 52.74%. This study shows that the SVM algorithm can work better than the Naïve Bayes algorithm and KNN. The accuracy value for the KNN algorithm obtains a low value, this is because the KNN algorithm is sensitive to features that are less relevant. |
| format | Article |
| id | doaj-art-a0a33a14470d4082b5ee61a569dbe21a |
| institution | Matheson Library |
| issn | 2460-092X 2623-1662 |
| language | Indonesian |
| publishDate | 2022-06-01 |
| publisher | Program Studi Sistem Informasi, Universitas Islam Negeri Raden Fatah Palembang |
| record_format | Article |
| series | Jurnal Sistem Informasi |
| spelling | doaj-art-a0a33a14470d4082b5ee61a569dbe21a2025-06-27T02:47:02ZindProgram Studi Sistem Informasi, Universitas Islam Negeri Raden Fatah PalembangJurnal Sistem Informasi2460-092X2623-16622022-06-0181132210.19109/jusifo.v8i1.121169823Analisis Sentimen Masyarakat Indonesia terhadap Pemindahan Ibu Kota Negara Indonesia pada TwitterSri Lestari0Mupaat Mupaat1Adhitia Erfina2Universitas Nusa PutraUniversitas Nusa PutraUniversitas Nusa PutraThe relocation state capital of Indonesia raises various responses, especially from the Indonesian people. The discussion related to these issues is very interesting to study, how are the positive and negative sentiments of the Indonesian towards the government's decision. This study aims to analyze the sentiments of the Indonesian people regarding the relocation state capital of Indonesia, including the chosen name of Nusantara on Twitter. In this study, a comparison of 3 algorithms is used, namely the Support Vector Machine (SVM), Naïve Bayes, and K-Nearest Neighbor (KNN) algorithms. From this study, the results obtained are 1,141 positive comments, while negative sentiments are 591 comments. This shows that the Indonesian people have a positive opinion towards the new capital city of Indonesia. In the classification and model testing phase, 10-fold cross validation is used. From these tests, the SVM algorithm obtained an accuracy value of 85.71%, the Naïve Bayes algorithm obtained an accuracy value of 76.70%, the KNN algorithm obtained an accuracy value of 52.74%. This study shows that the SVM algorithm can work better than the Naïve Bayes algorithm and KNN. The accuracy value for the KNN algorithm obtains a low value, this is because the KNN algorithm is sensitive to features that are less relevant.https://jurnal.radenfatah.ac.id/index.php/jusifo/article/view/12116iknsentiment analysistwitter |
| spellingShingle | Sri Lestari Mupaat Mupaat Adhitia Erfina Analisis Sentimen Masyarakat Indonesia terhadap Pemindahan Ibu Kota Negara Indonesia pada Twitter Jurnal Sistem Informasi ikn sentiment analysis |
| title | Analisis Sentimen Masyarakat Indonesia terhadap Pemindahan Ibu Kota Negara Indonesia pada Twitter |
| title_full | Analisis Sentimen Masyarakat Indonesia terhadap Pemindahan Ibu Kota Negara Indonesia pada Twitter |
| title_fullStr | Analisis Sentimen Masyarakat Indonesia terhadap Pemindahan Ibu Kota Negara Indonesia pada Twitter |
| title_full_unstemmed | Analisis Sentimen Masyarakat Indonesia terhadap Pemindahan Ibu Kota Negara Indonesia pada Twitter |
| title_short | Analisis Sentimen Masyarakat Indonesia terhadap Pemindahan Ibu Kota Negara Indonesia pada Twitter |
| title_sort | analisis sentimen masyarakat indonesia terhadap pemindahan ibu kota negara indonesia pada twitter |
| topic | ikn sentiment analysis |
| url | https://jurnal.radenfatah.ac.id/index.php/jusifo/article/view/12116 |
| work_keys_str_mv | AT srilestari analisissentimenmasyarakatindonesiaterhadappemindahanibukotanegaraindonesiapadatwitter AT mupaatmupaat analisissentimenmasyarakatindonesiaterhadappemindahanibukotanegaraindonesiapadatwitter AT adhitiaerfina analisissentimenmasyarakatindonesiaterhadappemindahanibukotanegaraindonesiapadatwitter |