Avista, Adelia Ayu (2025) Analisis Sentimen Pada Pengguna Twitter Terhadap Hasil Pengumuman Pasca Pilpres 2024 Menggunakan Metode Naive Bayes Classifier. Undergraduate thesis, Politeknik Negeri Jember.
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Abstract
This study aims to analyze public sentiment regarding the announcement results following the 2024 Presidential Election using the Naïve Bayes Classifier method. Data was collected through a crawling process using the Tweet Harvest tool, followed by preprocessing steps such as cleansing, case folding, filtering, normalization, stopword removal, stemming, and tokenizing. A total of 1,115 data points were obtained, consisting of 589 positive and 526 negative sentiments. The classification process was carried out using the Naïve Bayes method and evaluated with a confusion matrix to calculate accuracy. The model achieved an accuracy of 81%, precision of 81%, recall of 80%, and F1-score of 81%. The results indicate that this method is capable of classifying tweets with a satisfactory level of accuracy, thereby providing an overall picture of public opinion on the results of the 2024 presidential election. This study also highlights the significant potential of sentiment analysis as a tool to understand public perception of emerging political issues. Keywords: Sentiment Analysis, Twitter, 2024 Presidential Election, Naïve Bayes Classifier.
| Item Type: | Thesis (Undergraduate) | ||||||
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| Uncontrolled Keywords: | Analisis Sentimen, Twitter, Pilpres 2024, Naïve Bayes Classifier | ||||||
| Subjects: | 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 459 - Ilmu Komputer 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 461 - Sistem Informasi 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 463 - Teknik Perangkat Lunak |
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| Divisions: | Jurusan Teknologi Informasi > Prodi D4 Teknik Informatika > PKL | ||||||
| Depositing User: | Adelia Ayu Avista | ||||||
| Date Deposited: | 12 Jun 2025 08:08 | ||||||
| Last Modified: | 12 Jun 2025 08:09 | ||||||
| URI: | https://sipora.polije.ac.id/id/eprint/41775 |
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