Ferdiansyah, Sagama (2025) Analisis Sentimen Masyarakat Terkait Pembaruan Sistem Pelatihan Prakerja Tahun 2024 Pada Media Sosial Instagram Dengan Menggunakan Metode SVM. S1 Sistem Informasi thesis, STMIK WIDYA CIPTA DHARMA.
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Abstract
Ferdiansyah Ijian Sagama, 2024, Analisis Sentimen Masyarakat Terkait Pembaruan Sistem Pelatihan Prakerja Tahun 2024 Pada Media Sosial Instagram Menggunakan Metode SVM di DPD Parati Golkar. Skripsi jurusan Sistem Informasi, Sekolah Tinggi Manajemen Informatika dan Komputer Widya Cipta Dharma, Pembimbing Utama Dr. Heny Pratiwi, S.Kom., M. Pd., M. TI, Pembimbing Pendamping Kusno Harianto, S. Kom., M. Kom. Kata kunci: Analisis Sentimen, Politik, Media Sosial, Instagram, Support Vector Machine (SVM). Penelitian ini bertujuan untuk menganalisis sentimen masyarakat terkait pembaruan sistem pelatihan prakerja tahun 2024 pada media sosial instagram menggunakan metode SVM. Media sosial, khususnya Instagram, menjadi platform penting untuk mengamati reaksi masyarakat terhadap berbagai isu, termasuk politik. Dalam penelitian ini, data komentar Instagram dikumpulkan dan dianalisis untuk mengidentifikasi sentimen positif, negatif, dan netral. Proses analisis meliputi Pengumpulan Data, Pre-Processing, Pelabelan, Pembobotan TF-IDF, Pemodelan Dengan Support Vector Machine (SVM), Confusion Matrix dan Visualisasi. Hasil penelitian, yang dilakukan pada media sosial menunjukkan bahwa metode SVM mampu mengklasifikasikan sentimen dengan tingkat akurasi sebesar 86%, presisi sebesar 86%, dan recall sebesar 85%. Penelitian ini diharapkan dapat memberikan kontribusi dalam pengembangan metode analisis sentimen yang lebih canggih dan efektif serta menjadi landasan bagi penelitian lebih lanjut dalam memahami dinamika opini publik dalam konteks politik modern yang semakin kompleks. ============================================================ Ferdiansyah Ijian Sagama, 2024, Analysis of Public Sentiment Regarding Updates to the 2024 Pre-Employment Training System on Instagram Social Media Using the SVM Method at DPD Parati Golkar. Thesis majoring in Information Systems, Widya Cipta Dharma College of Information and Computer Management, Main Supervisor Dr. Heny Pratiwi, S. Kom., M.Pd., M. TI, Co-Advisor Kusno Harianto, S. Kom., M. Kom. Keywords: Sentiment Analysis, Politics, Social Media, Instagram, Support Vector Machine (SVM). This research aims to analyze public sentiment regarding the 2024 pre-employment training system update on Instagram social media using the SVM method. Social media, especially Instagram, has become an important platform for monitoring people's reactions to various issues, including politics. In this research, Instagram comment data was collected and analyzed to identify positive, negative and neutral sentiments. The analysis process includes Data Collection, Pre-Processing, Labeling, TF-IDF Weighting, Modeling with Support Vector Machine (SVM), Confusion Matrix and Visualization. The results of research conducted at the social media showed that the SVM method was able to classify sentiment with an accuracy rate of 86%, precision of 85%, and recall of 85%. It is hoped that this research can contribute to the development of more sophisticated and effective sentiment analysis methods and become a basis for deeper research into understanding the dynamics of public opinion in the increasingly complex context of modern politics.
| Item Type: | Thesis (S1 Sistem Informasi) |
|---|---|
| Additional Information: | Dr. Heny Pratiwi, S. Kom., M. Pd., M. TI Kusno Harianto, S. Kom., M. Kom |
| Uncontrolled Keywords: | Analisis Sentimen, Politik, Media Sosial, Instagram, Support Vector Machine (SVM), Sentiment Analysis, Politics, Social Media, Instagram, Support Vector Machine (SVM). |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Sistem Informasi |
| Depositing User: | Ferdiansya ijian Sagama |
| Date Deposited: | 14 Feb 2025 00:38 |
| Last Modified: | 14 Feb 2025 00:38 |
| URI: | http://repository.wicida.ac.id/id/eprint/6120 |
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