FAHRANI, FADMI (2025) SENTIMENT ANALYSIS OF X USERS ON THE PALESTINE-ISRAEL CONFLICT USING THE SUPPORT VECTOR MACHINE METHOD. Tugas Akhir thesis, Informatics.
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Abstract
The ongoing conflict between Palestine and Israel, particularly in the city of Rafah in the Gaza Strip, has sparked widespread reactions from the global community, including Indonesian social media users. This study aims to analyze public sentiment on the topic “Eyes on Rafah” using a machine learning approach. The dataset consists of 403 Indonesian-language tweets that reflect public opinion in Indonesia regarding the humanitarian crisis. The methodology applies the Support Vector Machine (SVM) algorithm with Term Frequency-Inverse Document Frequency (TF-IDF) weighting and is optimized using the Synthetic Minority Oversampling Technique (SMOTE) to address data imbalance. This combination is hypothesized to produce an accurate and balanced classification model for identifying both positive and negative sentiments. The study also investigates the impact of varying training and testing data ratios to determine the optimal model performance configuration. Keywords: Sentiment Analysis, Rafah, Support Vector Machine, SMOTE, TF-IDF
| Item Type: | Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Fakultas Sains Dan Teknologi > S1 Informatika |
| Depositing User: | Kaprodi S1 Informatika UTY |
| Date Deposited: | 17 Jul 2025 01:27 |
| Last Modified: | 17 Jul 2025 01:27 |
| URI: | http://eprints.uty.ac.id/id/eprint/18188 |
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