ANALISIS SENTIMEN DALAM APLIKASI X TERHADAP PENGUNGSI ROHINGYA DENGAN LSTM - Pratama, Andri; Rosyda, Miftahurrahma (SKANIKA: Sistem Komputer dan Teknik Informatika, 2025)
Rohingya refugees in Indonesia face discrimination and hate speech due to disinformation in Indonesian society The polemic over the influx of Rohingya refugees to Indonesia has created a variety of responses among the public. Understanding the perspectives and reactions of the Indonesian public regarding this issue is crucial, especially in analyzing the growing sentiment. This research was conducted to evaluate the views and sentiments of Indonesians towards the Rohingya through X social media platforms. Data was collected through web scraping using twikit during December 2023, resulting in 17,613 tweets. Labeling was done using the trained IndoBERTweet model with the IndoNLU smsa_doc-sentiment-prosa dataset. The Long Short-Term Memory (LSTM) model is applied with two class balancing methods, Random Oversampling and SMOTE. The results show that with Random Oversampling, the model achieves precision 0.9139, recall 0.9632, F1 score 0.9379, and accuracy 0.9069. Meanwhile, the use of SMOTE resulted in precision 0.9092, recall 0.9445, F1 score 0.9265, and accuracy 0.8906.