PERBANDINGAN NLP DAN SVM DALAM ANALISIS SENTIMEN KOMENTAR INSTAGRAM TERKAIT STIGMA MASYARAKAT TERHADAP BANJIR SUMATERA 2025
DOI:
https://doi.org/10.54314/jssr.v9i2.6176Keywords:
Sentiment Analysis, Natural Language Processing, IndoBERTAbstract
This study aims to analyze public sentiment regarding the 2025 Sumatra flood based on Instagram comments using a Natural Language Processing (NLP) approach. The methods applied include IndoBERT and Support Vector Machine (SVM) with TF-IDF features. A total of 711 comments were collected through a crawling process and processed using preprocessing techniques. The results show that negative sentiment dominates at 44.7%, followed by positive (30.4%) and neutral (24.9%) sentiments. Model evaluation indicates that IndoBERT outperforms SVM with an accuracy of 74.8% compared to 66.4%. WordCloud visualization reveals dominant terms such as flood, government, forest, and palm oil, reflecting public concerns about environmental issues and government policies.
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Copyright (c) 2026 Muhammad Akbar Firdaus, Maisya Fitri Anugrah, Sri Hidayati, Dedy Rahman Harahap, Rendy Rabensi Sembiring, Muhammad Syahputra Novelan
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