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Nurirwan Saputra, Nurirwan
Universitas PGRI Yogyakarta
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Journal : Jurnal ULTIMATICS

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Multiclass Emotion Detection on YouTube Comments Using IndoBERT: A Web-Based Incremental Learning System with Multiple Data Split Evaluation Naufal; Saputra, Nurirwan
ULTIMATICS Vol 17 No 2 (2025): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v17i2.4558

Abstract

YouTube comments contain rich emotional expressions, but their large volume makes manual analysis inefficient. This study proposes a multiclass emotion classification approach for Indonesian YouTube comments using the IndoBERT model integrated with a database-driven incremental learning system. Comment data were collected through the YouTube Data API and labeled into six emotion categories: anger, sadness, happiness, fear, surprise, and neutral. Text preprocessing included lowercasing, text cleaning, and normalization of informal Indonesian words. The model was fine-tuned using three training–testing split scenarios (60:40, 70:30, and 80:20). The results show that the 80:20 split achieved the highest accuracy of 68%, influenced by an imbalanced class distribution with underrepresented minority classes. In addition, the system supports continuous data storage and incremental retraining, allowing the model to learn from new data without retraining from scratch. This adaptive mechanism makes the proposed system suitable for long-term emotion analysis on YouTube comments.
Co-Authors Adhistya Erna Permanasari Ahmad Riyadi Ahmad Riyadi Anwar Fauzi, Muhammad Afif Ari Kusuma Wardana Arip Febrianto Darwanto Darwanto Guritno, Muhammad Wahyu Suryo Hanif, Khairunnaufal Karandi Nurbagja Muhammad Muhajir, Muhammad Mustain, Riefyal Arshyza Naufal Pandri Ferdias Pandri Ferdias, Pandri Rianto Riefyal Arshyza Mustain Setia Wardani Syah, Firdiyan Teguh Bharata Adji Tentua, Meilani Nonsi Tentua, Meilany Nonsi Turiyan Turiyan