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All Journal Indonesian Journal on Computing (Indo-JC)
Shaufiah
Telkom University
Computer Science & IT Control & Systems Engineering Education Engineering

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Visualizing Functional Emotions: Mapping Counseling Responses from Text to Virtual Facial Expressions Rifki Padilah; Rifki Wijaya; Shaufiah
Indonesian Journal on Computing (Indo-JC) Vol. 10 No. 1 (2025): August, 2025
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/indojc.v10i1.9707

Abstract

This research develops an innovative virtual counseling system by integrating text-based emotion classification with visual representation to address the problem of early marriage in Lombok. The system leverages the sophisticated IndoRoBERTa model to accurately classify conselor responses into five functional emotion categories relevant to the counseling context: Enthusiasm, Gentleness, Analytical, Inspirational, and Cautionary. The limitations of conventional counseling services in rural areas serve as the primary justification for developing this responsive and accessible technological solution. Evaluation results demonstrate that the IndoRoBERTa model achieves a highly competitive accuracy rate of 89% after being trained on an expanded dataset, an achievement that significantly surpasses previous architectures. In conclusion, this IndoRoBERTa-based system is not only technically viable but also effective as a tool for providing initial empathetic support. Its capability to translate textual emotions into non-verbal visual cues makes it a promising technological solution to bridge the gap in current counseling services.
Emotion Recognition from Text and Gesture Generation for an Early Marriage Counseling Chatbot in Lombok Using BERT Adam Zahran Ramadhdan; Rifki Wijaya; Shaufiah
Indonesian Journal on Computing (Indo-JC) Vol. 10 No. 1 (2025): August, 2025
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/indojc.v10i1.9710

Abstract

Early marriage remains a pressing issue among adolescents in Lombok, Indonesia, influenced by cultural norms, educational barriers, and economic challenges. This study develops an emotion classification and reason identification framework for a virtual counseling chatbot to support prevention efforts. Five functional emotion categories ‘Enthusiastic’, ‘Gentle’, ‘Analytical’, ‘Inspirational’, and ‘Cautionary’ were defined to capture counseling tones. The system leverages IndoBERT with a two-phase fine-tuning strategy. Phase 1 used a balanced dataset of 2,000 samples and achieved a macro F1-score of 0.95, while Phase 2 refined the model using 10,000 imbalanced pseudo-labeled samples, yielding a macro F1-score of 0.88 and improved sensitivity to minority classes. In addition, a semantic similarity-based reason identification module was implemented to classify user inputs into Education, Economy, Religion, or Culture categories, enhancing context awareness beyond simple keyword matching. Performance evaluation employed accuracy, precision, recall, and F1-score, supported by confusion matrices and training plots for generalization analysis. A descriptive emotion-to-gesture mapping was also designed to link each emotion category with static body pose visualizations, providing a conceptual basis for future multimodal applications.
Co-Authors Adam Zahran Ramadhdan Rifki Padilah Rifki Wijaya