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Emotion Classification in Indonesian Text Using IndoBERT

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This analysis demonstrates emotion detection in tweets, suggesting crucial implications for mental health.

The IndoBERT model successfully classifies emotions in Indonesian text, aiding mental health detection.
Using a dataset of 5079 tweets, the model achieved optimal results with an 80:10:10 data split.
The research involved variations in training parameters including learning rate and batch size for better accuracy.
Findings highlight the potential for early emotion detection in text, which is vital for mental health interventions.

Rizky et al. (2025) studied this question.

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