Emotion Classification in Sundanese Text Using LSTM and BERT Models

Mahazzam Afrad ; Fauzi Irfan Syaputra ; Gilang Fibarkah ; Tectonia Nurul Silvani
Proceeding of the International Conference on Elec... 📅 2025 Vol 1, No 1 🔗 DOI: 10.62951/iceei.v1i1.36
Abstract
The Sundanese language, once spoken by 48 million individuals, has experienced a significant decline in speakers, losing 2 million in the past decade. This decline is attributed to weakened intergenerational transmission and the dominance of more widely used languages. The challenges in developing Natural Language Processing (NLP) tools for Sundanese stem from the lack of annotated corpora, trained language models, and adequate processing tools, complicating efforts to preserve and enhance the language's usability. This research aims to address these challenges by implementing emotion classification in Sundanese text using Long Short-Term Memory (LSTM) and Bidirectional Encoder Representations from Transformers (BERT) models. The study utilizes a dataset of annotated Sundanese tweets, applying preprocessing techniques such as cleansing, stopword removal, stemming, and tokenization to prepare the data for analysis. The results indicate that the BERT model significantly outperforms the LSTM model, achieving an accuracy of approximately 80% compared to LSTM's 70%. These findings highlight the potential of advanced NLP techniques in enhancing the understanding of emotional nuances in Sundanese communication and contribute to the revitalization of the language in the digital age.
Keywords
BERT; Emotion Classification; LTSM; Sundanese Language
How to Cite

Mahazzam Afrad, et al. (2025). Emotion Classification in Sundanese Text Using LSTM and BERT Models. Proceeding of the International Conference on Electrical Engineering and Informatics, 1(1). https://doi.org/10.62951/iceei.v1i1.36

Mahazzam Afrad; Fauzi Irfan Syaputra; Gilang Fibarkah; Tectonia Nurul Silvani, "Emotion Classification in Sundanese Text Using LSTM and BERT Models," Proceeding of the International Conference on Electrical Engineering and Informatics, vol. 1, no. 1, 2025.

Mahazzam Afrad; Fauzi Irfan Syaputra; Gilang Fibarkah; Tectonia Nurul Silvani. "Emotion Classification in Sundanese Text Using LSTM and BERT Models." Proceeding of the International Conference on Electrical Engineering and Informatics, vol. 1, no. 1, 2025.

Mahazzam Afrad; Fauzi Irfan Syaputra; Gilang Fibarkah; Tectonia Nurul Silvani. "Emotion Classification in Sundanese Text Using LSTM and BERT Models." Proceeding of the International Conference on Electrical Engineering and Informatics 1, no. 1 (2025).

Mahazzam Afrad, et al. (2025) 'Emotion Classification in Sundanese Text Using LSTM and BERT Models', Proceeding of the International Conference on Electrical Engineering and Informatics, 1(1). doi: 10.62951/iceei.v1i1.36.

Mahazzam Afrad; Fauzi Irfan Syaputra; Gilang Fibarkah; Tectonia Nurul Silvani. Emotion Classification in Sundanese Text Using LSTM and BERT Models. Proceeding of the International Conference on Electrical Engineering and Informatics. 2025;1(1).

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