Klasifikasi Multi-Class Pada Kondisi Kesehatan Mental Berbasis Data Media Sosial Menggunakan Model BERT
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Abstract
Kesehatan mental merupakan kondisi kesejahteraan psikologis yang memungkinkan individu mengelola stres, bekerja secara produktif, dan berinteraksi secara sosial. Peningkatan penggunaan media sosial menghasilkan data teks yang dapat merepresentasikan kondisi emosional dan psikologis pengguna. Berbagai penelitian telah mengembangkan klasifikasi kondisi kesehatan mental berbasis data media sosial menggunakan pendekatan machine learning dan deep learning. Namun, sebagian besar penelitian masih berfokus pada klasifikasi biner atau deteksi satu kondisi mental tertentu, sedangkan pendekatan multi-class untuk membedakan beberapa kondisi kesehatan mental secara bersamaan masih terbatas. Selain itu, kemiripan pola linguistik antar kondisi mental serta penggunaan bahasa informal pada media sosial menjadi tantangan dalam meningkatkan performa klasifikasi teks tidak terstruktur. Oleh karena itu, penelitian ini mengusulkan model Bidirectional Encoder Representations from Transformers (BERT) untuk mengklasifikasikan kondisi kesehatan mental berbasis data media sosial. Model BERT dipilih karena mampu memahami konteks bahasa secara bidirectional melalui mekanisme self-attention sehingga lebih efektif menangkap representasi semantik dibandingkan metode konvensional. Dataset yang digunakan adalah Reddit Mental Health dengan lima kategori, yaitu Stress, Depression, Bipolar Disorder, Personality Disorder, dan Anxiety. Tahapan penelitian meliputi preprocessing teks, tokenisasi menggunakan BERT tokenizer, pembagian data secara stratified, penanganan imbalanced data menggunakan class weighting dan focal loss, serta fine-tuning model. Hasil eksperimen pada 5.957 data menunjukkan bahwa konfigurasi hyperparameter terbaik memperoleh accuracy sebesar 80%, dengan rata-rata precision, recall, dan F1-score masing-masing sebesar 80%. Kategori Stress memperoleh F1-score tertinggi sebesar 87%, sedangkan kategori Depression sebesar 73%. Hasil penelitian menunjukkan bahwa model BERT efektif dalam memahami pola linguistik dan konteks emosional pada data media sosial tidak terstruktur.
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