LUSIANA , FERISCA N (2025) ANALISIS KINERJA AUGMENTASI TEKS BACK TRANSLATION DAN SYNONYM REPLACEMENT DALAM KLASIFIKASI STATUS KESEHATAN MENTAL MENGGUNAKAN DISTILLED-BERT (DISTILBERT). FAKULTAS MATEMATIKA ILMU PENGETAHUAN ALAM, UNIVERSITAS LAMPUNG.
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Abstrak (Berisi Bastraknya saja, Judul dan Nama Tidak Boleh di Masukan)
Mental health is an important aspect that supports the overall quality of life of individuals. In today’s digital age, social media has become a space for people to express their psychological conditions. This phenomenon opens up opportunities to utilize text data as a source of information in the process of identifying mental health disorders. This study aims to analyze the performance of two text-based data augmentation techniques, namely back translation and synonym replacement, in improving the performance of mental health status classification using the DistilBERT model. The study was conducted on English-language text data labeled according to the type of mental disorder. The synonym replacement and back translation augmentation techniques were applied to balance the data distribution in the minority class. The dataset was divided into 80% training data and 20% test data, with 20% of the training data used as validation data. The classification process was performed using a fine-tuned DistilBERT model. The results showed that the DistilBERT model with synonym replacement augmentation achieved the highest accuracy, namely 87%, while back translation achieved an accuracy of 86%. This indicates that the synonym replacement augmentation technique is more effective in increasing data variation and classification model performance on the dataset used in this study. Keywords: Mental Health, Text Augmentation, Text Classification, DistilBERT.
| Jenis Karya Akhir: | Skripsi |
|---|---|
| Subyek: | 500 ilmu pengetahuan alam dan matematika 500 ilmu pengetahuan alam dan matematika > 510 Matematika |
| Program Studi: | FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM (FMIPA) > Prodi S1 Matematika |
| Pengguna Deposit: | 2506877206 Digilib |
| Date Deposited: | 21 Jun 2025 09:02 |
| Terakhir diubah: | 21 Jun 2025 09:02 |
| URI: | http://digilib.unila.ac.id/id/eprint/89318 |
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