Mengungkap Opini Publik: Pendekatan BERT-based-caused untuk Analisis Sentimen pada Komentar Film
Abstract
BERT (Bidirectional Encoder Representations from Transformers) adalah model bahasa yang revolusioner dalam pemrosesan bahasa alami, mengandalkan encoder untuk menghasilkan representasi kontekstual dari teks input. Melalui pendekatan tokenisasi, embedding, dan attention mechanisms pada setiap layer transformer, BERT memungkinkan pemahaman hubungan antar kata secara mendalam dan bidireksional. Keunikan BERT terletak pada kemampuannya untuk memproses konteks dari kedua arah, menciptakan representasi vektor yang kaya makna. Model ini telah menjadi pionir dalam transfer learning di NLP, memungkinkan pemanfaatan representasi umum pada tugas-tugas khusus setelah proses pelatihan. Dengan demikian, BERT mengubah paradigma pemrosesan bahasa alami, membuka pintu untuk aplikasi yang lebih canggih seperti klasifikasi teks, analisis sentimen, dan pemahaman bahasa yang lebih kontekstual.
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