Analisis Sentimen Pada ChatGPT Menggunakan Algoritma Long Short Term Memory (LSTM)
Keywords:
Sentimen Analisis, Analisis ChatGPT, Metode LSTMAbstract
Penelitian ini fokus pada analisis sentimen menggunakan ChatGPT dengan memanfaatkan metode LSTM dan memanfaatkan dataset dari Kaggle. Tujuan utama dari penelitian ini adalah untuk meningkatkan kinerja analisis sentimen teks dengan mengadopsi model LSTM yang lebih canggih dibandingkan dengan model berbasis aturan yang umumnya digunakan. Metode LSTM dipilih sebagai pendekatan untuk menganalisis sentimen pada dataset teks yang telah diolah dan diberi label sentimen. Tahapan penelitian dimulai dengan proses pengumpulan dan persiapan data, diikuti dengan pembuatan model rule-based. Selanjutnya, dilakukan pemrosesan dan pre-training metode LSTM, featurization, training metode LSTM, evaluasi model, dan analisis hasil. Pada tahap evaluasi, kinerja Metode LSTM akan dinilai menggunakan metrik evaluasi seperti akurasi, presisi, recall, dan F1-score. Hasil evaluasi akan dibandingkan dengan model rule-based yang telah dibuat sebelumnya. Harapannya, hasil dari penelitian ini dapat memberikan wawasan baru terkait penggunaan Metode LSTM dalam analisis sentimen teks, sekaligus meningkatkan kinerja sentimen analisis secara keseluruhan.
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