Analisis Sentimen Review Hotel Menggunakan Metode Deep Learning BERT

Authors

  • Vidya Chandradev Universitas Udayana
  • I Made Agus Dwi Suarjaya Universitas Udayana
  • I Putu Agung Bayupati Universitas Udayana

DOI:

https://doi.org/10.24002/jbi.v14i02.7244

Keywords:

sentiment analysis, SmallBERT, deep learning, natural language processing, fine-tuning

Abstract

Pandemi COVID-19 telah menyebabkan penurunan kunjungan pariwisata dan okupansi hotel. Penting bagi pengusaha hotel untuk memantau gaya hidup pengunjung guna menjaga kelangsungan bisnis. Salah satu cara untuk melakukannya adalah dengan memahami sentimen pengunjung hotel melalui analisis review agar mendapatkan pemahaman yang lebih baik dalam pengambilan keputusan terkait layanan dan aspek bisnis di sektor perhotelan. Penelitian ini menerapkan model deep learning natural language processing BERT untuk menganalisis sentimen positif dan negatif dari review pengunjung hotel di Indonesia. Model BERT yang digunakan telah menjalani proses pretrained dan diterapkan metode fine-tuning untuk menghasilkan analisis sentimen yang akurat. Hasil evaluasi menunjukkan bahwa model fine-tuning SmallBERT yang dilatih menggunakan dataset 515k review hotel selama 5 epoch memberikan performa yang baik. Model SmallBERT mencapai akurasi sebesar 91,40%, presisi 90,51%, recall 90,51%, dan skor f1 90,51% saat dievaluasi dengan dataset yang diberi label secara manual. Visualisasi hasil perbandingan sentimen yang didominasi oleh sentimen positif, dilakukan menggunakan Tableau

Author Biographies

Vidya Chandradev, Universitas Udayana

Vidya Chandradev is a student in the Information Technology program at Udayana University, where she enrolled in 2019 and is expected to complete her undergraduate studies in 2023. Her initial focus of interest was in Data and Information Management, but due to curriculum changes in the Information Technology program, she switched her field of interest to Data Science. Her research paper focuses on the use of Deep Learning, specifically SmallBERT, for sentiment analysis.

I Made Agus Dwi Suarjaya, Universitas Udayana

Dr.Eng. I Made Agus Dwi Suarjaya, S.T., M.Eng. is an Assistant Lecturer in the Information Technology program. He holds the rank of IIIb/Penata Muda Tk I. He earned his Bachelor's degree in Engineering from Udayana University in 2007, followed by a Master's degree from Gadjah Mada University in 2009, and a Doctorate from Kanazawa University in 2017. His research during his undergraduate studies covered the fields of Software Engineering and Data Compression, while during his Master's degree, he focused on Antivirus, OS & Network Security research. During his Ph.D., he conducted research in the areas of Big Data, Signal Processing, Satellite, and Geosciences.

I Putu Agung Bayupati , Universitas Udayana

Dr. Eng. I Putu Agung Bayupati, S.T., M.T. is a Lecturer in the Information Technology program. He holds the rank of IIIc/Penata. He earned his Bachelor's degree in Engineering from Udayana University in 2000, followed by a Master's degree from the Bandung Institute of Technology in 2005, and a Doctorate from Kanazawa University in 2012.

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Published

2023-10-01

Issue

Vol. 14 No. 02 (2023): Jurnal Buana Informatika, Volume 14, Nomor 2, Oktober 2023

Section

Computational Science

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