ANALISIS SENTIMEN PARIWISATA TERHADAP DATA ULASAN TRIPADVISOR TANAH LOT BALI MENGGUNAKAN METODE RANDOM FOREST

Sekar Andika Putri, - (2024) ANALISIS SENTIMEN PARIWISATA TERHADAP DATA ULASAN TRIPADVISOR TANAH LOT BALI MENGGUNAKAN METODE RANDOM FOREST. S1 thesis, Universitas Pendidikan Indonesia.

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Official URL: https://repository.upi.edu/

Abstract

Ulasan online yang terdapat pada situs wisata seperti situs TripAdvisor memiliki peran yang signifikan dalam memengaruhi keputusan wisatawan. Data ulasan bervolume besar di situs TripAdvisor membuatnya sulit untuk secara manual mengevaluasi sentimen dari setiap ulasan. Pada penelitian ini akan dilakukan analisis sentimen terhadap data ulasan pengunjung Pura Tanah Lot Bali sebagai salah satu objek wisata terpopuler di Indonesia pada situs TripAdvisor dengan menggunakan metode random forest. Metode random forest digunakan untuk melakukan prediksi sentimen. Tahapan yang dilakukan pada penelitian ini diantaranya adalah pengumpulan data, preprocessing data, pembagian data training dan data testing, labelling data, TF-IDF, training dan testing model random forest, validasi model, aspect filtering, dan pembuatan web sistem analisis sentimen. Dengan menggunakan data ulasan dari November 2010 - September 2023, model random forest secara baik melakukan klasifikasi sentimen positif, negatif, dan netral dengan nilai akurasi dan f1-score tertinggi 0.85. Hasil yang diperoleh dari analisis sentimen ini diharapkan dapat menjadi informasi yang berguna bagi banyak pihak terutama wisatawan yang ingin berkunjung ke Tanah Lot Bali. Online reviews on travel sites such as the TripAdvisor site have a significant role in influencing tourists' decisions. The large volume of review data on the TripAdvisor site makes it difficult to manually evaluate the sentiment of each review. In this research, sentiment analysis will be carried out on review data from visitors to Tanah Lot Temple, Bali as one of the most popular tourist attractions in Indonesia on the TripAdvisor site using the random forest method. The random forest method is used to predict sentiment. The stages carried out in this research include data collection, data preprocessing, dividing training data and testing data, data labeling, TF-IDF, random forest model training and testing, model validation, aspect filtering, and creating a web sentiment analysis system. Using review data from November 2010 - September 2023, the random forest model performs good classification of positive, negative and neutral sentiment with the highest accuracy and f1-score of 0.85. The results obtained from this sentiment analysis are expected to be useful information for many parties, especially tourists who want to visit Tanah Lot Bali.

Item Type: Thesis (S1)
Additional Information: ID SINTA Dosen Pembimbing: Lala Septem Riza: 5975668 Yudi Wibisono: 260167
Uncontrolled Keywords: Pariwisata, Tripadvisor, Pemrosesan bahasa alami, Analisis sentimen, Pemelajaran mesin, Algoritma random forest, Dashboard Tourism, Tripadvisor, Natural language processing, Sentiment analysis, Machine learning, Random forest algorithm, Dashboard
Subjects: G Geography. Anthropology. Recreation > GV Recreation Leisure
L Education > L Education (General)
T Technology > T Technology (General)
Divisions: Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Program Studi Ilmu Komputer
Depositing User: Sekar Andika Putri
Date Deposited: 05 Sep 2024 03:46
Last Modified: 05 Sep 2024 03:47
URI: http://repository.upi.edu/id/eprint/122781

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