THE APPLICATION OF MULTINOMIAL NAIVE BAYES FOR SENTIMENT ANALYSIS OF CULTURAL TOURISM REVIEWS: A CASE STUDY OF BOROBUDUR AND PRAMBANAN TEMPLES
DOI:
https://doi.org/10.35457/dj70zr92Keywords:
Analisis Sentimen, Candi Borobudur, Candi Prambanan, Multinomial Naive Bayes, TF-IDF , VADER, Sentiment Analysis, Borobudur Temple, Prambanan Temple, Multinomial Naive Bayes, TF-IDF, VADERAbstract
Abstract : Candi Borobudur dan Candi Prambanan dikenal sebagai dua situs warisan dunia UNESCO, yang memiliki nilai sejarah dan budaya tinggi. Penelitian ini berfokus pada analisis komparatif sentimen wisatawan berdasarkan 10.000 ulasan yang diambil dari Google Maps. Tujuannya adalah mengidentifikasi persepsi wisatawan terhadap dua destinasi sekaligus mengevaluasi aspek kekuatan dan kelemahannya untuk memberikan umpan balik berbasis data bagi pengelola wisata. Metodologi yang diterapkan menggunakan pendekatan hibrida: data ulasan dikumpulkan melalui web scraping, diterjemahkan ke Bahasa Inggris dan dilabeli secara otomatis menggunakan VADER (Valence Aware Dictionary and sEntiment Reasoner). Setelah tahap preprocessing dan pembobotan fitur menggunakan TF-IDF, model klasifikasi Multinomial Naive Bayes dilatih untuk memprediksi polaritas sentimen. Hasil analisis menunjukkan bahwa Candi Prambanan memiliki proporsi sentimen positif sebesar 82,5%, lebih tinggi dibandingkan Candi Borobudur sebesar 73,7%. Model klasifikasi mencapai akurasi 81,9% untuk Prambanan dan 74,7% untuk Borobudur. Visualisasi word cloud mengindikasikan keluhan negatif yang berulang, seperti “panas”, “harga tiket”, dan “parkir”. Analisis ini menunjukkan adanya perbedaan signifikan dalam persepsi pengunjung terhadap kedua destinasi dan memberikan kontribusi praktis dalam pengembangan strategi peningkatan kualitas layanan wisata berbasis analisis sentimen.
English Abstract: Borobudur Temple and Prambanan Temple are known as two UNESCO world heritage sites, possessing high historical and cultural value. This research focuses on a comparative sentiment analysis of tourists based on 10,000 reviews taken from Google Maps. The objective is to identify tourist perceptions of the two destinations while also evaluating their strengths and weaknesses to provide data-driven feedback for tourism management. The methodology applied uses a hybrid approach: review data is collected via web scraping, translated into English, and automatically labeled using VADER (Valence Aware Dictionary and sEntiment Reasoner). After the preprocessing stage and feature weighting using TF-IDF, a Multinomial Naive Bayes classification model is trained to predict sentiment polarity. The analysis results show that Prambanan Temple has a higher proportion of positive sentiment at 82.5%, compared to Borobudur Temple at 73.7%. The classification model achieved an accuracy of 81.9% for Prambanan and 74.7% for Borobudur. Word cloud visualizations indicated recurring negative complaints, such as “panas” (hot), “harga tiket” (ticket price), and “parkir” (parking). This analysis indicates a significant difference in visitor perceptions of the two destinations and provides a practical contribution to developing strategies for improving tourism service quality based on sentiment analysis.
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[1] D. Nuryadi, F. Metandi, N. A. Hadiwijaya, M. Z. Rohman, S. Hartanto, A. Syafrizal and E. Yadie, "FINE TUNING INDOBERT UNTUK ANALISIS SENTIMEN PADA ULASAN PENGGUNA APLIKASI TIKET.COM DI GOOGLE PLAY STORE," JATI (Jurnal Mahasiswa Teknik Informatika), vol. 9, 2025.
[2] D. Rifaldi, A. Fadlil and Herman, "Teknik Preprocessing pada Text Mining Menggunakan Data Tweet 'Mental Health," Jurnal Pendidikan Teknologi Informasi, vol. 2, pp. 131-136, 2023.
[3] P. K. A. Duta, P. D. S. Pitanatri and C. P. Loanata, "BIG DATA-BASED SENTIMENT ANALYSIS ON TRIPADVISOR REVIEWS USING NAÏVE BAYES CLASSIFICATION: A CASE STUDY ON LUXURY RESORT IN BALI," Media Wisata, vol. 23, 2025.
[4] P. G. Rahadrdandi, M. Fauzan and M. P. Wicaksana, "Systematic Literature Review: Analisis Sentimen Pada Situs Google Dan Penerapannya," Innovative: Journal Of Social Science Research, vol. 4, pp. 8300-8317, 2024.
[5] R. Merdiansah, S. and A. A. Ridha, "Analisis Sentimen Pengguna X Indonesia Terkait Kendaraan Listrik Menggunakan IndoBERT," Ilmu Komputer dan Sistem Informasi (JIKOMSI), vol. 7, pp. 221-228, 2024.
[6] S. N. Budiman, S. Lestanti and E. , "Analisis Sentimen Berdasarkan Hasil Review Lokasi Google Map Menggunakan Natural Language Toolkit TextBlob dan Naïve Bayes," JAMI: Jurnal Ahli Muda Indonesia, vol. 5, p. 114–126, 2024.
[7] Y. Asri, W. N. Suliyanti, D. Kuswardani and M. Fajri, "Pelabelan Otomatis Lexicon Vader dan Klasifikasi Naive Bayes dalam menganalisis sentimen data ulasan PLN Mobile," PETIR: Jurnal Pengkajian dan Penerapan Teknik Informatika, vol. 15, pp. 221-230, 2022.
[8] M. T. Anwar and D. R. A. Permana, "Analisis Sentimen Masyarakat Indonesia Terhadap Produk Kendaraan Listrik Menggunakan VADER," Jurnal Teknik Informatika dan Sistem Informasi, vol. 10, p. 783–792, 2023.
[9] M. Gultom, J. Marikros, W. Rusli and V. C. Mawardi, "Penerapan Vader Sentiment untuk Mendeteksi Sentimen Bahasa Inggris berbasis Website," Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat CORISINDO , 2024.
[10] M. S. Hadi, J. Akbar and M. F. Zulkarnain, "Analisis Sentimen Wisata Air Terjun Di Kabupaten Lombok Tengah Menggunakan MetodeSupport Vector Machine (SVM)," SKANIKA: Sistem Komputer dan Teknik Informatika, vol. 8, pp. 318-329, 2025.
[11] S. Ernawati and R. Wati, "Evaluasi Performa Kernel SVM dalam Analisis Sentimen Review Aplikasi ChatGPT Menggunakan Hyperparameter dan VADER Lexicon," Jurnal Buana Informatika, vol. 15, 2024.
[12] M. P. Syah, A. P. Wardani, M. Idhom and T. , "Perbandingan Representasi Teks Tf-Idf Dan Bert Terhadap Akurasi Cosine Similarity Dalam Penilaian Otomatis Jawaban Berbasis Teks," Data Sciences Indonesia, 2025.
[13] M. I. Maulana, E. Budianita, M. Fikry and F. Yanto, "KLASIFIKASI SENTIMENT ULASAN APLIKASI SAUSAGE MAN MENGGUNAKAN VADER LEXICON DAN NAIVE BAYES CLASIFIER," Jurnal Sistem Komputer dan Informatika (JSON), 2023.
[14] D. Rifaldi, T. S. Famuji, B. O. S. Miranda, F. P. Ramadhan, I. P. Mulyadi, V. Saputra and G. P. I. Fanani, "Evaluasi Sentimen Pengguna ChatGPT Menggunakan Naive Bayes: Tinjauan dari Confusion Matrix dan Classification Report," Jurnal Riset Sistem dan Teknologi Informasi (RESTIA), vol. 3, 2025.
[15] M. Y. Pratama and C. Crysdian, ""Klasifikasi User Review pada Aplikasi Online Travel Booking Menggunakan Multinomial Naïve Bayes,"," The Indonesian Journal of Computer Science (IJCS), vol. 14, 2025.
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