Sentiment Analysis of Visitor Reviews on Google Maps at Kampung Coklat Tourism

Elok Nur Hamdana, Alifah Okta Nur Wardani, Ariadi Retno Tri Hayati Ririd

Sari


Google Maps plays an important role in the tourism industry, allowing visitors to share their reviews widely. These reviews not only influence potential visitors' decisions but also impact the reputation of tourist destinations. However, evaluating service quality based on offline reviews remains suboptimal compared to online reviews, which are more accessible and interpretable. This research focuses on sentiment analysis of visitor reviews on Kampung Coklat in Blitar using the Naïve Bayes algorithm. The goal is to classify reviews into positive, neutral, or negative to understand visitors' perspectives on the tourism services. Data was collected from Google Maps and processed using the Naïve Bayes method, which has proven effective in sentiment classification even with relatively small training data sets. Experimental results showed the highest accuracy of 75% with an 80% training data and 20% testing data ratio. WordCloud analysis also depicts frequently occurring words in positive, neutral, and negative reviews, providing insights into aspects influencing tourists' experiences.

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Referensi


D. Siti Utami and A. Erfina, “Analisis Sentimen Objek Wisata Bali Di Google Maps Menggunakan Algoritma Naive Bayes,†J. Sains Komput. Inform. J-SAKTI, vol. 6, no. 1, pp. 418–427, 2022.

R. Walalayo, E. A. W. Manuputty, and A. J. R. Ufie, “JURNAL ADMINISTRASI TERAPAN VOL 1, NO. 1, SEPTEMBER 2022,†vol. 1, no. 1, 2022.

K. Ariansyah, J. Prawiro, and R. Sanjaya, “Pengaruh Ulasan Online Terhadap Keputusan Wisatawan dalam Memilih Hotel,†J. Pariwisata Dan Perhotelan, vol. 2, no. 2, p. 8, Jan. 2025, doi: 10.47134/pjpp.v2i2.3559.

Y. A. Singgalen, “Analisis Sentimen Wisatawan Melalui Data Ulasan Candi Borobudur di Tripadvisor Menggunakan Algoritma Naïve Bayes Classifier,†Build. Inform. Technol. Sci. BITS, vol. 4, no. 3, 2022, doi: 10.47065/bits.v4i3.2486.

F. V. Sari and A. Wibowo, “Analisis Sentimen Pelanggan Toko Online Jd.Id Menggunakan Metode Naïve Bayes Classifier Berbasis Konversi Ikon Emosi,†J. SIMETRIS, vol. 10, no. 2, pp. 681–686, 2019.

E. N. Hamdana and M. B. I. Alfahmi, “Pengembangan Sistem Analisis Sentimen Berbasis Java Pada Data Twitter Terhadap Omnibus Law Menggunakan Algoritma Naïve Bayes dan K-Nearst Neighbor (K-NN),†J. Inform. Polinema, vol. 7, no. 2, pp. 79–84, Feb. 2021, doi: 10.33795/jip.v7i2.688.

Haniah Mahmudah, Okkie Puspitorini, Nur Adi Siswandari, Ari Wijayanti, and Eliya Alfatekha, “Metode Naive Bayes Classifier – Smoothing pada Sensor Smartphone untuk Klasifikasi Aktivitas Pengendara,†J. Nas. Tek. Elektro Dan Teknol. Inf., vol. 9, no. 3, pp. 268–277, 2020, doi: 10.22146/.v9i3.382.

D. Septiani and I. Isabela, “ANALISIS TERM FREQUENCY INVERSE DOCUMENT FREQUENCY (TF-IDF) DALAM TEMU KEMBALI INFORMASI PADA DOKUMEN TEKS,†vol. 01, no. 2, 2022.

B. Najibah Agus Ratri and Y. Arum Sari, “Analisis Sentimen Review Produk Kecantikan menggunakan Metode Naïve Bayes,†J. Pengemb. Teknol. Inf. Dan Ilmu Komput., vol. 5, no. 12, pp. 2548–964, 2021.

B. Mathayomchan and K. Sripanidkulchai, “Utilizing Google Translated Reviews from Google Maps in Sentiment Analysis for Phuket Tourist Attractions,†JCSSE 2019 - 16th Int. Jt. Conf. Comput. Sci. Softw. Eng. Knowl. Evol. Singul. Man-Mach. Intell., pp. 260–265, 2019, doi: 10.1109/JCSSE.2019.8864150.

I. F. Rozi, E. N. Hamdana, and Muhammad Balya Iqbal Alfahmi, “PENGEMBANGAN APLIKASI ANALISIS SENTIMEN TWITTER MENGGUNAKAN METODE NAÃVE BAYES CLASSIFIER (Studi Kasus SAMSAT Kota Malang),†J. Inform. Polinema, vol. 4, no. 2, p. 149, Feb. 2018, doi: 10.33795/jip.v4i2.164.

A. Menditto, M. Patriarca, and B. Magnusson, “Understanding the meaning of accuracy, trueness and precision,†Accreditation Qual. Assur., vol. 12, no. 1, pp. 45–47, Jan. 2007, doi: 10.1007/s00769-006-0191-z.

P. Agusia, M. U. A. Manurung, V. Calista, and V. C. Mawardi, “Pemanfaatan Word Cloud Pada Analisis Sentimen Dalam Menggali Persepsi Publik,†2024.




DOI: http://dx.doi.org/10.30811/jaise.v5i1.6488

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