SENTIMENT ANALYSIS ON OAKWOOD RESIDENCE CIKARANG HOTEL REVIEWS ON TRIPADVISOR WEBSITE USING K-NEAREST NEIGHBOR ALGORITHM
Keywords:
K-Nearest Neighbor, Sentiment Analysis, reviews, Tripadvisor
Abstract
Tripadvisor is used not only as a platform to find and book hotels but also as a comparison material before buying, reviews written for a hotel will greatly influence the decisions of potential guests. One of the hotels that received the majority of Excellent ratings is Oakwood Residence Cikarang. This research has several stages, the first is called the Preprocessing stage. The second stage is to use the TF-IDF method, namely to do word weighting, the last stage is to classify the data using the K-Nearest Neighbor method. The test results related to sentiment analysis at Oakwood Residence Cikarang with the K-NN algorithm get an average accuracy of k = 3 of 90%.
References
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[25] Suryadi, Ridho, A., & Murhaban. (2021). Analisis Sentimen Review Hotel Menggunakan Algoritma Naïve Bayes Classifier. TECHSI - Jurnal Teknik Informatika, 13(2), 95–105. https://doi.org/10.29103/techsi.v13i2.5596
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[2] Cahyani, R., & Pandu Adikara, P. (2019). Analisis Sentimen terhadap Ulasan Hotel menggunakan Boosting Weighted Extreme Learning Machine. Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 3(8), 2548–2964. http://j-ptiik.ub.ac.id
[3] Chandrasekaran, R. M., & Vinodhini, G. (2012). Sentiment Analysis and Opinion Mining: A Survey. In International Journal of Advanced Research in Computer Science and Software Engineering (Vol. 2, Issue 6). www.zdnet.com
[4] Demolingo, R. H., & Sriwulandari. (2022). Analisis Artificial dan Natural Attraction terhadap Kepuasan Wisatawan. Syntax Literate: Jurnal Ilmiah Indonesia, 7(3).
[5] Deviyanto, A., Didik Wahyudi, M. R., & Informatika UIN Sunan Kalijaga Yogyakarta Jl Marsda Adi Sucipto No, T. (2018). PENERAPAN ANALISIS SENTIMEN PADA PENGGUNA TWITTER MENGGUNAKAN METODE K-NEAREST NEIGHBOR. Jurnal Informatika Sunan Kalijaga), 3(1), 1–13. https://twitter.com/search?l=id&q=AHY%20since%3A2017-01-01%20until%3A2017-01-
[6] Ernawati, S., & Wati, R. (2018). Penerapan Algoritma K-Nearest Neighbors Pada Analisis Sentimen Review Agen Travel. JURNAL KHATULISTIWA INFORMATIKA, VI(1), 64–69. https://www.trustpilot.com/categories/tr
[7] Feldman, R., & Sanger, J. (2007). The text mining handbook: advanced approaches in analyzing unstructured data. Cambridge University Press.
[8] Gerson, R. F. (2002). Tingkat Kepusan Pelanggan (Widyaningrum, Ed.). PPM.
[9] Helilintar, R., Ramadhani, R. A. ·, & Rochana, S. (2017). DATA MINING K-Nearest Neighbor (D. P. Pamungkas, Ed.; 1st ed., Vol. 1). Fakultas Teknik Universitas Nusantara PGRI Kediri. https://www.researchgate.net/publication/321804055
[10] Hermawan, F., & Agung, H. (2017). Implementasi Metode K-Nearest Neighbor Pada Aplikasi Data Penjualan PT. Multitek Mitra Sejati. Jurnal Sains Dan Teknologi: Kalbiscentia, 4(2), 103` – 109.
[11] Indriyanto, J. (2021). ALGORITMA K-NEAREST NEIGHBOR UNTUK PREDIKSI NASABAH ASURANSI. PT. Nasya Expanding Management (NEM).
[12] Irawan, B. S. (2018). Manajemen Pemasaran Modern. Liberty.
[13] Kotler, P. (2002). Manajemen Pemasaran (T. Hendra, Ed.). Jakarta: Prenhalindo.
[14] Liga Suryadana, M., Nurul Nugraha, R., & Tinggi Pariwisata Bandung, S. (2018). EFFECT OF APPLICATION OF RICH MEDIA ADVERTISING ON PURCHASE DECISIONS (STUDY OF TRAVEL COMPANIES). Bisnis & Entrepreneurship, 12(2), 135–146.
[15] Liu, B. (2012). Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers.
[16] Moleong, L. J. (2002). Metodologi Penelitian Kualitatif. Remaja Rosdakarya.
[17] Nugraha, N. R. (2018). PENGARUH RICH MEDIA ADVERTISING TERHADAP KEPUTUSAN PEMBELIAN PAKET BULAN MADU BALI KEROBOKAN-SEMINYAK-PETITENGET DI BULANMADU.COM. Jurnal Ilmu Manajemen Oikonomia, 63(1).
[18] Oliver, R. L., & Sharpe, J. W. E. (2014). A Behavioral Perspective on the Consumer Second Edition Richard L Oliver (2nd ed.). McGraw-Hill.
[19] Permana, K., Putra, Z. P., & Nugroho, A. (2021). Analisa Sentimen Pengunjung Hotel Dengan K-Nearest Neighbor Studi Kasus Hotel Pop! Surabaya. Jurnal Ilmu Komputer Dan Bisnis (JIKB), XII(2), 159–166.
[20] Prakoso, P. A. (2017). Front office praktis: administrasi dan prosedur kerja. Yogyakarta: Gava Media.
[21] Rendrawan, G., & Ngr Yudha Martin Mahardika, A. (2020). Jenis Keluhan dan Cara Penanganan Keluhan di Hotel Holiday Inn Resort Baruna Bali. JMPP, 3(1).
[22] Sarudin, R., Achmad Ismail, dan, Tanggal Bulan Tahun, D., & Tanggal Bulan Tahun, D. (2021). ANALISIS ONLINE REVIEW TRIPADVISOR.COM TERHADAP MINAT PEMBELIAN PRODUK JASA AKOMODASI DI HOTEL MANHATTAN TRIPADVISOR.COM REVIEW ONLINE ANALYSIS ON THE INTEREST OF BUYING ACCOMMODATION SERVICES IN HOTEL MANHATTAN. Jurnal Hospitality Dan Pariwisata, 7(4), 33–43. https://doi.org/10.30813/.v7i1.2634
[23] Setiawan, R. A., Estetikha, A. K. A., Nurharyanto, E. M. O., Asmara, Y., & Wahyudi, A. (2022). Analisis Sentimen Hotel di Nusa Tenggara Barat Menggunakan Algoritma SVM 149. Jurnal Informasi Interaktif, 7(1), 149–155.
[24] Setiowati, Y., & Helen, A. (2018). KLASIFIKASI ANALISIS SENTIMEN MENGENAI HOTEL DI YOGYAKARTA. Scan: Jurnal Teknologi Informasi Dan Komunikasi, 13(1). www.traveloka.com
[25] Suryadi, Ridho, A., & Murhaban. (2021). Analisis Sentimen Review Hotel Menggunakan Algoritma Naïve Bayes Classifier. TECHSI - Jurnal Teknik Informatika, 13(2), 95–105. https://doi.org/10.29103/techsi.v13i2.5596
[26] Tika, Moh. P. (2005). Metode Penelitian Geografi. Jakarta: PT. Bumi Aksara.
[27] Wilson, T., Wiebe, J., & Hoffmann, P. (2005). Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. Association for Computational Linguistics. http://www.cs.pitt.edu/
Published
2022-11-02
How to Cite
Nugraha, R., Tarigan, E., & Trisnawati, Y. (2022). SENTIMENT ANALYSIS ON OAKWOOD RESIDENCE CIKARANG HOTEL REVIEWS ON TRIPADVISOR WEBSITE USING K-NEAREST NEIGHBOR ALGORITHM. Jurnal Inovasi Penelitian, 3(6), 6495-6506. https://doi.org/10.47492/jip.v3i6.2105
Section
Articles
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