Analisis Sentimen dan Sistem Pendukung Keputusan Menginap di Hotel Menggunakan Metode CRISP-DM dan SAW
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Yerik Afrianto Singgalen
*
Universitas Katolik Indonesia Atma Jaya, Jakarta,
Indonesia
(*) Corresponding Author
Abstract
Research combining sentiment analysis approaches with decision support systems in the hospitality industry is still very limited. This study aims to analyze hotel guest sentiment based on location, cleanliness, service, and value criteria using Cross Industry Standard Process for Data Mining (CRISP-DM) to identify five and ten famous words based on sentiment data and the sentiment classification model with the best performance. Furthermore, the results of identifying five and ten famous words based on sentiment data related to location, cleanliness, service, and value ratings were processed using the Simple Additive Weighting (SAW) method. The results of this study show that the performance of SVM algorithms using SMOTE operators has accuracy values (99.74%), precision values (100%), recall values (99.48%), f-measure values (99.74%), and AUC (100%). This shows that sentiment classification results using the SVM algorithm with SMOTE operators can be used as a sentiment data classification model with 30% training and 70% test data. This model is relevant to be used as a model for the classification process of 1680 review data obtained from the Tripadvisor website at Grand Zuri Malioboro Hotel Yogyakarta, Tentrem Hotel Yogyakarta, Grand Ambarukmo Hotel, El Royale Yogyakarta Malioboro, and Ceria Hotel @alun alun Yogyakarta. Specifically, aspects that concern guests relate to staff, breakfast, room, and service. In addition, the results of the implementation of the SAW method show that Grand Zuri Malioboro Hotel Yogyakarta ranks first with a total value of 0.907663917. Otherwise, Ceria Hotel @alun Yogyakarta Square ranks second with a total value of 0.897193878. Meanwhile, Hotel Tentrem Yogyakarta ranks third with a total value of 0.861265289. This shows that hotel guests who assess the criteria of location, cleanliness, service, and value by giving value weights as rated on the Tripadvisor website and provide importance weights with similar values, where location (0.20), cleanliness (0.25), service (0.30), value (0.25) then the alternative with the highest weight is Hotel Grand Zuri Malioboro Yogyakarta.
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References
N. W. Ritonga, S. Sudiarti, and Atika, “Pengaruh Religiusitas, Harga dan Lokasi Terhadap Keputusan Konsumen Menginap di Wisma Syariah Aceh House,” J. Ilm. Multi Disiplin Indones., vol. 2, no. 7, pp. 1–10, 2023.
A. N. Andika and A. Mifdlol, “Pengaruh Penerapan Prinsip Syariah , Kualitas Produk dan Kualitas Pelayanan terhadap Keputusan Konsumen Menginap dengan Minat Sebagai Variabel Intervening ( Studi Kasus Pada Konsumen Menginap Di Hotel Ibrahim Syariah Kota Semarang ),” MABNY J. Sharia Manag. Bus., vol. 3, no. 1, pp. 18–21, 2023.
I. S. Marwani, H. Darmawan, and E. R. U. Kalsum, “Influence Implementation of CHSE , Prices and Facilities for Decisions to Stay During the COVID -19 Pandemic at Non-Star Resort Hotels,” NHI Int. Hosp. J., vol. 1, no. 1, pp. 39–53, 2023.
K. A. Purty, H. Indriastuti, and D. Lestari, “Pengaruh Strategi Pemasaran Syariah terhadap Keputusan Menginap konsumen pada Penginapan Belatuk Guest House Syariah Samarinda,” JESM J. Ekon. Syariah Mulawarman, vol. 2, no. 1, pp. 11–18, 2023.
Y. A. Singgalen, “Analisis Performa Algoritma NBC, DT, SVM dalam Klasifikasi Data Ulasan Pengunjung Candi Borobudur Berbasis CRISP-DM,” Build. Informatics, Technol. Sci., vol. 4, no. 3, pp. 1634–1646, 2022, doi: 10.47065/bits.v4i3.2766.
Y. A. Singgalen, “Analisis Sentimen Wisatawan terhadap Kualitas Layanan Hotel dan Resort di Lombok Menggunakan SERVQUAL dan CRISP-DM,” Build. Informatics, Technol. Sci., vol. 4, no. 4, pp. 1870–1882, 2023, doi: 10.47065/bits.v4i4.3199.
Y. A. Singgalen, “Analisis Sentimen Konsumen terhadap Food , Services , and Value di Restoran dan Rumah Makan Populer Kota Makassar Berdasarkan Rekomendasi Tripadvisor Menggunakan Metode CRISP-DM dan,” Build. Informatics, Technol. Sci., vol. 4, no. 4, pp. 1899–1914, 2023, doi: 10.47065/bits.v4i4.3231.
Y. A. Singgalen, “Analisis Sentimen Pengunjung Pulau Komodo dan Pulau Rinca di Website Tripadvisor Berbasis CRISP-DM,” J. Inf. Syst. Res., vol. 4, no. 2, pp. 614–625, 2023, doi: 10.47065/josh.v4i2.2999.
Y. A. Singgalen, “Analisis Sentimen Wisatawan Melalui Data Ulasan Candi Borobudur di Tripadvisor Menggunakan Algoritma Naïve Bayes Classifier,” Build. Informatics, Technol. Sci., vol. 4, no. 3, p. 1343−1352, 2022, doi: 10.47065/bits.v4i3.2486.
Y. A. Singgalen, “Analisis Perilaku Wisatawan Berdasarkan Data Ulasan di Website Tripadvisor Menggunakan CRISP-DM : Wisata Minat Khusus Pendakian Gunung Rinjani dan Gunung Bromo,” J. Comput. Syst. Informatics, vol. 4, no. 2, pp. 326–338, 2023, doi: 10.47065/josyc.v4i2.3042.
Y. A. Singgalen, “Analisis Sentimen Wisatawan terhadap Taman Nasional Bunaken dan Top 10 Hotel Rekomendasi Tripadvisor Menggunakan Algoritma SVM dan DT berbasis CRISP-DM,” J. Comput. Syst. Informatics, vol. 4, no. 2, pp. 367–379, 2023, doi: 10.47065/josyc.v4i2.3092.
D. William, F. K. Marpaung, J. Yuniar, and C. Leslie, “Decision To Stay In Hotels In Medan City Pengaruh Harga , Kualitas Pelayanan Dan Promosi Terhadap Keputusan Pembelian Konsumen Untuk Menginap Di Hotel Kota Medan,” Manag. Stud. Entrep. J., vol. 4, no. 1, pp. 303–308, 2023.
C. C. Widayati, Islahulben, E. Ernawati, and D. R. Rahadi, “Pengaruhi Green Marketing, Brand Image, dan Service Quality terhadap Keputusan Menginap di Greenhost Boutique Prawirotaman Yogyakarta,” J. Ekon. Manaj., vol. 7, no. 2, pp. 127–138, 2021.
A. R. T. Hamdani, “Pengaruh Produk dan Media Sosial Terhadap Keputusan Menginap Pada Hotel Syariah di Bandung, Jawa Barat,” J. Res. Bus. Tour., vol. 2, no. 2, pp. 95–108, 2022, doi: 10.37535/104002220222.
A. B. Danurdara and I. G. A. G. Witarsana, “Pengaruh Tripadvisor Electronic Word Of Mouth Terhadap Online Booking Decision Tamu Domestik Di Bali,” J. Kepariwisataan Destin. Hosp. dan Perjalanan, vol. 6, no. 2, pp. 203–218, 2022, doi: 10.34013/jk.v6i2.414.
W. Wijaya, D. E. Herwindiati, and N. J. Perdana, “Penerapan Metode Support Vector Machine Untuk Analisis Sentimen Pada Ulasan Pelanggan Hotel di Tripadvisor,” J. Ilmu Komput. dan Sist. Inf., vol. 10, no. 2, pp. 1–6, 2022, doi: 10.24076/joism.2021v3i2.558.
V. W. D. Thomas and F. Rumaisa, “Analisis Sentimen Ulasan Hotel Bahasa Indonesia Menggunakan Support Vector Machine dan TF-IDF,” J. Media Inform. Budidarma, vol. 6, no. 3, pp. 1767–1774, 2022, doi: 10.30865/mib.v6i3.4218.
T. Wee and M. Liow, “Short-term rental versus small hotel industry amid COVID-19 pandemic: What drives millennials’ accommodation choices?,” J. Glob. Hosp. Tour., vol. 1, no. 1, pp. 69–84, 2022, doi: 10.5038/2771-5957.1.1.1004.
W. Adisaputra and E. Elisa, “Sistem Penunjang Keputusan Pemilihan Hotel di Kota Tanjungpinang dan Pulau Bintan Menggunakan Metode Simple Additive Weighting,” J. Comasie, vol. 4, no. 1, pp. 87–96, 2021.
P. Apriani and B. M. Nainggolan, “Pengaruh Kualitas Pelayanan, Persepsi Harga Dan Promosi Terhadap Keputusan Menginap Di Morrissey Hotel Jakarta,” SIBATIK J. J. Ilm. Bid. Sos. Ekon. Budaya, Teknol. dan Pendidik., vol. 1, no. 11, pp. 2445–2456, 2022, doi: 10.54443/sibatik.v1i11.370.
H. Lumentut, W. Nurmansyah, and S. Rumagit, “Sistem Pendukung Keputusan Pemilihan Duta Pariwisata Kabupaten Jayawijaya dengan Metode SAW,” J. Sist. Inf., vol. 14, no. 1, pp. 2520–2532, 2022.
A. Hermawan and Evan, “Hotel Recommendation System Using SAW (Simple Additive Weighting) And TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) Method,” Bit-Tech, vol. 1, no. 3, pp. 131–145, 2019, doi: 10.32877/bt.v1i3.71.
E. L. Amalia, E. N. Hamdana, and A. M. Hutami, “Implementasi Metode Ahp Dan Promethee Pada Spk Pemilihan Hotel,” J. Inform. Polinema, vol. 6, no. 1, pp. 49–54, 2020, doi: 10.33795/jip.v6i1.325.
Y. S. Pasaribu, “Sistem Pendukung Keputusan Pemilihan Hotel Bintang Lima Terbaik Di Kota Medan Menggunakan Metode Promethee,” J. Pelita Inform., vol. 7, no. 3, pp. 395–403, 2019.
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