Analisis Perpindahan Wisatawan dan Preferensi Desrinasi Wisata Favorit Berdasarkan Geotag Instagram (Studi Kasus pada Destinasi Wisata Bandung Raya)

Penulis

  • Herry Irawan Universitas Telkom, Bandung
  • Eva Nurhazizah Universitas Telkom, Bandung
  • Joe Nathan C.G. Panjaitan Universitas Telkom, Bandung

DOI:

https://doi.org/10.25126/jtiik.2022935747

Abstrak

Pariwisata adalah salah satu generator utama cadangan devisa nasional dengan pertumbuhan 10,1% per tahun. Pariwisata juga diharapkan akan menjadi kekuatan utama ekonomi lokal. Beberapa langkah ditempuh Pemerintah Provinsi Jawa Barat dalam rangka meningkatkan kunjungan wisata, salah satunya dengan penerapan teknologi komunikasi dan informasi atau dikenal dengan konsep smart tourism. Instagram adalah media yang memungkinkan pengguna dapat membagikan foto dan video. Data foto dan video pada Instagram di-generate oleh pengguna sendiri (user generated content). Media Instagram dapat menjadi alat ukur daya tarik pengunjung, mengidentifikasi point of interest popular suatu kota, saran destinasi wisata, dan bahkan membuat rute perjalanan wisata yang baik.

Penelitian ini bertujuan untuk mengidentifikasi pola kunjungan wisatawan dan preferensi tujuan wisata favorit pada 43 destinasi wisata pilihan di Bandung Raya berdasarkan data unggahan media sosial Instagram. Identifikasi pola perpindahan kunjungan wisatawan dilakukan dengan menggunakan metode association rules. Temuan dari penelitian ini adalah destinasi wisata dengan daya tarik wisata pusat perbelanjaan memiliki nilai support dan confidence yang lebih tinggi dibanding daya tarik wisata lainnya. Identifikasi destinasi wisata favorit didasarkan pada intensitas jumlah unggahan dari wisatawan (unique visitor). Penelitian ini berhasil mengidentifikasi bahwa top 3 diduduki oleh wisata pusat perbelanjaan, akan tetapi top 10 destinasi wisata didominasi oleh destinasi wisata dengan daya tarik wisata alam. Mayoritas destinasi wisata dengan daya tarik wisata rekreasi kota berada di urutan 20 terbawah.

 

Abstract

Tourism is one of the main generators of national foreign exchange reserves with a growth of 10.1% per year. Tourism is expected to become a major force for the local economy. Several steps were taken by the West Java Provincial Government in order to increase tourist visits, one of which was the application of communication and information technology or known as the concept of smart tourism. Instagram is a medium that allows users to share photos and videos. Photo and video on Instagram are generated by the users themselves (user generated content). Instagram can be a tool for measuring visitor attractiveness, identifying popular points of interest in a city, suggesting tourist destinations, and even making good travel routes.

The purpose of this study is to identify patterns of tourist visits and preferences for favorite tourist destinations in 43 selected tourist destinations in Greater Bandung based on data uploaded by Instagram social media. Identification of tourist movement pattern is done by using the association rules method. The findings of this study are tourist destinations with shopping center tourist attractions have higher support and confidence values than other tourist attractions. Identification of favorite tourist destinations is based on the intensity of the number of uploads from tourists (unique visitors). This study succeeded in identifying that the top 3 were occupied by shopping center tourism, but the top 10 tourist destinations were dominated by tourist destinations with natural tourist attractions. The majority of tourist destinations with urban recreational attractions are in the bottom 20.


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Referensi

APJII, 2018. Infografis Penetrasi & Perilaku Pengguna Internet di Indonesia. [online]. Tersedia melalui: https://apjii.or.id/content/read/39/342/Hasil-Survei-Penetrasi-danPerilaku-Pengguna-Internet-Indonesia-2018 [Diakses 15 November 2019]

ARORA, J., BHALLA, N., RAO, S., 2013. A Review on Association Rule Mining Algorithms. International Journal of Innovative Research in Computer and Communication Engineering (1)5.

BAPPENAS, 2018. Menteri Bambang Brodjonegoro: “PDB Indonesia terbesar kelima dunia di tahun 2045”. [online]. Tersedia melalui: https://www.bappenas.go.id/id/berita-dan-siaran-pers/menteri-bambang-brodjonegoro-pdb-indonesia-terbesar-kelima-dunia-di-tahun-2045/ [Diakses 15 November 2019]

BUHALIS, D., & AMARANGGANA, A., 2013. Smart Tourism Destinations. In: Xiang Z., Tussyadiah I. (eds) Information and Communication Technologies in Tourism. 2014. Springer International Publishing Switzerland.

COOPER, C., 2005. Tourism Principle and Practice. Prentice-Hall.

DATABOKS, 2018. Berapa Pendapatan Devisa Dari Sektor Pariwisata Indonesia?. [online]. Tersedia melalui: https://databoks.katadata.co.id/datapublish/2018/09/10/berapa-pendapatan-devisa-dari-sektor-pariwisata-indonesia [Diakses 15 November 2019]

IRAWAN, H., WIDYAWATI, R.S., & ALAMSYAH, A., 2020. Identification of tourism destination preferences based on geotag feature on Instagram using data analytics and topic modeling. Proceedings of the Conference on Managing Digital Industry, Technology and Entrepreneurship (CoMDITE 2019); July 10-11, 2019.

JABARPROV, 2018. Indeks Pariwisata Kota Bandung Salah Satu Tertinggi Di Indonesia. [online]. Tersedia melalui: https://jabarprov.go.id/index.php/news/26881/2018/01/12/Indeks-Pariwisata-Kota-Bandung-Salah-Satu- [Diakses 15 November 2019]

KACHKAEV, A., & WOOD, J., 2013. Investigating spatial patterns in user-generated photographic datasets by means of interactive visual analytics. Paper presented at the GeoViz Hamburg: Interactive Maps that Help People Think, 6-8 Mar 2013. Hamburg, Germany: HafenCity University

KOO, C., YOO, K.H., LEE, J.N., & ZANKER, M., 2016. Special section on generative smart tourism systems and management: Man-machine interaction. International Journal of Information Management (36)6, pp.1301-1305.

LI, Y., HU, C., HUANG, C., & DUAN, L., 2017. The concept of smart tourism in the context of tourism information services. Tourism Management (58), pp.293-300.

MUKHINA, K.D., RAKITIN, S.V., & VISHERATIN, A.A., 2017. Detection of tourist attraction points using Instagram profiles. Procedia Computer Science 108C, pp. 2378–2382.

ÖNDER, I. 2017. Classifying Multi-Destination Trips in Austria With Big Data. Tourism Management Perspectives, pp.54-58.

THAMER, M., & EL-SAPPAGH, S. & EL-SHISHTAWY, T., 2020. A Semantic Approach for Extracting Medical Association Rules. International Journal of Intelligent Engineering & System 13(3).

VU, H.Q, Rong, L.R., & Yuan, M., 2016. Exploring Park Visitors’ Activities in Hong Kong using Geotagged Photos. Information and Communication Technologies in Tourism, pp.183-196.

WASILAH, & HILDAYANTI, A., 2019. Pola Pergerakan Wisatawan pada Kawasan Pariwisata Pantai Kota Makassar. Jurnal Koridor 10(1), pp.27-34.

YANG, K., WAN, W., XIA, T., HE, X., 2017. Urban tourism research based on the social media check-in data. 4th International Conference on Smart and Sustainable City (ICSSC 2017).

YULIANTO, A., 2017. Analisis Obyek Daya Tarik Wisata Favorit Berdasarkan Jumlah Pengunjung Di Daerah Istimewa Yogyakarta. Jurnal Media Wisata(15)2.

Diterbitkan

20-06-2022

Terbitan

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Ilmu Komputer

Cara Mengutip

Analisis Perpindahan Wisatawan dan Preferensi Desrinasi Wisata Favorit Berdasarkan Geotag Instagram (Studi Kasus pada Destinasi Wisata Bandung Raya). (2022). Jurnal Teknologi Informasi Dan Ilmu Komputer, 9(3), 639-646. https://doi.org/10.25126/jtiik.2022935747