GOOGLE TRENDS ANALYTICS DALAM BIDANG PARIWISATA
Abstract views: 1589
DOI:
https://doi.org/10.36456/majeko.vol24.no2.a2069
Keywords:
google trends, pariwisata, big data, word cloud, prediksiAbstract
Perkembangan era ke arah digital berakibat terdapatnya berbagai jenis data yang beragam mulai dari text, photo, video, music, postingan di sosial media dan memiliki karakteristik 4V (Volume, Velocity, Variety, Veracity) yang dikenal dengan nama Big Data. Data tersebut dapat digunakan sebagai data penelitian yang dapat meningkatkan tingkat keakurasian dalam menyelesaikan suatu permasalahan. Salah satu big data sederhana yaitu google trends yang dapat digunakan sebagai prediksi maupun kebijakan lainnya. Penelitian ini mengkaji pemanfaatan google trends dalam bidang pariwisata. Hasil dari penelitian ini adalah penelitian mengenai google trends dan pariwisata mengalami tren naik, dan sebagian besar analisis yang digunakan untuk google trends adalah prediksi. Indonesia menjadi dua puluh besar negara yang mencari istilah google trends pada mesin penulusarn web Google, namun masih jarang yang menggunakannya sebagai data penelitian, bahkan untuk pariwisata belum terdapat penelitian yang menggunakan google trends. Untuk itu, penelitian ini dapat dijadikan rujukan informasi pertama dalam pencarian google trends di bidang pariwisata.
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Anggraeni, W., & Aristiani, L. (2017). Using Google Trend data in forecasting number of dengue fever cases with ARIMAX method case study: Surabaya, Indonesia. Proceedings of 2016 International Conference on Information and Communication Technology and Systems, ICTS 2016. https://doi.org/10.1109/ICTS.2016.7910283
Bangwayo-Skeete, P. F., & Skeete, R. W. (2015). Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach. Tourism Management. https://doi.org/10.1016/j.tourman.2014.07.014
Blazquez, D., & Domenech, J. (2018). Big Data sources and methods for social and economic analyses. Technological Forecasting and Social Change, 130, 99–113. https://doi.org/10.1016/j.techfore.2017.07.027
Carrière-Swallow, Y., & Labbé, F. (2013). Nowcasting with Google trends in an emerging market. Journal of Forecasting. https://doi.org/10.1002/for.1252
Dergiades, T., Mavragani, E., & Pan, B. (2018). Google Trends and tourists’ arrivals: Emerging biases and proposed corrections. Tourism Management. https://doi.org/10.1016/j.tourman.2017.10.014
Google. (2019). Google Trends Help, in, Google Inc.
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Ullah Khan, S. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98–115. https://doi.org/10.1016/j.is.2014.07.006
Husnayain, A., Fuad, A., & Lazuardi, L. (2019). Correlation between Google Trends on dengue fever and national surveillance report in Indonesia. Global Health Action. https://doi.org/10.1080/16549716.2018.1552652
Jun, S. P., Yoo, H. S., & Choi, S. (2018a). Ten years of research change using Google Trends: From the perspective of big data utilizations and applications. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2017.11.009
Jun, S. P., Yoo, H. S., & Choi, S. (2018b). Ten years of research change using Google Trends: From the perspective of big data utilizations and applications. Technological Forecasting and Social Change, 130, 69–87. https://doi.org/10.1016/j.techfore.2017.11.009
Kambatla, K., Kollias, G., Kumar, V., & Grama, A. (2014). Trends in big data analytics. Journal of Parallel and Distributed Computing, 74(7), 2561–2573. https://doi.org/10.1016/j.jpdc.2014.01.003
Kwan, Z., Yong, S. S., & Robinson, S. (2019). Analysis of Internet searches using Google Trends to measure interest in sun protection and skin cancer in selected South-East Asian populations. Photodermatology Photoimmunology and Photomedicine. https://doi.org/10.1111/phpp.12510
Li, J., Xu, L., Tang, L., Wang, S., & Li, L. (2018). Big data in tourism research: A literature review. Tourism Management. https://doi.org/10.1016/j.tourman.2018.03.009
Nijman, V. (2015). CITES-listings, EU eel trade bans and the increase of export of tropical eels out of Indonesia. Marine Policy. https://doi.org/10.1016/j.marpol.2015.04.006
Önder, I., & Gunter, U. (2016). Forecasting tourism demand with Google Trends for a major European city destination. Tourism Analysis. https://doi.org/10.3727/108354216X14559233984773
Padhi, S. S., & Pati, R. K. (2017). Quantifying potential tourist behavior in choice of destination using Google Trends. Tourism Management Perspectives. https://doi.org/10.1016/j.tmp.2017.07.001
Pan, B., Wu, D. C., & Song, H. (2012). Forecasting hotel room demand using search engine data. Journal of Hospitality and Tourism Technology. https://doi.org/10.1108/17579881211264486
Park, S., Lee, J., & Song, W. (2017). Short-term forecasting of Japanese tourist inflow to South Korea using Google trends data. Journal of Travel and Tourism Marketing. https://doi.org/10.1080/10548408.2016.1170651
Paturohman, S., Suhartanto, D., & Muflih, M. (2018). The Effect of Consumer Interest on Islamic Bank Deposits: An Analysis Using Google Trends. 2018 International Conference on Information Technology Systems and Innovation, ICITSI 2018 - Proceedings. https://doi.org/10.1109/ICITSI.2018.8695913
Rivera, R. (2016). A dynamic linear model to forecast hotel registrations in Puerto Rico using Google Trends data. Tourism Management. https://doi.org/10.1016/j.tourman.2016.04.008
Santika, B. M., Arini, C. D., K, W. S., Ortega, S. P. Q., Kleinman, C. W., Almudhahkah, F. H. Y. Y. M., & Al Meseb, D. M. M. N. R. (2018). THE STRATEGY OF REACHING THE INTERNATIONAL MARKET SHARE FOR PT. HILDAN FATHONI INDONESIA. International Journal of Applied Business and International Management. https://doi.org/10.32535/ijabim.v2i2.11
Scott, J., Carrington, P., Marin, A., & Wellman, B. (2015). Social Network Analysis: An Introduction. In The SAGE Handbook of Social Network Analysis. https://doi.org/10.4135/9781446294413.n2
Shu, H. (2016). Big data analytics: six techniques. Geo-Spatial Information Science, 19(2), 119–128. https://doi.org/10.1080/10095020.2016.1182307
Suhermi, N., Suhartono, Permata, R. P., & Rahayu, S. P. (2019). Forecasting the Search Trend of Muslim Clothing in Indonesia on Google Trends Data Using ARIMAX and Neural Network. https://doi.org/10.1007/978-981-15-0399-3_22
Sullivan, D. (2016). Google now handles at least 2 trillion searches per year.
Vaughan, L., & Chen, Y. (2015). Data mining from web search queries: A comparison of google trends and baidu index. Journal of the Association for Information Science and Technology. https://doi.org/10.1002/asi.23201
Yang, X., Pan, B., Evans, J. A., & Lv, B. (2015). Forecasting Chinese tourist volume with search engine data. Tourism Management. https://doi.org/10.1016/j.tourman.2014.07.019
