Abstract
Pandemic has a significant impact on many sectors, especially for the hotel industry sector in Indonesia. To find out the impact of the pandemic on the hotel industry sector, we conducted an inferential statistic using a nonparametric location test to determine the significant differences between variables in 2019 and 2020. Then, we conducted cluster analysis using K-Means and Self-Organizing Map (SOM) methods. We also create the perceptual mapping by Biplot. Using the paired-fisher test for multivariate nonparametric location test, we found that the differences between variables relating to the occupancy rate of hotel rooms in 2019 and 2020 have been significantly decreasing. According to the biplot analysis, in 2019, the characteristics between provinces were quite different. While, in 2020, almost all provinces have identical characteristics. The result shows that SOM and K-Means have the same performance. In 2019, there are 4 clusters, and in 2020 there are 3 clusters. There has been a change in cluster members before and during the COVID-19 pandemic. Bali is the province that most affected by the COVID-19 incident because the tourism sector is the primary regional income. We found that the small and medium hotel industry is severely affected by COVID-19 outbreaks.
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Saputri, P.D. et al. (2021). Multivariate Analysis to Evaluate the Impact of COVID-19 on the Hotel Industry in Indonesia. In: Mohamed, A., Yap, B.W., Zain, J.M., Berry, M.W. (eds) Soft Computing in Data Science. SCDS 2021. Communications in Computer and Information Science, vol 1489. Springer, Singapore. https://doi.org/10.1007/978-981-16-7334-4_30
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