TY - GEN
T1 - Multivariate Analysis to Evaluate the Impact of COVID-19 on the Hotel Industry in Indonesia
AU - Saputri, Prilyandari Dina
AU - Angrenani, Arin Berliana
AU - Guminta, Dinda Galuh
AU - Leviany, Fonda
AU - Fitriana, Ika Nur Laily
AU - Rahayu, Santi Puteri
AU - Khusna, Hidayatul
N1 - Publisher Copyright:
© 2021, Springer Nature Singapore Pte Ltd.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Biplot
KW - COVID-19
KW - Clustering
KW - Hotel
KW - K-Means
KW - SOM
UR - http://www.scopus.com/inward/record.url?scp=85119453205&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-7334-4_30
DO - 10.1007/978-981-16-7334-4_30
M3 - Conference contribution
AN - SCOPUS:85119453205
SN - 9789811673337
T3 - Communications in Computer and Information Science
SP - 411
EP - 426
BT - Soft Computing in Data Science - 6th International Conference, SCDS 2021, Proceedings
A2 - Mohamed, Azlinah
A2 - Yap, Bee Wah
A2 - Zain, Jasni Mohamad
A2 - Berry, Michael W.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th International Conference on Soft Computing in Data Science, SCDS 2021
Y2 - 2 November 2021 through 3 November 2021
ER -