Main Article Content
Abstract
In December 2020, the number of foreign tourists visiting Indonesia experienced a sharp decline of 88.08% compared to the number of visits in December 2019. However, compared to the previous month, November 2020, this number increased by 13.58%. Modeling the number of foreign tourists visiting Indonesia in 2020 using the Geographically Weighted Poisson Regression (GWPR) method is needed to elaborate on the Indonesian government’s policy decisions, especially in the tourism sector. The results showed that the GWPR model with the Kernel fixed Gaussian weighted function had an AIC value of 1,521,240.873, deviance of 1,521,196.695, and deviance-R2 of 0.741 or 74.1%. This model produced two different clusters of characteristics of foreign tourists’ country of origin based on the variable’s significance. Cluster one consisted of Finland and Qatar and the rest were in cluster two. The characteristics of cluster two were influenced by the rupiah exchange rate variable, short stay visa free (Bebas Visa Kunjungan Singkat, BVKS), Consumer Price Index (CPI), economic growth, total imports, and the distance of CGK to the international airport. Meanwhile, cluster one had almost the same characteristics as cluster two but was not influenced by the BVKS factor variables.
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References
H. Wulandari, R, Indriani, R. Untari, and S.S. Bethagustav, Statistik Kunjungan Wisatawan Mancanegara 2020. Jakarta, Indonesia: Badan Pusat Statistik Indonesia, 2021.
L.U. Calderwood and M. Soshkin, “The Travel & Tourism Competitiveness Report 2019: Travel and Tourism at a Tipping Point,” World Economic Forum, Geneva, Switzerland, Insight Rep., 2019.
M. Azizurrohman, R.B. Hartarto, Y-M. Lin, and F.H. Nahar, “The Role of Foreign Tourists in Economic Growth: Evidence from Indonesia,” Jurnal Ekonomi & Studi Pembangunan, Vol. 22, No. 2, pp. 313–322, Oct. 2021, doi: 10.18196/jesp.v22i2.11591.
R. Berk and J.M. MacDonald, “Overdispersion and Poisson Regression,” Journal of Quantitative Criminology, Vol. 24, pp. 264–286, Sep. 2008, doi: 10.1007/s10940-008-9048-4.
M.J. Hayat, and M. Higgins, “Understanding Poisson Regression,” Journal of Nursing Education, Vol. 53, No. 4, pp. 207–215, 2014 doi: 10.3928/01484834-20140325-04.
D.W. Osgood, “Poisson-Based Regression Analysis of Aggregate Crime Rates,” Journal of Quantitative Criminology, Vol. 16, pp. 21–43, Mar. 2000, doi: 10.1023/A:1007521427059.
R. Paternoster And R. Brame, “Multiple Routes to Delinquency? A Test of Developmental and General Theories of Crime,” Criminology, Vol. 35, No. 1, pp. 45–84, Feb. 1997, doi: 10.1111/j.1745-9125.1997.tb00870.x.
R.J. Sampson and J.H. Laub, “Socioeconomic Achievement in the Life Course of Disadvantaged Men: Military Service as a Turning Point, Circa 1940–1965,” American Sociological Review, Vol. 61, No. 3, pp. 347–367, Jun. 1996.
I.M. Fadlilah, Sugiman, and Sunarmi, “Estimasi Parameter Model Regresi Spasial dengan Metode Geographically Weighted Poisson Regression, ” UNNES Journal of Mathematics, Vol. 8, No. 2, pp. 21–31, Nov. 2019, doi: 10.15294/ujm.v8i2.23796.
H. Akaike, “A New Look at the Statistical Model Identification,” IEEE Transactions Automatic Control, Vol. 19, No. 6, pp. 716–723, Dec. 1974, doi: 10.1109/TAC.1974.1100705.
S. Candraningtyas, “Regresi Robust Mm-Estimator untuk Penanganan Pencilan Regresi Linier Berganda,” Jurnal Gaussian, Vol. 2, No. 4, pp. 395–404, Oct. 2013, doi: 10.14710/j.gauss.2.4.395–404.
Darnah, “Menentukan Model Terbaik dalam Regresi Poisson dengan Menggunakan Koefisien Determinasi,” Jurnal Matematika, Statistika, dan Komputasi, Vol. 6, No. 2, pp. 59–71, Jan. 2010.
W. Kusuma, D, Komalasari, and M. Hadijati, “Model Regresi Zero Inflated Poisson pada Data Overdispersion,” Jurnal Matematika, Vol. 3, No. 2, pp. 71–85, Dec. 2013, doi: 10.24843/JMAT.2013.v03.i02.p37.
L. Anselin, “An Introduction to Spatial Autocorrelation Analysis with GeoDa.” Accessed: May 20, 2022. [Online]. Available: https://www.dpi.inpe.br/gilberto/tutorials/software/geoda/tutorials/spauto.pdf
M. Fathurahman, “Pemilihan Model Regresi Terbaik Menggunakan Metode Akaike’s Information Criterion dan Schwarz Information Criterion,” Jurnal Informatika Mulawarman, Vol. 4, No. 3, pp. 37–41, Sep. 2009, doi: 10.30872/jim.v4i3.41.