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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.

Keywords

tourists Poisson spatial GWPR AIC

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How to Cite
Subarkah, M. Z., Wahyuningtia , R. ., Hildha , M., & Sulandari , W. (2024). Modeling the Number of Foreign Tourist Visits to Indonesia in 2020 Using GWPR Method . Enthusiastic : International Journal of Applied Statistics and Data Science, 4(2), 143–151. https://doi.org/10.20885/enthusiastic.vol4.iss2.art6
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