Clustering Biplot on Tourist Visits in Indonesia

Isma Muthahharah; Zakiyah Mar'ah

doi:10.30812/ijecsa.v3i1.3890

Isma Muthahharah Universitas Negeri Makassar
Zakiyah Mar'ah Universitas Negeri Makassar https://orcid.org/0000-0003-2334-9240

DOI: https://doi.org/10.30812/ijecsa.v3i1.3890

Keywords: Clustering, K-Medoids, Biplot, Tourist

Abstract

This research aims to find out whether or not many tourists visited Indonesia after Covid-19 by clustering. This will generate foreign exchange earnings and contribute directly to the country's economic growth. The analytical method used in this research is K-Medoids. K-Medoids is a partition clustering technique that groups a collection of n objects into k clusters by utilizing the objects in the collection of objects to represent a cluster called a medoid. The data in this research used secondary data related to foreign tourist visits to Indonesia from several publication sources in 2017-2021. The results of this research show that there were 3 clusters obtained: Cluster 1 shows the number of tourist visits visiting Indonesia in 2017, 2018 and early 2019 because the Covid-19 pandemic has not yet occurred, Cluster 2 shows that there were no tourist visits in 2020 due to the start of the Covid-19 pandemic, and Cluster 3 indicates low tourist arrivals in 2021 due to the Covid 19 pandemic which temporarily prohibited foreign tourists from visiting Indonesia.

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