KLASTERISASI KARAKTERISTIK WISATAWAN MANCANEGARA MENGGUNAKAN METODE K-MEANS CLUSTERING - MAHARDIKA, ANNISA AGUSTIN; KENCANA, EKA N.; SUKARSA, I KOMANG GDE; JAYANEGARA, KETUT; WIJAYAKUSUMA, IGN LANANG; SUMARJAYA, I WAYAN (E-Jurnal Matematika, 2023)
Since the Covid-19 pandemic, Indonesian tourism has experienced a drastic decline. This decline can be seen in the number of foreign tourists visiting Indonesia. The number of foreign tourist arrivals in 2020 and 2021 is far less compared to 2019 before Covid-19 entered. As a result, the Indonesian economy also suffered. Regarding the recovery of Indonesian tourism after the pandemic has been slow down, this study aims to cluster foreign tourists visiting Indonesia based on the amount of their expenditures and length of stays using the K-means algorithm. Secondary data from National Statistics Bureau classified the origin of tourists were 86 countries. Applying k-means algorithm methods to cluster country of origin, result showed they were three clusters formed based on the attributes of visiting, i.e. length of stay in Indonesia and total amount of their expenditures. Each cluster consists of 14, 54 and 18 countries. The first cluster is characterized by countries that have high tourism spending; the second cluster is formed by countries with moderate tourism spending; and the third cluster is characterized by countries with low tourism spending. The accuracy of the three clusters in explaining the variance of tourist spending is 68.8 percent.