Dicki Pramayuda
STIKOM Tunas Bangsa, Pematangsiantar, Medan, Indonesia

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Pengelompokan Tamu Asing Ke Indonesia Berdasarkan Provinsi Dengan Algoritma K-Means Dicki Pramayuda; Muhammad Ridwan Lubis; Ilham Syahputra Saragih
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 1, No 4 (2020): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v1i4.38

Abstract

The development of the industry in Indonesia has been growing rapidly; this is marked by the number of foreign guests who come to Indonesia to visit an object of tourist attraction. Also, which makes foreign guests feel happy coming to Indonesia, the population's friendliness is also one of the factors that are very supportive. Lack of information and grouping regarding the visit of foreign guests to various tourist attraction objects in various provinces resulted in difficulties for the Regional Government, especially the Office of Tourism and Creative Economy, in planning tourism marketing strategies in various provinces so that tourism promotion or marketing is not on target, causing foreign guests rarely visit tourism- tours in lesser-known provinces.The goal to be achieved in this study is to get a grouping of data on foreign guest visits in each province during the period 2014-2018 using the K-Means algorithm. K-means is a non-hierarchical data clustering method that attempts to partition existing data into one or more clusters / groups. The results obtained can be considered by the government, especially the Office of Tourism and Creative Economic in the Provinces to develop the potential of tourist attraction objects in the provinces in Indonesia.