Analysis Of Tourist Visit Places Using Principal Component Analysis In The K-Means Method

DOI

10.2991/978-94-6463-618-5_4How to use a DOI?

Keywords

Tourism; Visiting Places; Tourists; PCA/Principal Component Analysis; K- Means

Abstract

Tourism is a place where domestic and foreign tourists visit with many facilities which aim to increase the number of visits abroad with E-tourism which can further develop with quality internet data services. The opportunity for tourism operators to introduce lesser-known tourism destinations will be greater, thereby increasing the number of tourists visiting. This research will create a system to analyze the level of accuracy of grouping data on tourist visits using the K-Means method and apply the PCA/Principal Component Analysis method in grouping tourist visits using data taken from the Central Statistics Agency from 2020–2022 on the BPS North Kalimantan website, website Ministry of Park and Creative Economy and National Library website. Therefore, tourist visiting places in North Kalimantan will be grouped based on the number of tourist visits into several clusters, namely tourist visiting places that are good, quite good and not so good using the k-means method and the PCA/Principal Component Analysis method in grouping tourist visits. The result obtained is that. There are 3 clusters with the results obtained based on a comparison of tourism clustering of places visited by tourists in North Kalimantan using the k-means method with a silhouette value of 0.945952526 which begins with reducing the dimensions of the dataset using PCA.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Sema Oktaviani Tinting
AU  - Ari Purno Wahyu Wibowo
PY  - 2024
DA  - 2024/12/29
TI  - Analysis Of Tourist Visit Places Using Principal Component Analysis In The K-Means Method
BT  - Proceedings of the Widyatama International Conference on Engineering 2024 (WICOENG 2024)
PB  - Atlantis Press
SP  - 27
EP  - 35
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-618-5_4
DO  - 10.2991/978-94-6463-618-5_4
ID  - Tinting2024
ER  -