K-Affinity Propagation Clustering and GIS on Instagram Accounts of Tourist Destinations in Java
- 10.2991/assehr.k.200827.129How to use a DOI?
- Instagram, Tourist Destinations, Cluster, SIG, K-Affinity Propagation Clustering
This research was conducted at the Department of Statistics of Indonesian Islamic Universities. The purpose of this study was to determine the general description of tourist destinations, the formation of tourist destination clusters, and the application of GIS. The tourist destination data used in this study were obtained from Instagram accounts on Java from January to December 2018. From each of these account posts there is a like value that researchers use as a reference for the most popular tourist destinations. The analytical methods used in this study are descriptive analysis, K-Affinity Propagation Clustering and GIS application. Obtained research results that in general tourist destinations are divided into 3 categories, namely nature, culture, and man-made. Grouping is formed using 3 clusters in each Instagram account to group each tourist destination from the level of the lowest number of likes to the highest. Then, with the application of GIS a visualization of mapping tourist destinations will be formed in Java in 2018. This research is expected to be able to provide benefits to the government especially the ministry of tourism in order to increase promotion through social media and review services related to tourist destinations offered on Java.
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Anugrah Sandra Aprilliana AU - Muhammad Muhajir PY - 2020 DA - 2020/08/28 TI - K-Affinity Propagation Clustering and GIS on Instagram Accounts of Tourist Destinations in Java BT - Proceedings of the SEMANTIK Conference of Mathematics Education (SEMANTIK 2019) PB - Atlantis Press SP - 122 EP - 129 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.200827.129 DO - 10.2991/assehr.k.200827.129 ID - Aprilliana2020 ER -