Regional Mapping Based on Tourism Destinations in West Java: K-Medoid Clustering Analysis

Authors

  • Nafis Almajid Universitas Bhayangkara Jakarta Raya
  • Prima Dina Atika Universitas Bhayangkara Jakarta Raya
  • Khairunnisa Fadhilla Ramdhania Universitas Bhayangkara Jakarta Raya

Keywords:

Tourism Destinations, Tourism, regional analysis, K-Medoid, West Java

Abstract

The growth of the tourism sector in West Java demands an optimal development strategy. This study aims to cluster regions in West Java based on the characteristics of their tourist destinations using the K-Medoid algorithm. This algorithm was chosen because of its superiority in producing optimal clusters and robustness to outliers. Data on tourist destination characteristics were analyzed using the K-Medoid algorithm and the Elbow method to determine the optimal number of clusters. As a result, three clusters with different characteristics were formed. The first cluster, "Medium potential and achievement", consists of 1 region with unoptimized potential for campsite tourism. The second cluster, "High potential and moderate achievement", consists of 25 regions with a diversity of attractions and a high number of visits. The third cluster, "Medium potential and high achievement", consists of 1 region with popular historical and cultural attractions and high visitation. The model evaluation showed a DBI score of 0.08, indicating good clustering quality. This research is expected to provide insights for the government and related stakeholders to formulate targeted tourism development policies in West Java. The K-Medoid algorithm helps identify certain patterns, providing deeper insights into regional differences in terms of tourism.

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Published

2025-03-11

How to Cite

Almajid, N., Dina Atika, P., & Fadhilla Ramdhania, K. (2025). Regional Mapping Based on Tourism Destinations in West Java: K-Medoid Clustering Analysis. International Journal on Information and Communication Technology (IJoICT), 10(2), 287–296. Retrieved from https://socjs.telkomuniversity.ac.id/ojs/index.php/ijoict/article/view/1011

Issue

Vol. 10 No. 2 (2024): Vol.10 No. 2 Dec 2024

Section

Data Science

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