Analysis of International Tourist Visits Based on Nationality and Tourism Travel Characteristics Using Complete Linkage

Abstract. This research aims to analyze the characteristics of international tourists in Indonesia using Clustering Method: Complete Linkage. The study successfully identified 5 distinct clusters based on nationality and tourism travel characteristics. The analysis showed significant differences between clusters in terms of country of origin, travel patterns, preferences, expenditure, and tourist activities. Cluster 1 was dominated by ASEAN and Middle Eastern countries with stable visitation patterns influenced by geographical proximity and cultural and business relationships. Cluster 2 was the largest group, encompassing various countries with holiday and business tourism characteristics, longer stays, and higher expenditure. Clusters 3, 4, and 5 each consisted of a single country: Timor Leste, Hong Kong, and Papua New Guinea respectively, with unique visitation patterns. Each cluster showed differences in travel purposes, length of stay, expenditure, and activities of interest. A deep understanding of each tourist group’s characteristics was crucial for developing more targeted tourism marketing strategies. The clustering results could be utilized for infrastructure planning, resource allocation, promotional strategies, and service improvements tailored to each group’s characteristics, thereby enhancing tourist experiences and Indonesia’s overall tourism competitiveness.

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Publication Details

Journal
STATISTIKA Journal of Theoretical Statistics and Its Applications
Published
2025-06-29
DOI
https://doi.org/10.29313/statistika.v25i1.5801
Primary Topic
Diverse Aspects of Tourism Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis of International Tourist Visits Based on Nationality and Tourism Travel Characteristics Using Complete Linkage

Eko Sulistyono, Vitri Aprilla Handayani, Nahrul Hayati, Adamsyam Arrafi
STATISTIKA Journal of Theoretical Statistics and Its Applications
Diverse Aspects of Tourism Research
article

Analysis of International Tourist Visits Based on Nationality and Tourism Travel Characteristics Using Complete Linkage

Eko Sulistyono, Vitri Aprilla Handayani, Nahrul Hayati, Adamsyam Arrafi
article en

Abstract

Abstract. This research aims to analyze the characteristics of international tourists in Indonesia using Clustering Method: Complete Linkage. The study successfully identified 5 distinct clusters based on nationality and tourism travel characteristics. The analysis showed significant differences between clusters in terms of country of origin, travel patterns, preferences, expenditure, and tourist activities. Cluster 1 was dominated by ASEAN and Middle Eastern countries with stable visitation patterns influenced by geographical proximity and cultural and business relationships. Cluster 2 was the largest group, encompassing various countries with holiday and business tourism characteristics, longer stays, and higher expenditure. Clusters 3, 4, and 5 each consisted of a single country: Timor Leste, Hong Kong, and Papua New Guinea respectively, with unique visitation patterns. Each cluster showed differences in travel purposes, length of stay, expenditure, and activities of interest. A deep understanding of each tourist group’s characteristics was crucial for developing more targeted tourism marketing strategies. The clustering results could be utilized for infrastructure planning, resource allocation, promotional strategies, and service improvements tailored to each group’s characteristics, thereby enhancing tourist experiences and Indonesia’s overall tourism competitiveness.

STATISTIKA Journal of Theoretical Statistics and Its ApplicationsVol. 25(1)
Universitas Batam (ID)
Openalex Percentile: Top 79%
Diverse Aspects of Tourism Research
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Analysis of International Tourist Visits Based on Nationality and Tourism Travel Characteristics Using Complete Linkage — Eko Sulistyono, Vitri Aprilla Handayani, et al. · STATISTIKA Journal of Theoretical Statistics and Its Applications (2025) | TGRS Research Map | TGRS