TOURIST VISIT PATTERN ANALYSIS AT HOTELS IN NORTH PENAJAM PASER REGENCY USING K-MEANS CLUSTERING
DOI:
https://doi.org/10.47709/cnahpc.v7i4.6821Keywords:
Data Mining, K-Means Clustering, Tourists, Hotels, Penajam Paser UtaraAbstract
Penajam Paser Utara Regency, as a strategic area in East Kalimantan, has experienced significant development in the tourism sector in line with the plan to relocate the national capital (IKN). However, the utilization of tourist visitation data in hotels in this region is still not optimal. This study aims to analyze tourist visit patterns at Penajam Paser Utara Regency hotels using data mining techniques with the K-Means Clustering algorithm. The data used is secondary data obtained from the Penajam Paser Utara Regency Culture and Tourism Office, covering 34 hotels with variables including domestic and foreign visitors from 2019 to 2024. The clustering results show two main clusters: a high-visitation cluster comprising large hotels and a low-visitation cluster consisting of hotels with fewer visitors. The analysis reveals the dominance of domestic tourists, accounting for 99% of total visits, and the tourism sector's recovery pattern, reflecting a V-shaped recovery post-pandemic. This research contributes to hotel managers in designing market segment-based marketing strategies and local governments in designing data-driven tourism policies to enhance the sustainable competitiveness of destinations.
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