The Study of the Distribution and Clustering of Tourist Attraction Zones and Facilities in Buriram Province using the DBSCAN Algorithm
DOI:
https://doi.org/10.14456/jiskku.2024.17Keywords:
Distribution of tourist attractions, Clustering of tourism zones, DBSCAN algorithm, Data Management, Spatial dataAbstract
Purposes: To investigate the distribution and clustering of tourist attraction zones and facilities in Buriram Province using the DBSCAN algorithm and to cluster the tourism zones in Buriram Province.
Methodology: The research methodology employed five stages of data mining. Firstly, data collection was conducted by extracting 400 data points from websites. Secondly, data preparation was performed. Thirdly, the data were grouped using the DBSCAN algorithm. Fourthly, the results were presented through maps displaying the spatial distribution of tourist attractions and facilities and showcasing the clustering of tourism zones. Lastly, the effectiveness of the grouped tourism zones in Buriram Province was evaluated by comparing them with existing tourism routes.
Findings: The research findings reveal that the DBSCAN algorithm successfully clustered the tourism zones in Buriram Province using data extracted from websites. The study identified three distinct zones: the sports tourism zone, the Khmer cultural heritage tourism zone, and the culinary cultural tourism zone. Comparing the grouped tourism zones with the established tourism routes in Buriram Province showed a correlation between the two datasets. This indicates that the DBSCAN algorithm can be utilized as a valuable tool for studying the distribution and clustering of tourism zones in Buriram Province.
Applications of this study: The DBSCAN algorithm can be used as a tool to present data on the spatial distribution of tourist attraction zones in Buriram Province in order to support the consideration of tourism development and promotion in the province.
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References
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