Abstract
This study aims to analyze the expenditure patterns of tourists visiting the Ke’te’ Kesu’ Tourist Attraction in North Toraja Regency. Understanding expenditure patterns is crucial for measuring the economic contribution of tourism to local communities. This research employed a quantitative method using the K-Means Cluster analysis approach to categorize tourists based on their characteristics and spending behaviors. Data collection was conducted through questionnaires, observations, and documentation involving a sample of 50 respondents selected via the accidental sampling technique. The obtained empirical data were subsequently processed using statistical software through descriptive analysis, data preprocessing (data cleaning), the Elbow Method evaluation, and cluster analysis. The computational results demonstrated the formation of three optimal tourist cluster segmentations, specifically groups with low, high, and very high expenditure levels. Significant differences in expenditure patterns for both primary and additional cost attributes were directly influenced by the respondents' characteristics, including age, occupation, income level, place of origin, length of stay, and travel purpose. The findings are expected to serve as a strategic reference for destination managers and local governments in formulating tourism development policies to optimize economic benefits for the surrounding community.
