Behavioral Analysis of Consumer Economic Decision-Making Based on Price and Location: Evidence from K-Means Clustering in the Restaurant Sector

This study examines how price and location are perceived across heterogeneous consumer segments in a traditional restaurant setting, using Pondok Gudeg Rini in Depok as a case study. Moving beyond regression-based causal models, the research employs a data-driven K-Means clustering approach to identify distinct behavioral decision patterns. A quantitative descriptive design was applied, using survey data from 100 respondents collected through structured questionnaires and analyzed with SPSS. The clustering analysis reveals three behavioral segments: (1) consumers with high price tolerance and strong decision engagement, (2) value-oriented consumers with moderate evaluations, and (3) highly price-sensitive consumers with lower decision engagement. One-way ANOVA results (p < 0.05) confirm statistically significant differences among the clusters. Rather than assuming homogeneous rational responses, the findings highlight the heterogeneity of economic decision profiles and demonstrate the relevance of clustering techniques for capturing behavioral segmentation in micro-level economic contexts.