CLUSTER ANALYSIS OF FINANCIAL LITERACY AND FINANCIAL BEHAVIOR AMONG UNIVERSITY STUDENTS

Abstract

This study aims to classify university students based on their financial literacy and financial behavior using cluster analysis. Financial literacy and behavior are essential competencies for students as they transition toward financial independence. This study employs a quantitative exploratory approach with data collected through a structured questionnaire from undergraduate students. The variables used in the clustering process consist of financial literacy and financial behavior indicators measured using a five-point Likert scale. Data were analyzed using hierarchical cluster analysis with Ward’s method to determine the optimal number of clusters, followed by K-Means cluster analysis for final classification. The results reveal the existence of three distinct student clusters with different characteristics of financial literacy and financial behavior. These findings indicate that students are not homogeneous in managing their personal finances. The study contributes to the literature by providing a segmentation-based perspective and offers practical implications for designing targeted financial education programs for university students.