Ordinal Logistic Modeling in the Case of Academic Anxiety: The Dominance of Time Management Factors in Final-Level Students
DOI:
10.29303/jppipa.v12i7.15463Published:
2026-07-25Downloads
Abstract
Academic anxiety is a psychological barrier often experienced by final-year students during their thesis creation. This study aims to construct and evaluate a mathematical model using the Ordinal Logistic Regression approach to predict the probability of student anxiety levels based on four predictor factors: thesis advisor support (X_1), time management (X_2), moral support (X_3), and environmental factors (X_4). Data were obtained from 115 final-year student respondents whose anxiety was measured through the Anxiety subscale of the DASS-21 instrument transformed into an ordinal scale. The parameter estimation results show that the mathematical model of the cumulative logit function fits the empirical data (p>0.05). Partially, only the time management variable (X_2) has a significant inverse effect on anxiety (0.002>0.05) with an Odds Ratio value of 0.488. These findings conclude that internal intervention through time management regulation algebraically reduces the probability of severe anxiety by 51.2% in final-year students.
Keywords:
Academic Anxiety Cumulative logit model DASS-21 Odds RatioReferences
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