This study aims to model the dynamic system of transportation choices in Gorontalo City, evaluate improvements in public transportation service conditions, and identify interactions among various influencing variables. A quantitative approach using dynamic system modeling is applied, as this method is effective in capturing complex relationships between variables over time. Findings reveal a consistent upward trend in the number of vehicles in Gorontalo City. According to BPS data, the number of vehicles increased from 88,386 units in 2017 to 125,033 units in 2025, with an average annual growth of 4,581 vehicles. The modeling was conducted using the dynamic system approach through Stock and Flow Diagrams (SFD) and Causal Loop Diagrams (CLD). The study successfully captures complex interactions involving population growth, community income, birth rate, education level, and urbanization. Using STELLA software for dynamic system simulation, the analysis demonstrates that these variables have causal relationships and mutual influence, shaping the dynamics of transportation growth in Gorontalo City
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