<![CDATA[Corruption remains a critical issue hindering Indonesia's development across various sectors, necessitating innovative approaches to combat it. This study explores alternative strategies to eradicate corruption by leveraging mathematical modeling and numerical simulations. A dynamic system representing corruption propagation is formulated, considering key variables such as enforcement intensity, public awareness, and policy effectiveness. The 4th-order Runge Kutta method simulates the model and analyzes the impact of various strategic interventions over time. The results show that the difference in initial conditions significantly affects the level of corruption, which increases or decreases in a specific time. These findings provide valuable insights for policymakers and stakeholders in designing effective, data-driven anti-corruption strategies, emphasizing the integration of rigorous mathematical tools with socio-political frameworks. The study highlights the potential of numerical simulations as a complementary approach to traditional qualitative analyses in addressing complex societal challenges like corruption.]]>
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