<![CDATA[Population dynamics modeling is one of the important approaches in understanding population development and its influence on various aspects of life, such as economic, social, and environmental. This article discusses the application of differential equation methods in modeling population dynamics, with a focus on the analysis of growth and interactions between populations. The models used include exponential growth models, logistics, and the Lotka-Volterra model to describe competitive interactions and predations between populations. Through numerical simulations and qualitative analysis, this article shows how parameters such as birth rate, mortality, and environmental carrying capacity affect population growth patterns. In addition, the influence of external factors such as government policies and natural disasters is also incorporated into the model to expand the application in real contexts. The results of the analysis show that the differential equation model is able to provide an accurate picture of population dynamics if the parameters are estimated correctly. This article also highlights the importance of model validation using empirical data to ensure prediction reliability. This modeling can be used as a tool in development planning, resource allocation, and risk mitigation in various sectors. The conclusion of this study is that the differential equation method is not only effective in explaining population phenomena, but also flexible to adapt to various dynamic conditions. As such, this approach offers a significant contribution to demographic studies and data-driven decision-making.]]>
