Implementasi algoritma genetika dalam mengestimasi kepadatan populasi jackrabbit dan coyote

Dian Savitri, Ninik Wahju Hidajati, Hasan S. Panigoro


This article studies about the parameter estimation using genetic algorithm for a Lotka-Volterra prey-predator model. The secondary data consist of the density of jackrabbit as prey and coyote as predator in Southwest Presscott–Arizona are used. As results, the Mean Absolute Percentage Error (MAPE) are computed to compare the results of parameter estimation and the real data. We have shown that MAPE for jackrabbit and coyote respectively given by 7.75424% and 7.95283%. This results show that the parameter estimation with genetic algorithm using Lotka-Volterra model is passably. Furthermore, some numerical simulations are portrayed to show each population density for the next 100 years.


Genetic Algorithm; Prey-predator Model; Parameter Estimation; Simulation

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