This study aims to solve the mathematical model of anaemia disease numerically using the Runge-Kutta fourth-order method. The mathematical model used is a SAR model in the form of a system of differential equations that includes the number of susceptible populations (S), anaemic populations (A), and recovered human populations (R) as initial values. This model is analysed and simulated with the values of µ, α, β, ε, π as parameters and carried out as many as several iterations with an interval time or h= 0.5 months. The initial values given are S0 = 12881, A0 = 129, R0 = 129. The simulation results in the first iteration are the rate of susceptible population (S) = 12754 , anaemic population (A) = 128 and recovered population (R) = 192 . In the second iteration the rate of susceptible population (S) = 12630, anaemic population (A) = 126 and recovered population (R) = 254 . From the results obtained it can be concluded that the rate of susceptible population and anaemic population has decreased, while for the recovered population has increased.