Rubella disease is an infectious disease transmitted through the respiratory tract caused by a virus. In some cases, there are diseases that can enter an endemic condition, which is a condition in which the outbreak of a disease in a certain area over a long period of time. This condition can be modeled mathematically by using certain assumptions which will then seek for analytical and numerical solutions. This type of research is a literature study. This study examines the theory and application of the Runge-Kutta method in analyzing the spread of Rubella with the effect of vaccination. The Runge-Kutta method is widely used in solving ordinary differential equations and is more accurate than the Euler method. In this study, two methods were used to analyze it, namely the Runge-Kutta Order 4 and Order 5 methods which were used to analyze and compare the numerical results obtained, and the aim of the study was to obtain and interpret mathematically a mathematical model of the spread of Rubella’s disease with the effect of vaccination. and comparing the results obtained from the numerical solution using the Runge-Kutta Order 4 and Runge-Kutta Order 5 methods simulated with Maple software 13. From the results of this study, the results obtained in the 1st iteration of the numerical solution model for Rubella’s disease using the Runge-Kutta Order 4 is the value of 푆1 = 8771655, E
1 = 142, 퐼1 = 38, and R
1 = 30. While the results in the first iteration of the numerical solution model for Rubella’s disease using the Runge-Kutta Order 5 method were that the values of 푆1 = 8771759, E
1 = 142, 퐼1 = 37, and R
1 = 30 were obtained. So it can be concluded that the Order 5 Runge-Kutta is better than the Order 4 Runge-Kutta in predicting the state rate of the Rubella disease case population in the Suspectible, Exposed, Infected, Recovered, Suspected (SEIRS) model. Because the image / graph of Order 5 Runge-Kutta is more like / closer to the results of the analytical simulation using maple 13 software, which is as many as 27 infected individuals.