Penerapan Metode Runge-Kutta Orde 3 Untuk Penyelesaian Persamaan Diferensial Biasa

This research studies the application of the nth order Runge-kutta method as a numerical solution to ordinary differential equations. This method was chosen because it is able to provide high accuracy and flexibility in various PDB problems. We implement the nth-order Runge-Kutta algorithm in MATLAB and compare with other numerical methods, such as Euler's method. The results show that the nth order Runge-Kutta method is able to produce more accurate solutions, especially for nonlinear systems. This research makes a significant contribution to the development of numerical solutions for PDB and shows the potential of MATLAB as an effective tool for numerical simulation. Sensitivity analyzes of parameters and time steps were also performed to understand the impact of variations on stability and convergence.

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Publication Details

Journal
Algoritma
Published
2024-10-11
DOI
https://doi.org/10.62383/algoritma.v2i6.263
Primary Topic
Computer Science and Engineering
Type
article
Field-Weighted Citation Impact
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article

Penerapan Metode Runge-Kutta Orde 3 Untuk Penyelesaian Persamaan Diferensial Biasa

Asri cahyati sitorus pane, Novaria Br. Saragih, Jadata Dompak Ambarita
Algoritma
Computer Science and Engineering
article

Penerapan Metode Runge-Kutta Orde 3 Untuk Penyelesaian Persamaan Diferensial Biasa

Asri cahyati sitorus pane, Novaria Br. Saragih, Jadata Dompak Ambarita
article en

Abstract

This research studies the application of the nth order Runge-kutta method as a numerical solution to ordinary differential equations. This method was chosen because it is able to provide high accuracy and flexibility in various PDB problems. We implement the nth-order Runge-Kutta algorithm in MATLAB and compare with other numerical methods, such as Euler's method. The results show that the nth order Runge-Kutta method is able to produce more accurate solutions, especially for nonlinear systems. This research makes a significant contribution to the development of numerical solutions for PDB and shows the potential of MATLAB as an effective tool for numerical simulation. Sensitivity analyzes of parameters and time steps were also performed to understand the impact of variations on stability and convergence.

AlgoritmaVol. 2(6)
State University of Medan (ID)
Openalex Percentile: Top 82%
Computer Science and Engineering
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