Implementasi Algoritma Genetika untuk Estimasi Parameter Model Matematika SEIR

Abstract View: 73, PDF Download: 61

Authors

  • Aminatus Sa'adah Institut Teknologi Telkom Purwokerto
  • Prihantini Prihantini Institut Teknologi Bandung

DOI:

https://doi.org/10.32665/james.v7i1.1940

Keywords:

Genetic Algorithm, SEIR Model, COVID-19, Parameter Estimation, Algoritma Genetika, Model SEIR, Estimasi Parameter

Abstract

Model matematika penyebaran penyakit yang paling umum digunakan adalah model SEIR (Susceptible-Exposed-Infected-Recovered). Dinamika model SEIR bergantung pada banyak faktor, salah satunya adalah pada nilai parameter model. Pada penelitian ini, dijelaskan langkah-langkah mengestimasi parameter pada model matematika SEIR menggunakan algoritma genetika. Algoritma genetika adalah teknik optimisasi dan pencarian berbasis prinsip genetika dan seleksi alam. Dataset kumulatif kasus positif COVID-19 di provinsi DKI Jakarta, Indonesia, digunakan sebagai bentuk pengimplementasian metode. Terdapat empat parameter yang diestimasi yaitu laju infeksi β, laju transisi α, laju kesembuhan ε, dan laju kematian akibat penyakit μ_1. Berdasarkan hasil estimasi, algoritma genetika mampu mendapatkan nilai-nilai parameter terbaik dengan error sebesar 8.90%. nilai parameter yang diperoleh adalah β=0.1908, α=0.5028, ε=0.0268, dan μ_1=0.1431.

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Published

2024-04-29

How to Cite

[1]
A. Sa’adah and P. Prihantini, “Implementasi Algoritma Genetika untuk Estimasi Parameter Model Matematika SEIR”, JaMES, vol. 7, no. 1, pp. 77–83, Apr. 2024.
Abstract View: 73, PDF Download: 61