Implementasi Algoritma Genetika untuk Estimasi Parameter Model Matematika SEIR
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DOI:
https://doi.org/10.32665/james.v7i1.1940Keywords:
Genetic Algorithm, SEIR Model, COVID-19, Parameter Estimation, Algoritma Genetika, Model SEIR, Estimasi ParameterAbstract
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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