Use of genetic algorithm method for mathematical model for dengue fever = penggunaan metode genetic algorithm pada model matematika untuk demam berdarah

Tanoto, Patrick Alfredo (2018) Use of genetic algorithm method for mathematical model for dengue fever = penggunaan metode genetic algorithm pada model matematika untuk demam berdarah. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Dengue fever is an infectious disease caused by dengue virus. This virus consists of four serotypes, that is DEN-1, DEN-2, DEN3, dan DEN-4. Those who have already infected by dengue fever with a certain serotype can be affected by dengue fever again with different serotype. The change of population infected by dengue fever can be modeled into a system of differential equations. We discuss about mathematical model for dengue fever caused by two serotypes of virus, along with designing genetic algorithm used to find the parameters from the model. This mathematical model is designed based on SIR and SIRS model with demographic elements. This model is further tested through equilibrium point analysis. Using fourth-order Runge-Kutta Method, numerical solution will be made that will be the data which simulates the model. Then system of genetic algorithm will be used using that data and some known parameters. The outputs are unknown parameters from the model as a solution. The system is tested with a series of experiments. Simulation process is done to find the optimal value of some variables in genetic algorithm, such as number of chromosomes, selection value, crossover value, and mutation value. These values will result an approximation solution with the lowest error percentage./ Demam berdarah merupakan penyakit menular yang disebabkan oleh virus dengue. Virus ini terdiri dari empat serotipe, yaitu DEN-1, DEN-2, DEN3, dan DEN-4. Seseorang yang telah terkena demam berdarah dengan serotipe tertentu dapat terkena demam berdarah lagi dengan serotipe yang berbeda. Perubahan jumlah populasi yang terkena demam berdarah ini dapat dimodelkan ke dalam bentuk sistem persamaan diferensial. Tugas akhir ini akan membahas model matematika untuk kasus demam berdarah yang disebabkan oleh dua serotipe virus, serta perancangan sistem genetic algorithm yang digunakan untuk mencari parameter dari model. Model matematika ini dirancang berdasarkan model SIR dan SIRS dengan unsur demografi. Model yang telah dibentuk ini selanjutnya diuji melalui analisis titik tetap. Dengan menggunakan metode Runge-Kutta orde 4, akan dibuat solusi numerik yang akan menjadi data yang mensimulasikan model. Selanjutnya sistem genetic algorithm digunakan dengan menggunakan data tersebut dan parameter yang diketahui. Keluarannya berupa parameter dari model yang tidak diketahui nilainya sebagai solusi. Sistem ini diuji melalui serangkaian percobaan. Proses simulasi dilakukan untuk mencari nilai optimal dari beberapa variabel pada genetic algorithm, antara lain jumlah kromosom, nilai seleksi, nilai persilangan, dan nilai mutasi. Nilai optimal yang dihasilkan ini nantinya akan menghasilkan solusi aproksimasi dengan persentase error terkecil. / Dengue fever is an infectious disease caused by dengue virus. This virus consists of four serotypes, that is DEN-1, DEN-2, DEN3, dan DEN-4. Those who have already infected by dengue fever with a certain serotype can be affected by dengue fever again with different serotype. The change of population infected by dengue fever can be modeled into a system of differential equations. We discuss about mathematical model for dengue fever caused by two serotypes of virus, along with designing genetic algorithm used to find the parameters from the model. This mathematical model is designed based on SIR and SIRS model with demographic elements. This model is further tested through equilibrium point analysis. Using fourth-order Runge-Kutta Method, numerical solution will be made that will be the data which simulates the model. Then system of genetic algorithm will be used using that data and some known parameters. The outputs are unknown parameters from the model. The system is tested with a series of experiments. Simulation process is done to find the optimal value of some variables in genetic algorithm, such as number of chromosomes, selection value, crossover value, and mutation value. These values will result an approximation solution with the lowest error percentage.

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Tanoto, Patrick AlfredoNIM00000009861UNSPECIFIED
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorSaputra, Kie Van IvankyNIDN0401038203kie.saputra@uph.edu
Thesis advisorStefani, DinaUNSPECIFIEDUNSPECIFIED
Additional Information: SK 82-14 TAN p 2108 ; 31001000064544
Uncontrolled Keywords: epidemiological method; system of differential equations; equilibrium points; runge-kutta method; genetic algorithm
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: University Subject > Current > Faculty/School - UPH Karawaci > School of Information Science and Technology > Informatics
Current > Faculty/School - UPH Karawaci > School of Information Science and Technology > Informatics
Depositing User: Mr Samuel Noya
Date Deposited: 02 Oct 2019 03:48
Last Modified: 31 Oct 2023 09:31
URI: http://repository.uph.edu/id/eprint/4724

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