Analisis dan estimasi parameter model epidemi dengan waktu tunda dengan algoritma genetika = Analysis and parameter estimation of epidemic model with time delay with genetic algorithm

Armando, Yoso (2021) Analisis dan estimasi parameter model epidemi dengan waktu tunda dengan algoritma genetika = Analysis and parameter estimation of epidemic model with time delay with genetic algorithm. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Penularan penyakit, merupakan sebuah proses yang tidak terjadi secara langsung. Terdapat banyak faktor yang dapat membuat terjadinya penundaan dalam proses penularan. Pada penelitian ini, akan dilakukan analisis terhadap model epidemi SI, SIR, SIS, dan SIRS dengan mempertimbangkan waktu tunda, serta mengestimasi nilai parameter pada model berdasarkan data dengan menggunakan Algoritma Genetika. Penelitian akan dilakukan dengan menganalisa model tanpa waktu tunda secara analitik terlebih dahulu, setelah itu akan dilakukan simulasi numerik terhadap model tanpa waktu tunda dan dengan waktu tunda dengan menggunakan MATLAB. Pada bagian akhir dari penelitian, dilakukan estimasi nilai parameter berdasarkan data dengan menggunakan Algoritma Genetika. Hasil penelitian menunjukkan bahwa kestabilan titik kesetimbangan dari model tanpa waktu tunda belum dapat ditentukan dari proses linearisasi, namun secara numerik kestabilan titik kesetimbangan dan pengaruh waktu tunda dapat terlihat. Algoritma Genetika yang kurang dapat mengestimasi nilai parameter dengan akurat serta adanya hasil yang tak wajar pada model SIS. Kesimpulan dari penelitian ini adalah, 1) waktu tunda tidak mempengaruhi kestabilan titik kesetimbangan, namun dapat mempengaruhi konvergensi dari kestabilan tersebut, 2) hasil estimasi nilai parameter dengan Algoritma Genetika kurang akurat./Disease transmission, is a process that does not occur directly. There are many factors that can cause delays in the transmission process. In this study, an analysis of the SI, SIR, SIS, and SIRS epidemic models will be carried out by considering time delay, as well as estimating the parameter values in the model based on the data using the Genetic Algorithm. The research will be done by analyzing the model without time delay analytically first, after that numerical simulation will be carried out on the model without time delay and with time delay using MATLAB. At the end of the research, the parameter value estimation is carried out based on the data using the Genetic Algorithm. The results showed that the stability of the equilibrium point of the model without a time delay could not be determined from the linearization process, but numerically the stability of the equilibrium point and the effect of the time delay could be seen. Genetic Algorithm which is less able to estimate parameter values accurately and there are abnormal results in the SIS model. The conclusions of this study are, 1) the delay time does not affect the stability of the equilibrium point, but can affect the convergence of the stability, 2) the estimation results of parameter values with Genetic Algorithms are less accurate.
Item Type: Thesis (Bachelor)
Creators:
Creators
NIM
Email
ORCID
Armando, Yoso
NIM00000022100
yosoarmando09@gmail.com
UNSPECIFIED
Contributors:
Contribution
Contributors
NIDN/NIDK
Email
Thesis advisor
Saputra, Kie Van Ivanky
NIDN0401038203
kie.saputra@uph.edu
Thesis advisor
Cahyadi, Lina
NIDN0328077701
linacahyadi@gmail.com
Uncontrolled Keywords: waktu tunda; simulasi; algoritma genetika, dde23, matlab
Subjects: Q Science > QA Mathematics
Divisions: University Subject > Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Depositing User: Users 5943 not found.
Date Deposited: 26 Aug 2021 07:38
Last Modified: 26 Aug 2021 07:38
URI: http://repository.uph.edu/id/eprint/42166

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