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) |
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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 |