Claim Missing Document
Check
Articles

Found 18 Documents
Search

Dynamical Analysis of HIV/AIDS Epidemic Model with Treatment Badria Ulfa; Trisilowati Trisilowati; Wuryansari M. K.
The Journal of Experimental Life Science Vol. 8 No. 1 (2018)
Publisher : Postgraduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1284.963 KB) | DOI: 10.21776/ub.jels.2018.008.01.04

Abstract

In this article, an epidemic model of HIV/AIDS with treatment is observed. This model consists of five populations: susceptible, educated susceptible, exposed, HIV infected, and AIDS infected. Antiretroviral therapy (ART) is one type of treatment that can be given to individual that is infected by HIV. This medication can prevent the growth of the virus. Exposed individuals are given short-term antiretroviral treatment called Post Exposure Prophylaxis (PPP), while for infected individuals are given treatment by combining two or three types of antiretroviral drugs. Dynamical analysis is performed by determining equilibrium points and local stability analysis. Based on the analysis results, two equilibrium points are obtained, namely disease-free equilibrium point and endemic equilibrium points. The stability analysis shows that the free equilibrium point is locally asymptotically stable if R0 < 1 and the endemic equilibrium point is locally asymptotically stable under certain conditions. Numerical simulations show that giving two medications together has a greater effect in reducing the spread of the disease. Keywords: antiretroviral, dynamical analysis, HIV/AIDS.
Optimal Control of Cervical Cancer Model with Vaccination and Screening Karunia Theda Kristanti; Trisilowati Trisilowati; Agus Widodo
The Journal of Experimental Life Science Vol. 10 No. 2 (2020)
Publisher : Postgraduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jels.2020.010.02.01

Abstract

In this paper, an optimal control problem of a cervical cancer model with vaccination and screening as controls is discussed. This vaccine can stimulate the immune system to produce antibodies that can prevent the occurrence of human papillomavirus (HPV) infections, while screening is used as secondary prevention of early detection of cervical cancer cells so that treatment can begin immediately. The models were divided into two compartments, females and males. The female's compartment consists of susceptible, vaccinated, infected, screening, cervical cancer, and recovered females. Meanwhile, the male's compartment consists of susceptible, infected, and recovered males. The purpose of this optimal control was to minimize the number of infected females, infected males, and cervical cancer, as well as to minimize the cost of the controls. Optimal control was obtained by using the Pontryagin principle. Furthermore, an optimal control problem was solved numerically using the Forward-Backward Sweep method to determine the effect of vaccination and screening on the model. The results indicate that vaccination and screening as controls are effective in reducing the subpopulation of HPV infection, which can further reduce the occurrence of cervical cancer. Keywords: cervical cancer, vaccination, screening, optimal control
Dynamics of Covid-19 model with public awareness, quarantine, and isolation Risyqaa Syafitri; Trisilowati Trisilowati; Wuryansari Muharini Kusumawinahyu
Jambura Journal of Biomathematics (JJBM) Volume 4, Issue 1: June 2023
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjbm.v4i1.19832

Abstract

This paper presents a new COVID-19 model that contains public awareness, quarantine, and isolation. The model includes eight compartments: susceptible aware (SA), susceptible unaware (SU), exposed (E), asymptomatic infected (A), symptomatic infected (I), recovered (R), quarantined (Q), and isolated (J). The introduction will be shown in the first section, followed by the model simulation. The equilibrium points, basic reproduction number, and stability of the equilibrium points are then determined. The model has two equilibrium points: disease-free equilibrium point and endemic equilibrium point. The next-generation matrix is used to calculate the basic reproduction number R0. The disease-free equilibrium point always exists and is locally stable if R0 1, whereas the endemic equilibrium point exists when R0 1 and is locally stable if satisfying the Routh-Hurwitz criterion. Stability properties of the equilibrium confirmed by numerical simulation also show that quarantine rate and isolation rate have an impact in the transmission of COVID-19
Dynamical Analysis of Fractional-Order Hastings-Powell Food Chain Model with Alternative Food Moh Nurul Huda; Trisilowati Trisilowati; Agus Suryanto
The Journal of Experimental Life Science Vol. 7 No. 1 (2017)
Publisher : Postgraduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1079.224 KB) | DOI: 10.21776/ub.jels.2016.007.01.08

Abstract

In this paper, a fractional-order Hastings-Powell food chain model is discussed. It is assumed that the top-predator population is supported by alternative food. Existence and local stability of equilibrium points of fractional-order system are investigated. Numerical simulations are conducted to illustrate analysis results. The analysis results show that alternative food can give a positive impact for top-predator population.Keywords: Alternative food, Fractional-order, Grunwald-Letnikov approximation, Hasting-Powell model, Stability.
Optimal Control of Tumor Growth Model with Dendritic Cells as Immunotherapy Firmansyah Reskal Motulo; Trisilowati Trisilowati; Abdul Rouf
The Journal of Experimental Life Science Vol. 8 No. 2 (2018)
Publisher : Postgraduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1053.56 KB) | DOI: 10.21776/ub.jels.2018.008.02.06

Abstract

In this paper, optimal control of tumor growth model with dendritic cells as immunotherapy is provided. The model equation can be expressed into a nonlinear differential equation system consisting of four compartments namely, tumor cells, CTL cells, helper T cells, and dendritic cells. Dendritic cells as immunotherapy are injected to the body at time t. The aim of this optimal control is to minimize the tumor cells density as well as the cost of dendritic cells to be administered to the body.Optimal control problem is carried out based on Pontryagin's maximum principle and numerical simulation is solved by using Forward-Backward Sweep methods. Simulation results show that control strategy shrinks tumor cells density which is shown by tumor cells density graph that monotonically decreases after applying dendritic cells as immunotherapy.Keywords: immunotherapy, optimal control, Tumor cell.
Numerical Simulation of Leslie-Gower Predator-Prey Model with Stage-Structure on Predator Rima Anissa Pratiwi; Agus Suryanto; Trisilowati Trisilowati
The Journal of Experimental Life Science Vol. 8 No. 3 (2018)
Publisher : Postgraduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1381.092 KB) | DOI: 10.21776/ub.jels.2018.008.03.011

Abstract

In this paper, we introduce Leslie-Gower predator-prey model with a stage-structure population on the predator. This model consists of two populations, that are prey and predator populations. Here, we divide predator into two stages. Thus, we have three classes of population in this model that are prey, juvenile predator, and mature predator. The focus of this paper is to know the interaction between the population that is affected by stage-structure in predator population in the model and to study numerically the effects of stage-structure in predator population on the interaction of prey and predator. It is found that the transition rate from juvenile to mature predator is a very important parameter which may determine the long-term behavior of both prey and predator.Keywords: Leslie-Gower model, predator-prey model, stage-structure.
Sensitivity and Stability Analysis of a SEIR Epidemic Model with Information Robiatul Witari Wilda; Trisilowati Trisilowati; Moch. Aruman Imron
The Journal of Experimental Life Science Vol. 9 No. 1 (2019)
Publisher : Postgraduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1163.176 KB) | DOI: 10.21776/ub.jels.2019.009.01.08

Abstract

In this paper, the construction and stability analysis of a SEIR epidemic model with information are discussed. This model contains information about how to prevent the spread of infectious diseases which is transmitted by infected individuals to susceptible individuals. Furthermore, the dynamical analysis of the model which includes determination of equilibrium points terms of existence, stability analysis of the equilibrium points and sensitivity analysis are observed. Local stability of the equilibrium point is determined by linearizing the system around the equilibrium point and checking for the eigenvalue sign of Jacobian matrix at each equilibrium point. Sensitivity analysis is performed by using a sensitivity index to measure the relative change of basic reproduction number on each parameter. Based on the analysis result, there are two equilibrium points namely disease-free equilibrium point and endemic equilibrium point. The disease-free equilibrium point always exists and is locally asymptotically stable if the basic reproduction number is less than one. Moreover, the endemic equilibrium point exists and is locally asymptotically stable under certain conditions. From sensitivity analysis, it is found that the rate of mortality is the most sensitive parameter and the least sensitive parameter is the rate of exposed individual becomes infected individual. Finally, numerical simulation is conducted to support the analysis result.Keywords: Epidemic, information, sensitivity analysis, SEIR, stability analysis.
KFCM-PSOTD : An Imputation Technique for Missing Values in Incomplete Data Classification Muhaimin Ilyas; Syaiful Anam; Trisilowati Trisilowati
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 1 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v9i1.25138

Abstract

Data mining is a very important process for finding out the data interpretation. Data preprocessing is the crucial data mining steps. The existence of missing values in the data is one of the primary issues with data preprocessing. Generally, this can be overcome with mean or median imputation because they are easy to implement. However, the use of these techniques is not recommended because they ignore the data variance. This research develops the Kernel Fuzzy C-Means Optimized by the Particle Swarm Optimizer with Two Differential Mutations (KFCM-PSOTD).  KFCM imputation is applied to obtain better estimation values due to its proven ability to recognize patterns in the data. In addition, the PSOTD algorithm is used as an optimization tool to boost the KFCM's performance. PSOTD is adopted because it has more balanced exploration and exploitation capabilities compared to classical PSO. Datasets that have been imputed on KFCM-PSOTD are classified using the Decision Tree algorithm. The results are evaluated using accuracy, precision, recall, and f1 score to determine the quality of the imputed values. The outcomes demonstrate that the KFCM-PSOTD algorithm has a better performance; even the difference in evaluation scores obtained reaches 10% better than other imputation techniques.