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Journal : Formosa Journal of Science and Technology (FJST)

Stability Analysis of Mathematical Models for Controlling the Spread of Pests and Diseases in Shallot Plants (Allium ascalonicum L.) Julius Sihole; Tri Andri Hutapea
Formosa Journal of Science and Technology Vol. 2 No. 1 (2023): January, 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v2i1.2567

Abstract

There is a pest of shallots (Allium ascalonicum L.) with the most common cases being onion caterpillars and purple spot which must be controlled to get good yields. This study aims to determine the properties of the stability of the model by examining the stability analysis by determining the model equation, equilibrium point, basic reproduction number, analysis of the equilibrium point by linearization of the Jacobian matrix to obtain eigenvalues ​​and stability properties. The simulation shows the effect of pesticide treatment using the fourth order Runge-Kutta method and the Matlab program. There are two equilibrium points: (1) Point (E0) free of pests and diseases is stable if R0 < 1. (2) Endemic point (E1) is stable if R0 > 1. The simulation shows that the greater the pesticide treatment, the faster the susceptible population and infected decreased, the faster the recovering population has increased.
Stability Analysis of Mathematical Models of Toxoplasmosis Spread in Cat and Human Populations with Time Delay Novandri Sitinjak; Tri Andri Hutapea
Formosa Journal of Science and Technology Vol. 2 No. 2 (2023): February 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v2i2.2855

Abstract

Toxoplasmosis is caused by the parasite Toxoplasma gondii. In this study, model construction, determining the equilibrium point, stability analysis, and model simulation were carried out. The results showed that there were two equilibrium points, namely the disease-free equilibrium point, locally asymptotically stable if and disease endemic, locally asymptotically stable if. The simulation results show when the solution is stable towards the free equilibrium point, when the solution is stable towards the disease endemic equilibrium point without delay or with time delay. Giving a time delay will cause differences in the population dynamics of each class at the start, but then all solutions move towards a stable point.