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Hasan S Panigoro
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Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Negeri Gorontalo, Jl. Prof. Dr. Ing. B. J. Habibie, Moutong, Tilongkabila, Kabupaten Bone Bolango 96554, Gorontalo, Indonesia
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Jambura Journal of Biomathematics (JJBM)
Published by Universitas Negeri Gorontalo
ISSN : -     EISSN : 27230317     DOI : https://doi.org/10.37905/jjbm
Core Subject : Health, Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Public Health
The Jambura Journal of Biomathematics JJBM is a peer reviewed academic journal published by the Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Indonesia. The journal is established with the vision of becoming a leading scientific publication in Southeast Asia and serves as a platform for researchers, academicians, and practitioners to publish original research articles and review papers. JJBM focuses on explaining complex biological phenomena through mathematical approaches and acts as a bridge between theoretical mathematics and the life sciences. JJBM has a broad and interdisciplinary scope covering various research areas. The journal welcomes high quality submissions involving mathematical analysis, computational modeling, and statistical methods to generate biological insights. The main areas include population dynamics, evolutionary dynamics, epidemiology, infectious disease modeling, systems biology, ecological modeling, and optimal control in biological systems. Through this scope, JJBM aims to support innovation in both mathematics and biological applications. To ensure scientific quality and originality, every submitted manuscript undergoes a single blind peer review process by experts in the field. The journal applies a strict policy against plagiarism and uses tools such as Turnitin to ensure originality. All accepted manuscripts are required to be prepared using LaTeX to maintain consistency and quality in mathematical formatting. JJBM is published quarterly in March, June, September, and December. The journal follows an open access policy, allowing all published articles to be freely accessed by the public. This approach supports wider dissemination of knowledge and increases the visibility and impact of published research. JJBM is committed to publication ethics and accessibility. The journal follows the guidelines of the Committee on Publication Ethics COPE. To support inclusivity, JJBM provides waiver options for article processing charges for authors from low and lower middle income countries.
Arjuna Subject : Matematika - Matematika Terapan
Articles 10 Documents
 1 
Search results for , issue "vol. 7 no. 2: june 2026" : 10 Documents clear
Numerical Analysis of a Caputo Fractional-Order SEIR Model for COVID-19 Using Hermite Polynomial Collocation and Laplace-Adomian Decomposition Methods Bosede Abubakre; Morufu Olayiwola; Ajimot Adebisi
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.58

Abstract

The rapid transmission of COVID-19 is a vital threat to the health systems of various countries, and the need to receive the correct mathematical models to implement control measures. This paper provides a numerical analysis of an exposed compartment Caputo fractional-order SEIR model with an incubation period of SARS-CoV-2 variants. The model is nonlinear and difficult to solve analytically, so there are no precise solutions. Two methods Hermite Collocation Method (HCM) and Laplace-Adomian Decomposition Method (LADM) are used. The system is turned into nonlinear algebraic equations by HCM through Hermite polynomial expansions whereas LADM uses Laplace transforms and Adomian polys to deal with nonlinearities. Simulations of the Maple indicate that the two methods can effectively estimate the dynamics of the fractional SEIR, although HCM is more accurate and converges more quickly. Fractional-order formulation also includes the effects of memory in the transmission of the disease. This evidence proves that the application of fractional-order modeling with Hermite based numerical methods provides a strong platform through which the dynamics, especially the epidemiological ones, may be analyzed and the adaptive public health responses may be directed.
Dimensional Analysis of the Bergman Minimal Model for Glucose-Insulin Dynamics in Normal and Diabetic Individuals Norazaliza Jamil; Chai Jian Tay
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.59

Abstract

The Bergman minimal model is commonly utilized to model glucose-insulin dynamics. However, the dimensional analysis of this model is somewhat limited. Dimensional analysis is an essential mathematical tool in fields such as engineering, physics, and applied sciences. Its main purposes include simplifying mathematical models, improving scalability and generalization, identifying key influencing factors, and enhancing computational efficiency. This study aimed to conduct a formal dimensional analysis of the Bergman minimal model, investigate the dimensionless model, simulate it, and investigate the dynamic of glucose-insulin to compare a normal and diabetic individual. The Bergman minimal model was transformed into a dimensionless format by reexpressing all state variables and parameters regarding their reference scales. The dimensionless model was solved and simulated using the fourth-order Runge-Kutta (RK4) numerical method, implemented in MATLAB software, to generate the dynamics of glucose and insulin in individuals with normal and diabetic conditions. In the dimensionless formulation, the number of parameters is reduced from eight to five and five new composite parameters are revealed, such as glucose clearance rate, insulin sensitivity, the rate of insulin degradation, insulin release response and basal glucose level. Results reveal that glucose levels decrease efficiently in normal individuals, while diabetic patients experience a slow decline in glucose level, not normalize (not return to 1 dimensionless) after a meal. A simulation study for the case where no insulin production occurs in response to glucose reveals that the glucose level increases over time rather than decreases, with no sign of stabilization. Hence, without insulin, cells cannot take up glucose, leading to uncontrolled blood sugar accumulation. These findings underscore the role of dimensional analysis in streamlining the Bergman model; it simplified the governing equations, enabling the direct identification of key composite factors and resulting in a more computationally efficient simulation framework for characterizing glucose metabolic control.
Optimal Diabetic Therapy Selection under Uncertainty: A Sinusoidal Pythagorean Fuzzy MOORA and TOPSIS Approach Vishalakshi Kuppusamy; Prasantha Dhandapani; Kalarani Murugesan; Kavitha Arumugam; Hasan Panigoro; Rebecca Nalule
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.60

Abstract

Sinusoidal waves are fundamental to the analysis and synthesis of signals in engineering, physics, and applied sciences. Their periodic nature and mathematical simplicity make them essential in modelling oscillations, communication signals, and even artificial intelligence systems where signal patterns matter. In this paper, we introduce a new class of sinusoidal Pythagorean fuzzy set. We define a sinusoidal Pythagorean fuzzy average aggregation operator and discuss its properties. This operator is then applied in decision-making problems using sinusoidal Pythagorean fuzzy CRITIC method, sinusoidal Pythagorean fuzzy MOORA method, and sinusoidal Pythagorean fuzzy TOPSIS method for optimal diabetic therapy selection under uncertain clinical judgements.
Performance Evaluation of Classical and Deep Learning Methods in Diabetes Prediction Buğçe Tatlıcıoğlu
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.62

Abstract

This study presents a comparative evaluation of three approaches for forecasting a diabetes complications dynamical model: the classical fourth-order Runge–Kutta method (RK4), the multiplicative Runge–Kutta method (MRK4), and a Multilayer Perceptron (MLP) trained as a surrogate predictor. RK4 and MRK4 are used to numerically simulate the model, while the MLP is trained on trajectories generated by MRK4. Performance is assessed using mean squared error (MSE), root mean squared error (RMSE), and mean absolute percentage error (MAPE). The results highlight the advantages and limitations of each approach in capturing the model dynamics and provide guidance on when numerical solvers or learning-based surrogates may be preferable in diabetes modeling.
The Numerical Simulations of Ligand Diffusion Towards Invadopodia Formation Hanis Nasir; Mohd Rashid Admon; Suzarina Sukri; Mohd Ariff Admon; Sharidan Shafie; Noorehan Yaacob
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.66

Abstract

Metastasis refers to the spread of a primary tumor to a different location through the invasion of nearby tissues or organs. This process is aided by the formation of invadopodia, a subcellular structure. Invadopodia are formed through a biological process that involves ligands, signals, receptors, actin, extracellular matrix (ECM), and matrix metalloproteinases (MMPs). In the literature, several studies of the invadopodia model have considered the ligand and signal in their mathematical model. However, for most of the work done, the diffusion rate of the ligands is not considered. Hence, this study aimed to explore the ligand diffusion rate to investigate the influence of the diffusion rate on the behavior of the invadopodia. Since invadopodia are formed as a result of the movement of the plasma membrane, the zero-level set method is applied to detect the movement. In addition, the invadopodia model is solved numerically using a finite difference coupled with the ghost fluid with a linear extrapolation approach for regular and neighboring points, respectively. In this research, different rates of ligand diffusion are applied, and the profiles of the ligand and interface (plasma membrane) are analyzed. The results show that the diffusion rate of the ligand can influence the availability of the invadopodia on the plasma membrane.
Modeling the Impact of Awareness and Environmental Sanitation on Typhoid Fever Transmission Olumuyiwa James Peter; Sharifah Ahmad; Janet O. Agbaje; Festus Abiodun Oguntolu; Zainab Olabisi Dere; Olasubomi Abdulateef Bakare; Dipo Aldila
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.21

Abstract

Typhoid fever has been a significant burden even now in many poorer countries, mainly because of poor sanitation, contaminated water supplies, and the steady steady stream of asymptotic carriers who incessantly contaminate the environment. In this paper, we propose and analyze a compartmental model incorporating these aspects along with awareness-induced behavioral changes. The model has compartments for the susceptible population, the carriers, the infectious population who show symptoms, those who have recovered from the disease, a separate compartmenting the quantity of Salmonella Typhi in the environment. The infection spreads largely because of the intake of contaminated food and water. It adopts a nonlinear saturation incidence function describing the reduced possibility of infection with elevated contact rates. An awareness factor diminishes the probability of infection. It determines the basic reproduction number. It also demonstrates the disease-free equilibrium being globally stable. A locally stable endemic equilibrium has also been determined. A PRCC analysis has identified awareness, sanitation standards, the strength of infection transfer, and the bacterial shedding rates as the dominating parameters influencing the dynamics. Numerical examples validate the above theoretical studies. It has been observed that increased awareness along with improved sanitation practices substantially reduce the extent of the spread of the disease. Most importantly, the combined effects of behavioral modification along with enhanced sanitation practices have the potentially most profound effects on the reduction of the extent of the disease.
Qualitative Dynamics and Hopf Bifurcation in a Hepatitis B Delay Model with Immune Interaction Sireesha Devi; Ranjith Kumar
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.85

Abstract

In this research, we build a three-compartment delay differential equation (DDE) model to examine the intra host dynamics of Hepatitis B Virus (HBV) infection. The model includes a biologically based intracellular delay that represents the eclipse phase of infection and a non monotone saturation incidence function that shows how the immune system controls infection dynamics. The suggested formulation takes into account saturation effects that come from immune depletion and limited cellular resources. This is different from standard HBV models that assume bilinear or simple saturation incidence rates. The system is made up of healthy hepatocytes, contaminated hepatocytes, and immune cells that kill cells. The fundamental reproduction number ${{R}_{0}}$, is calculated and used to find the minimum level of infection that has to be present for it to continue. To study the local stability of the equilibria, we linearize the system and get the transcendental characteristic equation that goes with it. Hopf bifurcation study concerning the delay parameter $\tau $ indicates the presence of crucial delay values that distinguish stable steady states from oscillatory dynamics. Sensitivity analysis shows that parameters linked to transmission have the biggest effect on the fundamental reproduction number ${{R}_{0}}$, while characteristics related to delay mostly affect the system's stability and the appearance of oscillatory dynamics. Numerical simulations, encompassing time-series graphs and bifurcation diagrams, demonstrate that elevating the delay over a crucial threshold can trigger persistent oscillations in infected and immune cell populations, mirroring the recurring fluctuations seen in chronic HBV infection. These findings underscore the significant influence of intracellular delay and immune-regulated infection mechanisms on the long-term dynamics of HBV, offering a theoretical foundation for the advancement of HBV infection models.
Numerical Analysis of Threats to Rice Production Due to Excess Use of Chemical Fertilizers Uzzwal Mallick; Pulak Kundu
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.86

Abstract

Rice production, an essential source of nutrition, is vital for food security and rural livelihoods. With a rapidly growing population and limited arable land, it increasingly depends on chemical fertilizers. Overuse of these fertilizers can threaten long-term sustainability. To address this issue, a field experiment was conducted using four distinct fertilizer management strategies. By fitting parameter values to the experimental data, a new nonlinear model has been proposed to analytically and numerically investigate the effects of chemical fertilizer use in rice cultivation. The analytical framework includes the examination of the existence, uniqueness, and stability of equilibrium points using the Jacobian matrix, along with sensitivity analysis to identify the parameters that most significantly influence system behavior. Results from both field experiments and simulations showed that a 40\% chemical fertilizer combined with 60\% organic fertilizer resulted in the highest soil nutrient content and rice yield. Organic inputs improve soil fertility through decomposition of plant residues, but excessive use can increase soil salinity, harming rice growth. Therefore, this study recommends that fertilizers should be applied in an efficient and balanced manner to maximize crop production while maintaining long-term soil fertility, and the developed model can serve as a practical and cost-effective tool for predicting field fertility, thereby reducing the need for conducting new field experiments.
Mathematical Analysis Of The Two-Patch SIRS-SIW Model For The Dynamical Transmission Of Dengue Fever Involving Wolbachia Fitriana Saptaningtyas; Fugo Takasu; Hartono; Fithri Lathifah; Ikha Parwitasari
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.87

Abstract

A promising, biologically safe approach to controlling dengue hemorrhagic fever (DHF) is the release of Wolbachia-infected mosquitoes. The use of mathematical modelling to identify optimal control strategies has been the focus of numerous studies. However, the dynamics of human movement between areas where Wolbachia is applied and areas where it is not remain poorly understood. In this study, the spread of dengue fever is examined through a two-patch autonomous ordinary differential equation system encompassing two human population patches, along with Aedes aegypti mosquitoes and Wolbachia, to characterise the dynamics of dengue transmission between humans interacting from two separate patches, alongside the mosquito populations. The Wolbachia strategy has been implemented in portions of the DIY region. We use a two-patch framework to model this issue. We propose developing a mathematical model to investigate the relationship between mosquito bite rates and the proportion of Wolbachia mosquitoes, while accounting for temporary population movements between spatially distinct patches. We assume that the human population is divided into two distinct patches: one in an area where Wolbachia has been implemented and the other in an area where it has not, with a temporary visit between the patches. We compute the local and global stability criteria for the disease-free equilibrium and the basic reproduction number for each patch. In addition, we conducted a thorough analysis of the key parameters related to the proportion of Wolbachia mosquitoes that affect the stability of this equilibrium point. These parameters may serve as vital references to aid in eradicating dengue hemorrhagic fever (DHF) within each patch. Our findings demonstrate that increasing the number of Wolbachia strains significantly limits the spread of dengue in Yogyakarta. The spread of dengue fever can be suppressed by targeting at least 69.9\% of Wolbachia mosquitoes from the total mosquito population.
Modeling Tuberculosis Transmission and Control Using Game Theory and Optimal Strategies Incorporating Migration Flow Dynamics Md. Abu Salek; Mehmet Yavuz; Md. Humayun Kabir; Jannatun Nayeem; Muhammad Hossain; Md. Fayz-Al-Asad
Jambura Journal of Biomathematics (JJBM) Vol. 7 No. 2: June 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v7i2.88

Abstract

A Tuberculosis (TB) transmission model,which optimizes the control strategy with migration dynamics utilizing evolutionary game theory, has been introduced in this work. Besides, the population dynamics is categorized into susceptible, vaccinated, migratory, exposed, infectious, treated, and recovered individuals, while three dynamic controls,distancing, vaccination, and treatment,modulate the spread of disease. Each control measure is considered within the range of 0 to 1 for the governing parameters,namely, migration rate ($\lambda$), treatment rate ($\gamma$), recovery rate ($\delta$) and transmission rate ($\beta$).This study develops a migration-integrated tuberculosis transmission model incorporating susceptible, vaccinated, migratory, exposed, infectious, treated, and recovered populations. Three intervention strategies, namely distancing, vaccination, and treatment, are included to examine their effects on TB transmission. The basic reproduction number is derived, and the positivity and boundedness of the model are established. Numerical simulations are performed using an Adams–Bashforth–Moulton predictor–corrector method. A formal evolutionary game-theoretic framework is introduced through payoff functions and replicator dynamics to evaluate the behavioral preference among the control strategies. The results indicate that treatment produces the strongest reduction in infection prevalence when applied as a single control, while combined strategies provide stronger epidemic suppression when sufficient resources are available. Cost-effectiveness analysis is used to compare the economic efficiency of the intervention strategies. The findings highlight the importance of incorporating migration and behavioral responses into tuberculosis control planning.

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