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Mikailalsys Journal of Mathematics and Statistics
Published by Lembaga Yasin Alsys
ISSN : 30308399     EISSN : 3030816X     DOI : https://doi.org/10.58578/mjms
Core Subject : Education, Engineering,
Engineering Mathematics Mechanical Engineering
The journal contains scientific articles covering topics such as mathematical theory, statistical methods, the application of mathematics in various disciplines, and statistical data analysis. The primary objective of this journal is to promote a better understanding of mathematical and statistical concepts and to encourage advancements in the methods and applications of mathematics and statistics in various contexts. The journal serves as a platform for researchers, academics, and practitioners to share knowledge and the latest research findings in the fields of mathematics and statistics. MJMS publishes three editions a year in February, June, and October.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 79 Documents
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A Class of One-Sixth Hybrid Methods for Direct Solution of Third Order Ordinary Differential Equations Taiwo, Oluwasayo Esther; Ogunniran, Muideen O.
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5368

Abstract

In this paper, a class of Hybrid methods for solving third order ordinary differential equations directly is developed. These methods were derived using interpolation and collocation techniques. The methods were analyzed based on the properties of linear multistep methods and were found to be zero-stable, consistent and convergent with good region of absolute stability. The proposed methods were implemented on higher order ordinary differential initial value problems. The superirity of the proposed methods over existing ones was demonstrated through some numerical examples.
A Study on Mixture Poisson Autoregressive (P) Model Mutah, Yaska; Abdulkadir, S. S.; Akinrefon, A. A.; Torsen, E.
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5379

Abstract

This research presents and assesses novel models for time series count data called the Mixture Poisson Autoregressive (MPAR) model addresses difficulties of discreteness, overdispersion, and serial correlation. A completely parametric technique was used, and a marginal distribution for the counts was defined. The parameters of the model were estimated using the Expectation Maximization method, through extensive Monte Carlo simulations, the stability of the estimates of the MPAR was evaluated and the results clearly revealed that the model was stable as the estimated parameters were converging to the values of the true parameters as the sample gets larger. Also, the results from the simulations revealed that the MPAR model outperform other count data models thus, Poisson distribution, Poisson Autoregressive (PAR) and Poisson Exponentially Weighted Moving Average (PEWMA).
A Model of the Spread of Chlamydia Trachomatis Michael, Ajao Olutunde; Adebowale, Adejumo O.
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5462

Abstract

Chlamydia as sexually transmitted disease that has major occurrence in sub-Saharan African where Nigeria is predominant this create a necessity to be concern about its spread within the nation.The SEScITR model with six compartments (Susceptible, Exposed, Screened, Infectious, Treated, Recovered) of human population was formulated. The parameters in the model were obtained from literatures and some were assumed. The ordinary differential equations were obtained using Runge Kutta Fehlberg Method and analysis of our system of equations was done using Maple 2017. Simulated data obtained through RStudio were used and our analysis were done using deSolve package on Rstudio. The formulated model was further analyse to get the reproduction number which is 0.67. The local and global stability ofSEScITR modelwas investigated using Jacobian matrix and Lyapunov function respectively and the results shows that Chlamydia disease free equilibrium is locally and globally asymptotically since R0<1 i.e.R0 =0.67. Also, the endemic state of Chlamydia equilibrium is locally and globally stable when R0>1.
On the Efficiency of a One-Fifth Step Hybrid Block Method for the Numerical Solution of Second-Order Ordinary Differential Equations Taiwo, Oluwasayo Esther
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5497

Abstract

In this paper, hybrid methods for solving second-order ordinary differential equations with a one-fourth step length were developed. This was accomplished using interpolation and collocation techniques. The methods were evaluated based on the properties of linear multistep methods and were found to be zero-stable, consistent, and convergent, exhibiting a favorable region of absolute stability. The proposed methods were implemented for second-order ordinary differential initial value problems. The performance of the new methods demonstrated superiority over previously developed methods in the literature, as evidenced by the resolution of five numerical examples. The results were presented in tabular form.
Mathematical Modeling of HIV Investigating the Effect of Inconsistent Treatment with Saturated Incidence Function Odebiyi, O. A.; O, Salahu W.; Oladejo, J. K.; Olabisi, O. O
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5570

Abstract

The Human Immunodeficiency Virus (HIV) remains a significant global health challenge, with millions of people worldwide living with the virus. Despite advances in treatment and prevention, the disease continues to spread, underscoring the need for a deeper understanding of its transmission dynamics. This study presents a mathematical model of HIV transmission dynamics, incorporating a saturation term to capture the complex interactions among susceptible, infected, AIDS, and treated populations. The validity of the solution confirms that the model is well-defined and holds epidemiological significance. The basic reproduction number is obtained using the next-generation matrix approach. To assess the stability of the model, we conducted a thorough analysis of the local and global stability of both the disease-free and endemic equilibria. This analysis provides a comprehensive understanding of the model’s behavior, illuminating the conditions necessary for the disease to persist or die out. A sensitivity analysis is conducted to identify key parameters influencing the model’s behavior. Numerical simulations are then performed to further explore the dynamics of the system. Our results highlight the importance of targeted interventions to control the spread of the disease, thereby informing public health policy and intervention strategies.
Solution of System of Volterra Integral Equations Using the Complex Sadiq Emad Eman Integral Transform T., Ezra E.; J., Ankale H.; Y., Hali I.
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5716

Abstract

Various analytical methods have been developed for solving systems of Volterra integral equations of both the first and second kind. In this study, we adopt and apply the complex Sadiq Eman Emad (SEE) integral transform as a novel approach for obtaining solutions to such systems. The complex SEE transform provides an effective framework for simplifying and solving integral equations through the use of operational techniques. This research explores the theoretical formulation of the transform, its properties including convolution and inverse operations and demonstrates its application through illustrative examples. The results confirm that the complex SEE integral transform offers a practical and efficient alternative for solving systems of Volterra integral equations, highlighting its potential for broader use in mathematical and engineering problems involving integral operators.
Fixed Point Theorems of Ćirić-Type Contraction Chiroma, Rhonda; Tanto, Ezra Emmanuel
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5756

Abstract

This paper introduces a novel class of Ćiríc-type contraction operators within the framework of complete metric-like spaces. The study establishes sufficient conditions under which fixed points exist for such mappings, expanding the theoretical foundation of fixed point theory. A carefully constructed, non-trivial comparative example is provided to illustrate the broader applicability and generality of the main result. Furthermore, several corollaries are derived, demonstrating that the proposed theorem not only encompasses but also unifies numerous existing fixed point theorems associated with Ćiríc-type contractions. The findings contribute to a deeper understanding of generalized contractive mappings and offer potential applications in related mathematical and applied contexts.
Effect of Money Supply on Stock Market Development in Nigeria (1985–2023) Stephen, Mathew; Akobi, Clement; Idi, Danjuma; Yusuf, Shadrach
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5883

Abstract

This study investigates the impact of money supply on stock market development in Nigeria over the period 1985 to 2023, with a focus on assessing the differential effects of monetary aggregates and policy rate dynamics. Using annual time-series data obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin, the analysis models stock market development proxied by total annual market capitalization as a function of narrow money supply (M1), broad money supply (M2), and the monetary policy rate (MPR). Multiple regression analysis was employed to test the formulated hypotheses, with standard diagnostic tests confirming the validity of the model, including the absence of multicollinearity and the normal distribution of residuals. Results reveal a statistically significant negative relationship between the monetary policy rate and stock market development (p < 0.05), suggesting that higher interest rates hinder capital market performance. In contrast, neither M1 nor M2 exhibited statistically significant effects (p > 0.05), indicating a limited influence of money supply aggregates on stock market growth within the observed period. These findings imply that interest rate adjustments remain a critical monetary policy tool in shaping investor behavior and capital market performance. The study recommends that policymakers prioritize interest rate management within a coherent monetary policy framework to foster a conducive environment for capital market development and broader economic growth.
Graph-Theoretic Characterization of Quasi-Nilpotent Elements in Finite Semigroups of Full Order-Preserving Transformations C., Eze; O., Olaiya O.; Kasim, S.
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5906

Abstract

This paper investigates the structural behavior of quasi-nilpotent elements within the semigroup On of all full order-preserving transformations on a finite chain Xn = {1, 2, . . ., n}. While quasi-nilpotency has been extensively studied in full and partial transformation semigroups, its characterization in On remains largely unexplored. By employing a graph-theoretic approach, we associate to each transformation α ∈ On a digraph Γ(α) and establish necessary and sufficient conditions under which α is quasi-nilpotent. Specifically, we show that α is quasi-nilpotent if and only if Γ(α) has a unique sink and all vertices are connected to it via directed paths. This char- acterization is further refined by relating the height of Γ(α) to the number of convex blocks in the domain partition of α. Illustrative examples and explicit constructions are provided to validate the theoretical findings. The results offer new insights into the interplay between algebraic properties of transformation semigroups and their combi- natorial representations.
Modeling Stock Data Using Multiple Linear Regression and LASSO Regression Analysis Daniel, Adashu Jacob; Ibrahim, Musa Dahiru; Josaphat, Anule Aondulum
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 2 (2025): Mikailalsys Journal of Mathematics and Statistics
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/mjms.v3i2.5927

Abstract

This study evaluates and compares the model fitting and predictive performance of Multiple Linear Regression (MLR) and Least Absolute Shrinkage and Selection Operator (LASSO) regression in the context of stock price prediction for four leading Nigerian companies. A dataset comprising 1,300 observations from 2019 to 2025 was obtained from Yahoo Finance and Investing.com. Multicollinearity assessment using the Variance Inflation Factor (VIF) revealed substantial collinearity among certain predictors, particularly for the variables "Open" (Honeywell: 55.45; Zenith: 920.30) and "Low" (Oando: 621.81), indicating the need for variable selection or dimensionality reduction. Comparative analysis based on model selection criteria, including Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) demonstrated the superior performance of LASSO over MLR across all companies. For example, Honeywell's LASSO model recorded an AIC of –12,112.64 and an MSE of 0.000021, compared to MLR's AIC of –2,690.54 and MSE of 0.00998. LASSO regression also identified key predictors such as "High" price, which exhibited strong statistical significance for Oando (z = 18.991, p < 0.001) and Zenith (z = 7.066, p < 0.001), whereas trading volume generally showed weak predictive power. The study concludes that LASSO provides a more parsimonious and accurate predictive model for financial time-series data. It is recommended for use in financial forecasting and investment analysis, particularly when dealing with multicollinear datasets and high-dimensional predictor variables.

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