cover
Contact Name
Suresh Kumar Sahani
Contact Email
mjms@yasin-alsys.org
Phone
-
Journal Mail Official
office@yasin-alsys.org
Editorial Address
Jalan Lingkok Pandan No 208 Kwang Datuk, Desa Selebung Ketangga, Kec. Keruak, kab. Lombok Timur, Prov. Nusa Tenggara Barat, Indonesia
Location
Kab. lombok timur,
Nusa tenggara barat
INDONESIA
Mikailalsys Journal of Mathematics and Statistics
Published by Lembaga Yasin Alsys
ISSN : 30308399     EISSN : 3030816X     DOI : https://doi.org/10.58578/mjms
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.
Articles 79 Documents
Risk Factors Associated with Mother-to-Child HIV Transmission in Wukari Local Government Areas (LGAs), Taraba State Bature, Gambo Innga
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.6704

Abstract

Mother-to-child transmission (MTCT) of HIV continues to pose a major public health concern in Nigeria, particularly in sub-Saharan Africa. This study investigated the factors influencing MTCT of HIV in Wukari Local Government, Taraba State, using secondary data from 550 nursing mothers attending the General Hospital. A cross-sectional design was adopted, with chi-square tests used to assess associations between MTCT and maternal characteristics, while binary logistic regression identified predictors of transmission. The MTCT rate was 11.5% (63/550). Chi-square analysis revealed significant associations with maternal age (χ² = 8.181, p = 0.017), mode of delivery (χ² = 68.469, p < 0.001), maternal education (χ² = 12.729, p = 0.005), and antenatal care (ANC) visits (χ² = 36.672, p < 0.001). Logistic regression showed that mothers aged 25–35 years (OR = 3.299) and above 35 years (OR = 3.930) had higher odds of transmission than those under 25. Caesarean delivery markedly increased transmission risk (OR = 15.964), while ANC visits were unexpectedly associated with higher odds (OR = 12.851). Higher maternal weight appeared protective (OR = 0.951). The findings demonstrate that maternal age, delivery mode, and ANC patterns are significant determinants of MTCT of HIV. Targeted interventions are needed for older mothers and to strengthen prevention strategies, particularly in the context of caesarean deliveries, to reduce transmission rates and improve maternal–child health outcomes.
The Impact of Religion and Ideology on Country’s Economic Growth: A Case Study of Wukari Local Government Area, Taraba State Wilson, Clement; N, Okeke E.; Akobi, Clement
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.6809

Abstract

This study examines the influence of religion and ideology on economic growth in Wukari Local Government Area of Taraba State, Nigeria. Recognizing that religious beliefs and ideological values shape social cohesion, governance, and individual behavior, the research investigates how these factors contribute to local economic dynamics. A multi-stage cluster sampling technique was used to select ninety respondents across nine villages, representing Christianity, Islam, and African Traditional Religion. Data were collected through structured questionnaires and analyzed using descriptive statistics and multinomial logistic regression. The findings reveal that religious teachings and ideological orientations significantly shape economic behavior and perceptions of development. Specifically, religion promotes ethical values, work discipline, and social capital, generating both direct and indirect effects on economic growth. The regression model confirmed a statistically significant relationship between religious ideology and perceived economic advancement. However, the influence of religion can either facilitate or hinder economic progress, depending on how it is interpreted and applied. The study concludes that integrating religious values into economic planning in a balanced way can strengthen development outcomes. It recommends that policymakers and religious leaders foster inclusive, growth-oriented interpretations of faith and ideology to enhance sustainable economic development in the region.
Contemporary Didactic Methodologies in the Teaching of Mathematics in Higher Education: A Systematic Literature Review (2020–2025) Gómez-García, Brayan
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.7137

Abstract

This study analyzes contemporary didactic methodologies applied to the teaching of mathematics in higher education within the Spanish-speaking context. Using a systematic literature review, peer-reviewed studies published between 2020 and 2025 were identified and assessed, focusing on innovative approaches such as problem-based learning, cooperative learning, gamification, flipped classroom, AI-supported instruction, and socio-emotional education. Strict inclusion criteria were applied to ensure quality, considering only full-text articles written in Spanish. The findings indicate that active methodologies significantly improve student motivation, critical thinking, autonomy, and conceptual understanding of mathematics. The incorporation of technological tools, including Python and AI-based platforms, enhances personalized learning, while socio-emotional strategies help reduce math anxiety and strengthen interpersonal competencies. Nonetheless, challenges remain, including the digital divide, resistance to pedagogical change, and the need for specialized teacher training. The study concludes that the convergence of active strategies, emerging technologies, and humanistic approaches offers a transformative opportunity for mathematics education in higher education. Realizing this potential requires supportive educational policies that promote equitable resource access, continuous professional development, and curricular adaptation aligned with 21st-century demands. Further longitudinal and context-specific studies are recommended to assess the long-term effectiveness of these methodologies.
Quantitative Assessment of Interest Rate Fluctuation Sensitivity in Nigerian Insurance Asset-Liability Management Adewale, Taiwo Abiodun; Tinuoye, Oladipo Abiodun; Adebayo, Ajala Olusegun; Oluwaseyi, Olaiya Olumide; Olalekan, Owoade Olusegun; Damilare, Olaleye Peter
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.7182

Abstract

This study investigates the sensitivity of insurance portfolios to interest rate fluctuations in Nigerian insurance companies, with particular focus on the implications for asset and liability valuation. The objective is to assess how interest rate variability affects the relative sensitivities of assets and liabilities, and the resulting solvency risks. A quantitative approach was adopted, using a sample of ten insurance companies selected based on asset base and data availability. Data covering a ten-year period (2013–2023) were obtained from published financial statements and Central Bank of Nigeria interest rate bulletins. Analytical techniques included stochastic simulations and regression modeling, applying the Vasicek and Heston frameworks, with visualization performed using Python 3.12.3. The results show that liabilities exhibit greater sensitivity to interest rate fluctuations than assets, with pronounced volatility under stress scenarios, thereby creating significant solvency challenges. These findings validate the importance of dynamic stochastic models in capturing the complexities of interest rate effects, as opposed to static mathematical assumptions. The study concludes that effective asset–liability management (ALM) requires robust dynamic interest rate modeling. Theoretical contributions include extending the application of stochastic differential equations to emerging market contexts, while practical recommendations urge insurance regulators and investment managers to adopt interest rate-sensitive frameworks for risk management and capital adequacy assessments. Future research is recommended on macroeconomic stress factors and stochastic volatility models tailored to African financial markets.
An Improved Black–Scholes Model to Determine the Optimal Boundary of Asset–Liability Akintayo, Olajide Olatunbosun; Tinuoye, Oladipo Abiodun; Adebayo, Ajala Olusegun; Oluwaseyi, Olaiya Olumide
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.7218

Abstract

The study addresses limitations of the Black–Scholes framework, specifically its reliance on a risk-neutral market and a self-financing hedging portfolio by proposing a generalized derivative pricing approach grounded in the efficient markets hypothesis. The research objective is to establish a valuation model in which a derivative’s fair value equals a conditional expectation discounted at the underlying asset’s drift, thereby explicitly retaining the asset’s drift rather than abstracting it away under risk neutrality. Methodologically, the paper develops a partial differential equation (PDE) that replaces the risk-free rate with an efficiency-consistent discount rate, derives a pricing formula for European call options that incorporates the underlying’s drift, and analyzes the optimal exercise boundary for American call options under varying parameters. Key findings show that the optimal exercise price increases with higher volatility and risk-free interest rates and decreases with higher dividend yield; moreover, it is never optimal to exercise an American call option early when the underlying pays no dividends. The study concludes that an efficiency-based discounting scheme offers a coherent alternative to risk-neutral valuation while preserving internal consistency with observed market dynamics. The contribution and implication are a drift-inclusive theoretical framework that refines PDE-based pricing, clarifies comparative statics for exercise policy, and provides practitioners with guidance for pricing and exercise decisions in settings where asset drift is informationally relevant.
On the Generalized Ulam–Hyers Stability for Caputo Fractional Derivatives with Nonlocal Conditions Ante, Jackson Efiong; Francis, Runyi Emmanuel; Essang, Samuel Okon; Aigberemhon, Ede Moses; Adamu, Samuel; Ogar-Abang, Michael; Okeke, Stephen Ikenna
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.7258

Abstract

This paper addresses the need for rigorous stability criteria in fractional integro-differential systems by investigating generalized Ulam–Hyers stability for equations involving a fractional-order derivative. The research objective is to establish sufficient conditions that guarantee generalized Ulam–Hyers stability for Caputo fractional differential equations. Methodologically, the study employs concise mathematical arguments together with an application of the Gronwall inequality to derive the required conditions. The key findings demonstrate that these conditions ensure stability in the generalized Ulam–Hyers sense for the considered class of equations. The paper concludes that the obtained results extend and improve upon existing findings in the literature. The contribution lies in refining the stability theory for fractional-order models by providing tractable criteria grounded in Gronwall-type estimates and Caputo derivatives.
A Short Note on: Optimal Control in Matching Pennies Game Habibi, Reza
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.7336

Abstract

This short note explores the application of optimal control theory in identifying mixed equilibrium strategies within the context of the Matching Pennies game. The study emphasizes the role of gradient descent as a fundamental mechanism in the players' learning dynamics. By formulating the game as an optimal control problem, the approach enables systematic analysis of strategic adaptation over time. In addition to the theoretical framework, simulation results are presented to illustrate and validate the effectiveness of the method in converging toward mixed equilibrium. The findings highlight the potential of control-theoretic techniques in advancing game-theoretic learning models.
Experimental Validation of Fractionalized Maxwell Fluid Model of MHD Blood Flow through Bifurcated Arteries for Tumor Treatments Abdulhamid, Mohammed Gazali; Mohammed, Abubakar; Abdullahi, Isah; Usman, Nafisatu
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.7338

Abstract

This study provides an experimental validation of a fractionalized Maxwell fluid model to describe magnetohydrodynamic (MHD) blood flow in bifurcated arteries, with targeted applications in tumor therapy. By incorporating fractional calculus, the model captures viscoelastic memory effects that account for key non-Newtonian properties of blood, including shear-thinning behavior, elastic recovery, and time-dependent stress relaxation under combined electromagnetic and thermal influences. The Homotopy Perturbation Method (HPM) was employed to derive approximate analytical solutions for the governing equations, and the model’s predictions were benchmarked against existing theoretical and experimental data. Numerical simulations indicate that the fractional Maxwell model outperforms classical models in predicting velocity profiles, thermal distributions during hyperthermia treatment, and nanoparticle concentration relevant to drug delivery. The model consistently yields lower mean square errors, demonstrating enhanced accuracy and robustness. These results validate the efficacy of fractional-order modeling in hemodynamic simulations and underscore its clinical potential in improving hyperthermia-based cancer therapies and nanoparticle-mediated drug delivery strategies in complex arterial geometries.
Advances in Bayesian Approaches for Stochastic Process Modeling and Uncertainty Quantification Weng Nyam, Peter; Bishir, A.; Mukhtar, Ummi; Gali, Abubakar Muhammad; Moses, Nyango Yusuf
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.7429

Abstract

Stochastic processes serve as foundational models for systems characterized by random evolution across time or space, making them essential tools in disciplines such as finance, physics, epidemiology, and environmental science. Traditional statistical methods often yield only point estimates of model parameters, limiting their capacity to capture the full scope of uncertainty inherent in such systems. In contrast, Bayesian inference offers a rigorous and comprehensive probabilistic framework by treating both parameters and stochastic processes as random variables. This approach enables the integration of prior knowledge and yields posterior distributions that encapsulate uncertainty more fully. This paper presents a comprehensive survey of Bayesian inference as applied to stochastic processes. It begins by outlining the theoretical foundations of Bayes' Theorem in this context, emphasizing the importance of prior specification for infinite-dimensional function spaces. The discussion then turns to key classes of stochastic processes—including Gaussian Processes, Markov Models, and State-Space Models—highlighting how Bayesian methods enhance their interpretability and predictive capacity. Given the complexity of posterior distributions in these models, the paper also reviews modern computational techniques such as Markov Chain Monte Carlo (MCMC) and Variational Inference (VI) that enable practical implementation. Applications across multiple domains are explored to demonstrate the flexibility and power of the Bayesian approach. The study concludes by identifying emerging challenges and outlining promising directions for future research in Bayesian inference for stochastic systems.
Multivariate Approaches to Neonatal Assessment of Newborn Babies Garba, B. A.; Baba, A. M.; Adamu, M. Y.
Mikailalsys Journal of Mathematics and Statistics Vol 3 No 3 (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.v3i3.7453

Abstract

This study examines gender-based differences in neonatal physical characteristics using multivariate statistical techniques. A total of 1,000 newborns (male and female) were sampled from the Federal University Wukari Teaching Hospital, Taraba State, Nigeria. Key anthropometric variables measured included occipito-frontal circumference (OFC), cranial circumference (CC), length of birth (LOB), abdominal circumference (AC), and weight (WT). Due to perfect correlation with other variables, AC was excluded from the multivariate analysis. The objective was to determine whether statistically significant physical differences exist between male and female neonates at birth. The study employed Hotelling’s T² test and profile analysis; however, the assumptions of homogeneity of covariance matrices (tested via Box’s M) and independence (assessed via scatter plots) were violated. To address these issues, a robust non-parametric permutation-based Hotelling’s T² test was conducted, yielding a statistically significant result (p < 0.001), indicating notable gender-based differences in multivariate mean vectors. While the main effect of Feature was highly significant (p < 0.001), revealing differences among OFC, CC, LOB, and WT, the Gender × Feature interaction was non-significant (p > 0.05), suggesting parallel measurement patterns across genders. The study concludes that gender significantly influences neonatal physical traits and that advanced multivariate methods, including Hotelling’s T² and profile analysis, are effective for analyzing high-dimensional neonatal data—even under violations of classical assumptions such as normality and homoscedasticity.