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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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Generic Count Distributions and Their Zero-Inflated Forms: A Simulation Study A., Adetunji A.; M., Sabri S. R.
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.v3i2.5171

Abstract

The percentage of zero observations necessitating zero-inflated distributions in count data modelling has been a major issue. The challenge in such a situation is determining when to shift from parent distributions to their zero-inflated versions. In most studies, the performances of parent distributions are assessed with those of their zero-inflated forms. This study conducts simulation studies for the Poisson and the negative binomial distributions and their respective zero-inflated forms. Count data [0, 4] with different percentages of zero counts are simulated using different sample sizes. Both negative log-likelihood and Bayesian information criterion (which considers the number of estimated parameters) are used to assess performance. Results show that the zero-inflated Poisson distribution best suits modelling all forms of data when the negative log-likelihood value is used to assess performance. When the BIC is used, the Poisson distribution gives the best performance for both 10% and 20% zeros, while the ZIP distribution is the best for both 50% and 90% zeros. The NB distribution outperforms the ZINB distribution in all situations. Also, in all cases, the negative binomial performs better than the zero-inflated negative binomial distributions. To further assess the distributions, four count data sets with varying percentages of zero are examined. Both the ZIP and the NB distributions perform better than others.
Developing an AI-Driven Predictive Model for Stock Market Forecasting in the Banking Sector Akinnagbe, Olayiwola Blessing; Akintayo, Taiwo Abdulahi; Adanna, Arinze Betsy
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.v3i2.5197

Abstract

This study develops an AI-driven predictive model for stock market forecasting in the banking sector, using LSTM, Random Forest, and Linear Regression. Historical stock prices, macroeconomic indicators, and banking sector metrics were analyzed, with data preprocessing techniques applied to enhance accuracy. Model performance was evaluated using MAE, RMSE, and R², with LSTM achieving the best results (R² = 0.92). Findings suggest AI models can improve investment decisions, trading strategies, and risk management. Future research should explore real-time data integration, sentiment analysis, and hybrid AI models for enhanced forecasting accuracy.
Optimal Control Analysis of the Dynamical Spread of Malaria/Cholera Co-Infection Adeniran, G. A.; Alabi, M. O.; Olopade, I. A.; Akinrinmade, V. A.
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.v3i2.5205

Abstract

In this paper, a fourteen (14) non-linear compartmental model is presented to study the transmission dynamics of Malaria/Cholera co-infection in a population at any point in time. The model is rigorously analyzed to gain insight into the dynamical features of Malaria/Cholera co-infection in order to know the effect of each control and which of the diseases should be treated before the other when all the controls are to be implemented. Optimal control analysis was carried out with different control strategies, Malaria Prevention (Mosquitoes treated bed net (µ1)), Malaria Treatment (µ2), Malaria-Cholera Prevention (µ3), Cholera Prevention (µ4), Cholera Treatment (µ5) and Boosting of Immune System (µ6) were introduced as the control strategy for the spread of Malaria-Cholera Co-infection and also, optimal control theory is applied to give an optimality system which we used to minimize the number of infected individuals and propose the most suitable control strategy for the spread of malaria/cholera co-infection. It is shown that the model has a diseases free equilibrium which is globally asymptotically stable (GAS). Also, there exists a unique endemic equilibrium point which is locally stable whenever the associated threshold is less than unity i.e Ro<1 and become unstable whenever the associated threshold quantity exceeds unity i.e Ro>1. It was also shown that there exists a solution for the optimality system. Numerical Simulation was performed using Differential Transformation Method (DTM). From the result, it was observed that the prevention control and treatment control strategies were more efficient in reducing the number of malaria/cholera infected individuals as compared to other control strategies.
Markov Chain Prediction of the Long-Run Behavior of Nigerian Oil Stock Jude, Iroka; Mamidu, Moses Joanna
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.v3i2.5263

Abstract

This study examined the behavior and long-term prospects of selected Nigerian oil stocks such as Conoil, Seplat Oil, and Total Oil by analyzing their daily closing prices using the Chi-Square test for independence, transition probability matrices, and steady-state probability analysis. The Chi-Square test revealed a significant dependence between the daily closing prices of the stocks, indicating a correlation between subsequent price movements. The transition probability matrices showed that Conoil and Seplat Oil have an equal likelihood of transitioning between the High (33.34%), Stable (33.33%) and Low (33.33%) price states, while Total Oil demonstrated a stronger preference for the High (41.92%) , stable (36.71%) and low (21.37%) states. The steady-state probabilities revealed that Conoil and Seplat Oil and Total Oil have a higher likelihood of remaining in the high state in the long term, with Total Oil exhibited a more balanced distribution, suggesting a more stable price movement. The findings imply that investors should consider the correlation between daily price movements and the long-term behavior of these stocks. However, the study's limitations, such as the exclusion of external factors like global oil prices and political stability, should be taken into account when interpreting the results.
Renyi Entropy Derivation for a Modified Skewed Student-t Distribution Nkombou, M. B. W.; David, I. J.; Okeke, E. N.
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.v3i2.5265

Abstract

This paper derives the Renyi entropy for a modified Skew Student-t distribution (SStD). The skew Student-t distribution was modified using DUS transformation technique. The final expression of the Renyi entropy was derived using the probability density function of the transformed (SStD).
The Effect of Teaching on Entry Behavior of Students in Mathematics Jude, Iroka; Napoleon, Ishaya Joseph
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.v3i2.5270

Abstract

This study investigates the impact of teaching method on the entry behavior of students in mathematics. The study utilized both quantitative and qualitative data analysis methods with a focus on pre-and post- intervention survey scores. The results indicate that student exposed to interactive and experimental teaching methods showed significant improvements in their attitude motivations, and perceptions towards the subject. The finding suggests that these teaching methods are more effective in influencing entry behavior compared to traditional methods. The study highlights the importance of adopting innovative teaching practices to create a more engaging learning environment and improve, overall learning outcomes. Further research is recommended to explore the long term effect of teaching methods on entry behavior and academic performance in different educational settings.
Exploratory Analysis of Students’ Score Jude, Iroka; Mamidu, Moses Joanna
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.v3i2.5276

Abstract

The main thrust of this study was to determine the effect of Sex, Age, School, and Mode of Entry on performance of students in the subject Biology using Univariate Analysis of variance for the four factors (Sex, Age, School, and Mode of Entry) at two levels each factorial design. The case study is a single random sampling of 100 students selected from the 150 in a class of 200 level students from the Department of Biochemistry, Biological Sciences and Microbiology, Federal University Wukari, Taraba State, Nigeria. To achieve the purpose of this study, hypotheses were formulated to direct the study. Literature review was carried out according. Secondary data from the Department of Biological Science were used to analyse the findings of this research work. All hypotheses were tested at 0.05 level of significance. The results obtained showed that the four factors interaction is the only significant treatment in the factorial design. Eta squared showed that the four factors (Sex, Age, School, and Mode of Entry) interaction contributes the greatest to the variations in the students’ scores in the subject. Noncent parameter and Observed power showed the same. The study recommended amongst other things that parents and educationists should provide enabling environment for the students by ensuring their age, school, and mode of entry is taken cognizance of as it has a significant impact on the students’ performance; parents who are interested in the educational performance of their children to become Biologists or take up Biology and parents who are tending to mould their children to become Biologists or take up Biology related careers in the future to take these four factors into consideration.
Analysis of a Mathematical Model for Malaria Transmission with Vaccination Parameter K., Adamu A.; W., Barde; M., Bulus S.; D., Yavalah
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.v3i2.5316

Abstract

Malaria remains a significant global health challenge, particularly in tropical regions. In this study, we extended the existing compartmental model of S. O. Adewale et al, (2017) by incorporating a vaccination parameter. We established the positivity of solutions, existence and uniqueness of solutions, and analyze the disease-free equilibrium (DFE). The basic reproduction number is derived using the next-generation matrix method, and local/global stability conditions were established. Numerical simulations were carried out to determine the impact of vaccination on the transmission dynamics of the disease. Our findings provide insights into effective malaria control strategies. Also, the result shows that effective vaccination can drastically eradicate the scourge of malaria within the shortest period of time.
The Binosson Distribution: A Unified Probabilistic Framework Bridging the Binomial and Poisson Models Ayo, Ayenigba Alfred; Emmanuel, Amoyedo Femi; Adebisi, Afariogun David
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.v3i2.5318

Abstract

Classical Binomial and Poisson distributions, constrained by fixed trials and static event rates, falter in modeling modern datasets with dynamic parameters or contextual dependencies (e.g., variable infection rates, covariate-influenced risks). This paper introduces the Binosson Distribution, a hybrid framework unifying Binomial trials and Poisson processes through dynamic parameterization of trial counts (n) and designed to address event rates (λ). The distribution has been proposed to bridge the gap between these two distributions, incorporating aspects of both. Binomial-cum-Poisson distributions are modified to obtain a distribution that will be able to solve the probability problems that lies between the two distributions. Binosson is the result from the product of Binomial and Poisson distributions. Statistical properties such as mean, variance, standard deviation, skewedness and kurtosis were also derived.
The Application of Brownian Motion Model on Nigeria Stock Exchange Data Joshua, ThankGod; Isah, Audu
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.v3i2.5349

Abstract

Fluctuations in stock prices and its random nature make stocks volatile and difficult for financial managers and investors to predict future stock prices. The path of stock can be described in relation to the random collision of tiny particles suspended in the molecules of liquid. In examining the martingale property in stock prices, this article examined whether stock price log follows a normal distribution and whether the expected mean and the expected volatility in stock is an increasing function of time. The sample for this study was based on listed monthly stock data quoted on the Nigerian stock exchange for a period of five years (2015-2019). The test of normality was conducted using the Kolmogorov-Smirnov test statistic and the geometric Brownian motion model was employed as the method of data analysis. Results of the analysis showed that the log of stock price follows a normal distribution, it also showed that the expected mean and expected volatility of stock price is an increasing function of time, depicting randomness and fluctuations in its path as a result of the market shocks and volatility.

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