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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 93 Documents
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Some Entropies Derivation for Entropy Transformed Exponential Distribution with Application to Health Data H. A., Tugga; I. J.,, David; O. D., Adubisi
Mikailalsys Journal of Mathematics and Statistics Vol 4 No 2 (2026): 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.v4i2.9197

Abstract

This study aims to estimate and comparatively evaluate the performance of four entropy measures—Havrda–Charvat, Kapur, Verma, and Mathai–Haubold—in modeling newborn weight. A quantitative approach was adopted through analytical derivations and Monte Carlo simulation techniques. The performance of each entropy measure was assessed across varying sample sizes using bias, mean squared error (MSE), and root mean squared error (RMSE) as evaluation criteria. The findings indicate that the Havrda–Charvat entropy measure demonstrates superior accuracy, consistency, and convergence toward the true entropy values, thereby exhibiting robust performance under the entropy-transformed exponential distribution (ETED). These results contribute to the theoretical development of entropy-based modeling by extending current understanding of estimator performance within ETED and providing comparative evidence on the suitability of alternative entropy measures for newborn weight modeling.
Enhancing Volatility Forecasting in the Nigerian Stock Exchange: Evaluating GARCH-Type Models and Innovation Densities Oboh, Samuel Ohiorhenuan; Alayande, Semiu Ayinla; Olatunde, Faith Oluwadamilola
Mikailalsys Journal of Mathematics and Statistics Vol 4 No 2 (2026): 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.v4i2.9210

Abstract

Although volatility modeling in emerging stock markets has received increasing attention, limited research has jointly compared GARCH-type model structures under alternative symmetric and skewed innovation densities in the Nigerian capital market. This study aims to evaluate the forecasting performance of selected GARCH-type models under alternative innovation densities using daily returns of the Nigerian Stock Exchange All Share Index (NSE-ASI) from February 2012 to July 2023. A quantitative econometric time-series design was employed, involving 2,820 daily observations selected through purposive sampling based on data availability. Data were obtained from the official market database and analyzed using Maximum Likelihood Estimation, model selection criteria comprising Log-Likelihood (LL), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC), and forecast accuracy measures including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). The findings indicate that the APARCH(1,1)-GED model provides the best in-sample fit, whereas the APARCH(1,1)-SGED specification produces the most accurate out-of-sample forecasts. These results demonstrate the importance of innovation density selection in capturing asymmetry and fat-tailed behavior in stock return volatility. The study concludes that incorporating skewed heavy-tailed distributions enhances volatility forecasting accuracy in the Nigerian capital market. The findings contribute to the theoretical development of conditional heteroskedasticity modeling and offer practical implications for risk management, portfolio analysis, and regulatory forecasting in emerging markets. Future research may extend this work by examining advanced nonlinear and regime-switching volatility models across broader emerging market contexts.
Utilizing Permutation and Combination Techniques in Business Decision-Making Processes Sah, Bardan; Jayswal, Ritika; Thakur, Satyam; Shah, Neha; Sah, Dilip Kumar; Sahani, Suresh Kumar
Mikailalsys Journal of Mathematics and Statistics Vol 4 No 2 (2026): 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.v4i2.9336

Abstract

Although permutations and combinations are often regarded as purely theoretical mathematical topics, they play a significant role in practical decision-making and contemporary business operations. This study examines the application of permutations and combinations in everyday decision-making and real business contexts, particularly in quality control, marketing strategy, resource planning, and inventory management. Using real-world examples and case studies, the article demonstrates how organizations employ these combinatorial concepts to improve productivity, reduce costs, optimize available resources, and strengthen competitive advantage in increasingly complex market environments. The findings indicate that a sound understanding of permutations and combinations enhances managerial and executive decision-making, especially when evaluating numerous alternatives, assessing the likelihood of possible outcomes, selecting appropriate combinations of people or products, and determining optimal configurations. The study concludes that permutations and combinations are not merely academic concepts but practical analytical tools that support more effective and strategic business decisions. This study contributes to a broader understanding of how foundational mathematical reasoning can be applied to improve organizational efficiency and decision quality in business practice.

Page 10 of 10 | Total Record : 93

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