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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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Business Insights Unveiled: A Journey through Linear Programming Problems Jha, Aditya; Sahani, Suresh Kumar; Jha, Anshuman; Sahani, Kameshwar
Mikailalsys Journal of Mathematics and Statistics Vol 1 No 1 (2023): 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.v1i1.1948

Abstract

This project delves into the world of linear programming problems (LPP), a powerful optimization technique. It delves into the historical background, key features, fundamental assumptions, and wide-ranging applications of LPP. It also explores two hypothetical case studies: one in investment portfolio optimization and the other in advertisement budget allocation. LPP serves as a guiding light in making strategic investment decisions by maximizing returns and minimizing risks. In the context of advertising, it enables efficient budget allocation to reach the maximum audience and achieve the highest impact within constraints. The project emphasizes how LP simplifies complex decision-making processes, highlighting its practicality and relevance across diverse sectors. In essence, linear programming emerges as an indispensable tool for informed, data-driven decision-making, much like a skilled navigator guiding a ship through challenging waters toward its destination.
Distance Metrics for Machine Learning and it's Relation with Other Distances Yadav, Dipendra Prasad; Kumar, Nand Kishor; Sahani, Suresh Kumar
Mikailalsys Journal of Mathematics and Statistics Vol 1 No 1 (2023): 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.v1i1.1990

Abstract

In machine learning, distance metrics play a crucial role in measuring the degree of dissimilarity among data points. When creating and optimizing machine learning models, data scientists and machine learning practitioners can make more informed choices by understanding the features of popular distance metrics and their relationships. The effectiveness and interpretability of the model's output can be greatly influenced by selecting the appropriate distance metric. We explain distance metrics and their relevance in machine learning with various examples of metrics, including Minkowski distance, Manhattan distance, Max Metric for R^n, Taxicab distance, Relative distance, and Hamming distance.
Expansive Type Rational Contraction in Metric Space and Common Fixed Point Theorems Yadav, Devnarayan; Tiwari, Surendra Kumar
Mikailalsys Journal of Mathematics and Statistics Vol 1 No 1 (2023): 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.v1i1.2029

Abstract

The field of expansive mappings in fixed-point theory is one of the most fascinating areas in mathematics. In this theory, contraction is one of the main tools used to prove a fixed point's existence and uniqueness. For all of the analyses, the fixed point theorem proposed by Banach's contraction theory is highly popular and widely used to prove that a solution to the operator equation Tx=x exists and is unique. Through the present article, we utilize rational expressions in metric spaces to deliver unique common stable (fixed) point results in expansive mapping. The main outcomes of numerous relevant innovations in the newest research are built upon them.
Fuzzy Arithmetic–Based Algorithm for Identifying Medical Conditions for Better Treatment Paudel, Gyan Prasad; Upadhyay, Parbati Kumari; Baral, Aasis
Mikailalsys Journal of Mathematics and Statistics Vol 1 No 1 (2023): 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.v1i1.2074

Abstract

Making the right medical decision is challenging work because, in our daily life, decision-making problems may have the components of membership and non-membership degrees with the possibility of hesitation. Since soft theory offers a theoretical framework for dealing with ambiguous, fuzzy, and ill-defined objects, it is a key development in the field of computer programming as well as other scientific disciplines. Intuitionistic fuzzy soft sets provide an effective tool for solving multiple attribute decision-making with intuitionistic fuzzy information. The most essential issue is how to derive the ranking of alternatives from the information quantified in terms of intuitional fuzzy values. This theory also has the potential to be used to solve such real-world problems. In this work, we explore how Sanchez's medical theory could be used in medical diagnosis and provide a fuzzy arithmetic-based algorithm for identifying medical conditions to address this.
Poincare's Theorem of Asymptotic Series and its Application Kumar, Nand Kishor; Yadav, Dipendsra Prasad; Sahani, Suresh Kumar
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 1 (2024): 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.v2i1.2460

Abstract

This article explains an important asymptotic series theorem. Poincare also demonstrates how to solve linear differentials with polynomial coefficients using asymptotic series. The significance of asymptotic series has also been discussed.
The Non-Seasonal Holt-Winters Method for Forecasting Stock Price Returns of Companies Affected by BDS Action Qur'ani, Anggun Yuliarum; Widyaningrum, Chandra Sari
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 1 (2024): 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.v2i1.2673

Abstract

The non-seasonal Holt-Winters method is one of the methods of smoothing theory. This method can be implemented on time series data that does not have a seasonal component. In this study, this method is used to forecast the stock price returns of companies affected by the Boycott, Divestment, and Sanctions (BDS) action. Forecasting gets very good results that can be seen from the MAPE value of modeling the six stocks affiliated with Israel that continue to carry out Zionism against Palestine is not more than 10%. This method can also accommodate the limitations of existing data while still obtaining good forecasting results. In addition, the use of several transformations of stock price returns in this case is very useful in modeling to obtain appropriate error assumptions. The forecasting results of the model formed as a whole follow the trend in the stock price of each company. To produce good forecasting results using this method, it is recommended to do forecasting in the short term. The forecasting results show that of the six company stocks, almost all of them experienced a decrease in stock price returns. Only one stock of PT Map Boga Adiperkasa Tbk has increased. This also illustrates that the BDS action influences on these companies.
Poisson-New Quadratic-Exponential Distribution Sah, Binod Kumar; Sahani, Suresh Kumar
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 2 (2024): 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.v2i2.2862

Abstract

This proposed distribution is a discrete compound probability distribution with only one parameter. To get this distribution, Poisson distribution has been mixed with the New Quadratic-Exponential distribution of Sah (2022). Hence, it is named as “Poisson-New Quadratic-Exponential Exponential Distribution (PNLED)”. The important statistical characteristics needed to check the validity of this distribution have been derived and clearly explained. To check the validity of the theoretical works of this distribution, while using goodness of fit on some over-dispersed count data, what we have been found that this distribution seems a better alternative of Poisson-Lindley distribution (PLD) of Sankaran (1970), Poisson Mishra distribution (PMD) of Sah (2017) and Poisson-Modified Mishra distribution (PMMD) of Sah and Sahani (2023).
Ensemble Machine Learning Algorithm for Diabetes Prediction in Maiduguri, Borno State Dada, Emmanuel Gbenga; Birma, Aishatu Ibrahim; Gora, Abdulkarim Abbas
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 2 (2024): 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.v2i2.2875

Abstract

Diabetes mellitus (DM) is a metabolic disease characterised by high levels of glucose in the blood, known as hyperglycemia, that can result in multiple problems within the body. The World Health Organisation (WHO) data for 2021 reveals a substantial increase in the prevalence of diabetes mellitus (DM), with the number of cases rising from 108 million in 1980 to 422 million in 2014. Between 2000 and 2019, there was a 3% increase in mortality rates associated with diabetes, categorised by age. In 2019, DM caused the deaths of more than 2 million people. These concerning figures clearly necessitate an immediate response. An alarming incidence of diabetes among the population of Maiduguri and Borno State inspired this investigation. This research proposed stacking ensemble learning approach to predict the rate of occurrence of diabetes cases in Maiduguri. The paper used different types of regression models to predict the occurrences of diabetes cases in Maiduguri over time. These models included adaptive boosting regression (Adaboost), gradient boosting regression (GBOOST), random forest regression (RFR), ordinary least square regression (OLS), least absolute shrinkage selection operator regression (LASSO), and ridge regression (RIDGE). The performance indicators studied in this work are root mean square (RMSE), mean absolute error (MAE), and mean square error (MSE). These metrics were used to assess the effectiveness of both the machine learning and proposed Stacking Ensemble Learning (SEL) approaches. Performance metrics considered in this study are root mean square (RMSE), mean absolute error (MAE), and mean square error (MSE), which were used to evaluate the performance of the machine learning and the proposed Stacking Ensemble Learning (SEL) technique. Experimental results revealed that SEL is a better predictor compared to other machine learning approaches considered in this work with an RMSE of 0.0493; a MSE of 0.0024; and a MAE of 0.0349. It is hoped that this research will help government officials understand the threat of diabetes and take the necessary mitigation actions.
Application of Queue Theory in Cafe Services with Erlang Distribution Ramadhani, Bagus D.; Cahyono, Budi; Rahayu, Joana K.; Rahmah, Syifa M.; Dani, Andrea Tri Rian
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 3 (2024): 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.v2i3.3403

Abstract

As urban lifestyles evolve, culinary businesses, particularly cafes, have experienced rapid growth. This surge in popularity has led to an increase in customers and, consequently, longer queues. These extended wait times can frustrate customers and pose challenges to cafe management. To address this issue, we conducted a comprehensive eval_uation and optimization of the service system at a Samarinda cafe using the Erlang distribution queuing system. Primary data was meticulously collected over six days, amounting to a total of 12 hours of observation. Kolmogorov-Smirnov distribution fitting tests were employed, revealing that customer service times adhered to an exponential distribution. The average customer arrival rate was determined to be 0.351 per minute, while the average service time was calculated at 5.546 minutes per customer. Our analysis confirmed that the system operates in a steady state with a utility value of 0.06, indicating sufficient service capacity to handle the current customer load. Therefore, the study concludes that the cafe's service system is currently optimal.
F-Test and Analysis of Variance (ANOVA) in Economics Kumar, Nand Kishor
Mikailalsys Journal of Mathematics and Statistics Vol 2 No 3 (2024): 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.v2i3.3449

Abstract

ANOVA remains a cornerstone of empirical economic research, providing economists with a robust framework to analyze differences between groups, eval_uate policy interventions, and draw meaningful conclusions from data. Its versatility and applicability across diverse economic contexts underscore its significance in advancing economic theory and informing evidence-based policymaking. As data availability and computational capabilities continue to expand, ANOVA's role in economic analysis is expected to evolve, supporting increasingly sophisticated studies of economic phenomena and policy impacts. In economics, particularly in empirical research and data analysis, the F-test and Analysis of Variance (ANOVA) are fundamental statistical tools used to test hypotheses regarding the equality of means across two or more groups.

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