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International Journal of Applied Mathematics and Computing.
Published by Asosiasi Riset Ilmu Matematika dan Sains Indonesia
ISSN : -     EISSN : 3047146X     DOI : 10.62951
Core Subject : Science, Education,
Computer Science & IT Mathematics
This Journal accepts manuscripts based on empirical research, both quantitative and qualitative. This journal is a peer-reviewed and open access journal of Mathematics and Computing
Arjuna Subject : Matematika - Matematika Komputer
Articles 23 Documents
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On Fuzzy α̂g-Topological R-Module Spaces Basim Mohammed Melgat
International Journal of Applied Mathematics and Computing Vol. 2 No. 1 (2025): International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i1.33

Abstract

The aim of this research is to give a new definition and study a new notion of fuzzy α̂g-topological R-module spaces using fuzzy α̂g-open sets. The concept of fuzzy α̂g-topological R-modules is introduced and study them to provide a mathematical basis. Traditional cautiousness for F bisected by α̂g-tautologies reigns furtive-space yield we assay different fuzzy α̂g-separation axioms such as  where  in the context of these spaces.  Also, we study fuzzy -separation axiom  in fuzzy  - Topological. R-Module space. The results indicate that throughout the  domain of a fuzzy topological R-module space  the following fuzzy separation axioms  and are valid.  Also, we also show that possessing fuzzy α̂g-open neighborhoods has further consequences to the structure and continuity of fuzzy topological spaces. The main conclusion of our research is that the mysterious α̂g topological R-unit spaces are a new and interesting area for further study. The terms of their operations in addition to providing important information about the interaction between fuzziness and topological properties that may be useful in many mathematical and applied branches.
Mutual Fund Performance Analysis Using Information Ratio, STJ Ratio and Value at Risk Ni Putu Leony Putri Paramita; Komang Dharmawan; I Gusti Ngurah Lanang Wijaya Kusuma
International Journal of Applied Mathematics and Computing Vol. 2 No. 1 (2025): International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i1.66

Abstract

Measuring performance solely by relying on returns is probably not enough, it is important to consider both returns and risks. Some measurement methods that consider both of these factors are the Sharpe Ratio index, Treynor Ratio, Jensen Alpha, and Information Ratio. Risk analysis using Value at Risk Monte Carlo simulation is also important to determine the potential for extreme risks. The purpose of this study is to provide a good understanding of the performance and risk of mutual fund investments. Based on the performance results, Schroder is the most superior mutual fund, with the highest Information Ratio, Sharpe Ratio, and Jensen Ratio, indicating that they are able to generate good returns considering the risks taken. However, Schroder also has the highest VaR, meaning it has the potential for large losses in the worst market conditions. On the other hand, MNC is at the bottom in almost all performance methods, indicating poor performance with low returns and lower risks.
A Numerical Solution for Heat Transfer in Nanofluid Flow Using Modified Lattice Boltzmann Method Dini Faradina; Mohamad Subagus Fahmi; Dadan Purnama
International Journal of Applied Mathematics and Computing Vol. 1 No. 2 (2024): April : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i2.70

Abstract

This research presents a numerical investigation into heat transfer in nanofluid flow using an advanced lattice Boltzmann method (LBM). The study modifies the standard LBM to incorporate the unique properties of nanofluids, such as enhanced thermal conductivity. We simulate convective heat transfer in a pipe with varying nanoparticle concentrations, assessing the effects on heat transfer rates. Results show that nanofluids significantly improve heat transfer efficiency, offering valuable insights for engineering applications in cooling systems.
A Comparative Analysis of Machine Learning Models for Time Series Forecasting in Finance Noraini Abu Talib; Rafiq Ahmad; Siti Norbaya Noor
International Journal of Applied Mathematics and Computing Vol. 1 No. 2 (2024): April : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i2.71

Abstract

This study compares different machine learning models for time series forecasting in financial data analysis. Models including ARIMA, LSTM, and GRU are applied to predict stock price movements. We measure the accuracy and computational efficiency of each model on various datasets and discuss their strengths and weaknesses in financial forecasting contexts. The findings suggest that deep learning models show significant improvement in capturing complex temporal patterns over traditional methods.
Optimization of Nonlinear Systems Using Genetic Algorithms: A Case Study in Resource Allocation Sarah Elhassan; Mohammed Idris; Hiba Abdallah
International Journal of Applied Mathematics and Computing Vol. 1 No. 2 (2024): April : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i2.72

Abstract

This paper explores the use of genetic algorithms (GAs) for optimizing nonlinear systems in resource allocation. By simulating various allocation scenarios, we demonstrate the efficiency of GAs in finding near-optimal solutions in complex environments. The study provides a comparison of GA performance against traditional optimization methods and identifies scenarios where GAs outperform. The results emphasize the utility of GAs in real-world applications, especially when conventional approaches struggle with large solution spaces.
Stability Analysis of Fractional Order Differential Equations with Time Delays Lutfiah Dwi Ristiani; Selvi Angelina; Tavika Trirahma
International Journal of Applied Mathematics and Computing Vol. 1 No. 2 (2024): April : International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v1i2.75

Abstract

This paper investigates the stability characteristics of fractional order differential equations (FODEs) incorporating time delays. Using the Lyapunov-Krasovskii method, we derive sufficient conditions for the stability of solutions to these delayed fractional systems. The theoretical findings are applied to several examples, including models of population dynamics and engineering systems. Numerical simulations validate the theoretical results, demonstrating the role of time delays in system behavior and stability.
Factors Influencing the Study Period of Students of the Mathematics Study Program at Udayana University Ulfatun Farika Novitasari; Adinda Audy Sita Mayzandy; Miltiades Dewifortuna Pulo; Juliani Tandi Tumbiri; Nurul Ilma; Made Susilawati
International Journal of Applied Mathematics and Computing Vol. 2 No. 1 (2025): International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i1.92

Abstract

The student study period is one of the important aspects to measure the quality of a higher education institution. The length of the student study period can be assumed to come from internal factors and external factors, so it is necessary to conduct research that aims to identify and model the factors that affect the student study period. The method used in this research is logistic regression and the data used is primary data obtained from distributing questionnaires. The target of this research is aimed at alumni students from the Mathematics Study Programme of Udayana University from 2011 to 2019. In this study, the best model produced has a classification accuracy of 98.17% and the independent variables that have a significant effect on the study period are gender, tuition fees and interest in majors.
Application of Conditional Monte Carlo Simulation in Determining European Option Contract Pricing (Case Study on Toyota Motor Corporation (TM) Stock) Fransisca Emmanuella Aryossi; Komang Dharmawan; I GN Lanang Wijayakusuma
International Journal of Applied Mathematics and Computing Vol. 2 No. 1 (2025): International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i1.97

Abstract

When making investment decisions, it is crucial for investors to consider various risks that may arise, both in the short and long term. One method to measure risk is through volatility. Volatility represents a statistical measurement of the degree of price variation over a specific period, expressed as volatility (σ) (Aklimawati & Wahyudi, 2013). This study aims to discuss the pricing of European option contracts using Conditional Monte Carlo simulation and the Black-Scholes method. The data used in this study is secondary data obtained from Yahoo Finance. The data consists of quantitative information, namely the monthly closing prices of Toyota Motor Corporation (TM) stock, spanning 5 years from July 1, 2019, to July 1, 2024, yielding 60 data points. In this research, the pricing of European call option contracts was calculated using Conditional Monte Carlo simulation and the Black-Scholes method. The study concludes that European option contract pricing can be determined using two methods: Conditional Monte Carlo simulation and the Black-Scholes method. Conditional Monte Carlo simulation can be employed to calculate European option prices in a structured manner, utilizing stochastic volatility estimated through the Ordinary Least Squares (OLS) method. The two methods yield differing option prices; Conditional Monte Carlo simulation produces lower option price estimates with relatively lower error values compared to the Black-Scholes method at every strike price. The lower estimates from Conditional Monte Carlo simulation are due to its consideration of stochastic changes in volatility, whereas the Black-Scholes method results in higher prices due to its assumption of constant volatility. The comparison demonstrates that Conditional Monte Carlo simulation provides cheaper price estimates under market conditions with non-constant volatility, despite requiring higher computational time compared to the Black-Scholes method. ,
Extended Gamma Distribution to Fitting Breast Tumors Adel Abbood Najm; Bashar Khalid Ali
International Journal of Applied Mathematics and Computing Vol. 2 No. 1 (2025): International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i1.109

Abstract

There are many patterns of breast cancer change that make it a global health challenge. The research aims to propose an expanded gamma distribution with parameters and apply it to data for (103) patients with breast cancer. Data normality tests were used, such as the Kolmigrov-Smirnov test, the Anderson-Darling test, and the Chi-square test, to fit the real data. The parameters of the proposed distribution were estimated using the maximum likelihood method. It was found that there is a large difference in the real data with positive Skewness in it. The maximum likelihood estimates reflected the suitability of the data to the proposed distribution, which indicates the accuracy of the obtained results.
Determining the Price of Asian Type Call Option Contracts Using the Monte Carlo Stratified Sampling Method Susanti Marito Barus; Komang Dharmawan; Luh Putu Ida Harini
International Journal of Applied Mathematics and Computing Vol. 2 No. 2 (2025): April: International Journal of Applied Mathematics and Computing
Publisher : Asosiasi Riset Ilmu Matematika dan Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijamc.v2i2.188

Abstract

Determining the price of option contracts is a crucial aspect of financial markets, particularly for investors aiming to manage risk and make informed investment decisions. In this study, the price of an Asian call option is calculated using the Monte Carlo Stratified Sampling method based on the stock price data of Tesla, Inc. (TSLA) from January 2021 to December 2023. This method has been proven to reduce variance compared to the Standard Monte Carlo simulation, leading to faster price convergence and more efficient results. The parameters used in the simulation include the initial stock price (S_0), number of simulations (N), maturity time (T)dividend = 0, risk-free rate (r), strike price ( K), and volatility

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