International Journal of Mathematics, Statistics, and Computing
International Journal of Mathematics, Statistics, and Computing (IJMSC) is an official journal of the Communication in Research and Publications (CRP) and publishes original research papers that cover the theory, practice, history, methodology or models of Mathematics, Statistics, and Computing (MSC). IJMSC will act as a platform to encourage further research in Mathematics, Statistics, and Computing, theory and applications. The rapid development of science and technology has had a significant impact on various aspects of human life, including in the fields of economy, education, culture and government. The positive impacts of science and technology include facilitating access to information and communication, accelerating production and service processes, as well as providing new business and investment opportunities. Mathematics, statistics, and computer science have a very important role for the advancement of science and technology. Among them are as a basis for computer programming, basic calculations in the development of modern tools, can solve a problem even with big data. The mission of the International Journal of Mathematics, Statistics, and Computing (IJMSC) is to enhance the dissemination of knowledge across all disciplines in theory, practice, history, methodology or models of Mathematics, Statistics, and Computing (MSC). The above discipline is not exhaustive, and papers representing any other social science field will be considered. The IJMSC particularly encourage manuscripts that discuss the latest research findings or contemporary research that can be used directly or indirectly in addressing critical issues and sharing of advanced knowledge and best practices in Mathematics, Statistics, and Computing (MSC). The essential but not exclusive, audiences are academicians, graduate students, researchers, policy-makers, regulators, practitioners, and others interested in business, management, economics, and social development studies. For ensuring a wide range of audiences, this journal accepts only the articles in English. The scope of mathematics are: Algebra, Applied Mathematics, Financial Mathematics, Approximation Theory, Combinatorics, Computing in Mathematics, Operations Research Methodology, Discrete Mathematics, Mathematical Physics, Geometry and Topology, Logic and Foundations of Mathematics, Number Theory, Numerical Analysis, and other relevant matters. The scope of statistics are: Probability Theory, Central Limit Theorem Computation, Sample Survey, Statistical Modeling, Statistical Theory, Computational Statistics, Data Sciences, Actuarial Sciences, Regression Models, Time Series Models, and other relevant matters. The scope of computing are: Algorithms and Data Structures, Computer Architecture, Software Engineering, Artificial Intelligence and Robotics, Human and Computer Interaction, Informatics Organizations, Programming Languages, Operating Systems and Networks, Databases, Computer Graphics, Computing Science, BioInformatics, Information Technology, and other relevant matters.
Articles
60 Documents
<![CDATA[Basic Concepts of Stock Option Pricing Models Traded in the Capital Market ]]>
<![CDATA[Ibrahim, Riza Andrian]]>;
<![CDATA[Azahra, Astrid Sulistya]]>;
<![CDATA[Kalfin]]>;
<![CDATA[Saputra, Moch Panji Agung]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 4 (2024): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v2i4.141
<![CDATA[An option, in the world of capital markets, is a right based on an agreement to buy or sell a commodity, financial securities, or a foreign currency at an agreed price at any time within a three-month contract period. Factors that determine the value of an option include the current price of the stock, intrinsic value, expiration time or time value, volatility, interest rate, and cash dividends paid. Some options pricing models use this parameter to determine the fair market value of an option. This paper aims to learn the basic concepts of option pricing. The method used in studying the pricing of options is a literature review, which is an activity to collect scientific data, especially in the form of theories, methods, or research that has been carried out previously, either in the form of books, manuscripts, journals, and others that already exist in the library. Based on the results of the study, concepts, scientific findings, and method innovations that have been achieved previously are obtained, which are very relevant and useful for understanding the determination of stock option prices. An option, in the world of capital markets, is a right based on an agreement to buy or sell a commodity, financial securities, or a foreign currency at an agreed price at any time within a three-month contract period. Factors that determine the value of an option include the current price of the stock, intrinsic value, expiration time or time value, volatility, interest rate, and cash dividends paid. Some options pricing models use this parameter to determine the fair market value of an option. This paper aims to learn the basic concepts of option pricing. The method used in studying the pricing of options is a literature review, which is an activity to collect scientific data, especially in the form of theories, methods, or research that has been carried out previously, either in the form of books, manuscripts, journals, and others that already exist in the library. Based on the results of the study, concepts, scientific findings, and method innovations that have been achieved previously are obtained, which are very relevant and useful for understanding the determination of stock option prices.]]>
<![CDATA[Optimization of Renewable Energy Company Stock Portfolio for Investment Decision Making using the Markowitz Model ]]>
<![CDATA[Saputra, Renda Sandi]]>;
<![CDATA[Rahayu, Alpi fauziah]]>;
<![CDATA[Suhaimi, Nurnisaa Binti Abdullah]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 4 (2024): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v2i4.142
<![CDATA[This study focuses on optimizing the renewable energy company's stock portfolio using the Markowitz model, which aims to balance risk and return for proper investment decision making. With the increasing demand for clean energy, portfolio optimization in the renewable energy sector is important for investors. This research takes into account historical stock performance and applies the Mean-Variance Optimization framework to minimize risk while maximizing return. This portfolio consists of selected renewable energy companies, and the analysis runs from September 2021 to August 2024. This study aims to analyze the allocation of investment portfolios in renewable energy company stocks in Indonesia. Based on the analysis results, the investment portfolio is allocated to five main stocks, namely BUMI.JK with an investment value of IDR 17,075,844 (17.08%), INDY.JK of IDR 5,825,852 (5.83%), KEEN.JK of IDR 33,766,798 (33.77%), RAJA.JK of IDR 43,084,876 (43.08%), and WIKA.JK of IDR 246,630 (0.25%). These results indicate that most of the funds are invested in RAJA.JK and KEEN.JK stocks, which contribute more than 75% of the total investment portfolio]]>
<![CDATA[Calculation of Life Insurance Premiums with Markov Chain Applications for Patients with Pulmonary Tuberculosis Disease in Indonesia ]]>
<![CDATA[Putra, Fachrul Ananda]]>;
<![CDATA[Purba, Daniel Victorio Rudolfo]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 4 (2024): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v2i4.143
<![CDATA[This study aims to calculate the premium for Long Term Care (LTC) insurance on Annuity as A Rider Benefit products with a multi-status model. Pulmonary Tuberculosis is one of the major infectious diseases that contribute significantly to morbidity and mortality rates. Therefore, it is necessary to calculate insurance premiums that consider the health risks of sufferers. In this study, Markov chains are used to model the health status transition of individuals with Pulmonary Tuberculosis over time, considering several health states, such as healthy, sick, and dead. Tuberculosis epidemiological data in Indonesia is used to estimate the transition probabilities between health states. The case study used in this research is a 35-year-old man who participates in LTC insurance with a coverage period of 5 years. It is known that the value of compensation when a person dies is IDR 100,000,000. The interest rate used is 5%. The calculation results obtained annual premium for LTC insurance on Annuity as A Rider Benefit product is Rp294,333. Then the calculation of the annual net premium of this insurance is also calculated based on age and gender. When age increases, the premium will be greater, this is influenced by the greater chance of death when age increases. In addition, based on gender, it is found that the male premium is more expensive than the female gender. This is influenced by the chance of death of men is greater than women.]]>
<![CDATA[Pure Premium Modeling for Property Fire Insurance Using Monte Carlo Method ]]>
<![CDATA[Putri, Linda Damayanti]]>;
<![CDATA[Firdaus, Muhammad Rayhan]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 4 (2024): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v2i4.144
<![CDATA[Modeling pure premium of property fire insurance is an important aspect for insurance companies in managing risk. This article discusses the Monte Carlo method in modeling pure premium of property fire insurance. The Monte Carlo method is used to simulate various scenarios and loss factors due to property fire. Monte Carlo simulation offers an effective approach to modeling property fire risk. The results of this study are expected to provide an overview of the modeling of pure premium of property fire insurance and assist insurance companies in decision making and determining optimal premium prices.]]>
<![CDATA[Modeling of Car Insurance Premiums Using the Bayes Method with Poisson and Exponential Distributions ]]>
<![CDATA[Farida, Nur Rizky]]>;
<![CDATA[Hikmah, Siti Nur]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 4 (2024): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v2i4.145
<![CDATA[Car insurance is included in the general insurance category. Determination of general insurance premiums can be done through various approaches, one of which is the Bayes method used in this study. The Poisson distribution is chosen to model the frequency of claims, while the Exponential distribution is used to model the amount of claims. Insurance premiums are calculated by multiplying the expected frequency of claims by the expected amount of claims. Based on the results of the analysis of car insurance data using the Bayes method, it was found that the highest premium rates were for Mercedes brand vehicles, while the lowest rates were for Saab brand vehicles. The results of this calculation can be used by insurance companies as a reference in managing car insurance reserve funds.]]>
<![CDATA[Financial Distress Analysis of Companies Carrying Out Mass Layoffs Throughout 2023 using the Altman Z-Score Method, Springate Method, and Zmijewski Method ]]>
<![CDATA[Puspitasari, Laras Dwi]]>;
<![CDATA[Syifana, Hani]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 4 (2024): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v2i4.147
<![CDATA[This research aims to estimate the financial condition of four companies that will carry out mass layoffs throughout 2023 using three financial distress prediction methods, namely the Z-Score Altman method, the Springate method and the Zmijewski method. Secondary data was used sourced from the financial reports of each company from 2022 to 2023. The research results showed that financial performance was analyzed using the Z-Score Altman method, the Springate method and the Zmijewski method in four companies, namely PT Net Visi Media Tbk for the period 2022-2023 classified as having the potential to experience bankruptcy, PT GoTo Gojek Tokopedia Tbk for the 2022-2023 period is classified as having a high potential for bankruptcy, PT Bukalapak.com Tbk for the 2022-2023 period is classified as being in good health, and JD.com, Inc. (JD) for the 2022-2023 period is classified as having absolutely no potential for bankruptcy.]]>
<![CDATA[Analysis of Aggregated Claim Numbers with Geometric Distribution and Claim Sizes with Weibull Distribution Using Convolution Method ]]>
<![CDATA[Maharani, Asthie Zaskia]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 3 No. 1 (2025): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v3i1.178
<![CDATA[An insurance claim is a form of claim from the insured party to the insurer, in this case the insurance company, which is submitted when a disaster or event that causes loss occurs. This claim is based on an agreement contract in the form of an insurance policy that has been agreed upon by both parties. Claims that arise every time a risk occurs are known as individual claims, while the total of individual claims that occur during a certain insurance period is called an aggregate claim. Aggregate loss refers to the total loss that must be borne by the insurance company due to claims filed by policyholders in a certain period. This study aims to estimate the total aggregate claim (aggregate loss) by modeling the number of claims using the Geometric distribution and the size of the claim using the Weibull distribution. The research was conducted using simulated data from PT Insurance XYZ. The method used in this research is the convolution method, which allows the calculation of the distribution of total aggregated claims based on the pairwise multiplication of the probability density function. To support the analysis, Easyfit and R Studio software were used in data processing and simulation. The results showed that the estimated total aggregate claim (aggregate loss) for a 12-month period on the simulated data was IDR2,809,454,000 using the Geometric distribution for the number of claims and the Weibull distribution for the size of the claim. In addition, the variance value obtained from the simulation results is 5.051215e-06. These findings provide an important overview of the estimation of potential losses that must be borne by insurance companies and can be used as a reference in risk management and the establishment of a more optimal financial strategy.]]>
<![CDATA[Application of Expected Loss (EL) for Loan Loss Estimation Based on Loan Term Using Simulation Data ]]>
<![CDATA[Tenripada, Andi Sakinah Yan]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 3 No. 1 (2025): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v3i1.179
<![CDATA[This study aims to evaluate the effect of loan tenor on loan loss estimation using the Expected Loss (EL) model. Through this simulation data calculation, various scenarios with varying loan tenors show that loan tenors have a significant influence on the calculation of Expected Loss (EL). Longer tenors tend to increase the Expected Loss (EL) due to an increase in credit risk over time. The calculation results provide important implications for financial institutions in setting lending policies and managing credit risk.]]>
<![CDATA[Calculation of Value at Risk of Property Fire Losses in West Jakarta with the Extreme Value Theory Method ]]>
<![CDATA[Putri, Linda Damayanti]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 3 No. 1 (2025): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v3i1.180
<![CDATA[Property fires are an inevitable disaster, but their impact can be minimized through proper risk management. In urban areas such as West Jakarta, with high population density and economic activity, fires often cause losses. In therange of 2014 to 2023, the peak of the loss occurred in 2019 of IDR 103,354,500,000. Soto avoid unwanted things, it is necessary to calculate the losses that may occur. The Extreme Value Theory (EVT) method is used in this study to analyze the risk of extreme losses. Using Peaks Over Threshold (POT), the estimated value at Risk (VaR) shows a maximum loss of IDR 86,245,771,176 (95% confidence level) and IDR 255,535,153,859 (99% confidence level). These results help manage fire insurance risks to reduce future economic impacts.]]>
<![CDATA[Estimation Model of Pure Health Insurance Premiums in Southeast America Using Generalized Linear Model (GLM) with Gamma Distribution ]]>
<![CDATA[Putri, Aulya]]>
<![CDATA[ International Journal of Mathematics, Statistics, and Computing Vol. 3 No. 1 (2025): International Journal of Mathematics, Statistics, and Computing ]]>
Publisher : <![CDATA[Communication In Research And Publications ]]>
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DOI: 10.46336/ijmsc.v3i1.181
<![CDATA[Health insurance premiums are on the rise due to increasing medical costs, inflation, and the lingering effects of the COVID-19 pandemic. Accurate premium pricing is crucial for insurance companies to maintain financial stability and offer fair rates to policyholders. Generalized Linear Models (GLM) have been widely used in actuarial science for modeling insurance premiums. This study proposes the use of GLM with a Gamma distribution to model health insurance premiums. The Gamma distribution is suitable for non-negative and positively skewed data, which is characteristic of insurance claim amounts. By analyzing historical data from a Southeast United State insurance company, we aim to identify key factors influencing premium pricing and develop a robust premium model. The model will consider factors such as age, gender, BMI, number of children, and smoking status to predict individual risk profiles and determine appropriate premiums. Our findings indicate that age and smoking status are the most significant factors affecting premium rates. Older individuals and smokers tend to have higher premiums due to their increased risk of health issues. Gender and BMI, however, were found to have no significant impact on premium pricing in this specific dataset. Insurance companies can use the identified factors (age, smoking status, etc.) to create more precise risk profiles for their policyholders.]]>
