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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi JTAM (Jurnal Teori dan Aplikasi Matematika) Zero : Jurnal Sains, Matematika, dan Terapan Teorema: Teori dan Riset Matematika Jurnal Cendekia : Jurnal Pendidikan Matematika International Journal of Supply Chain Management FIBONACCI: Jurnal Pendidikan Matematika dan Matematika Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika International Journal of Business, Economics, and Social Development International Journal of Research in Community Services Operations Research: International Conference Series International Journal of Global Operations Research International Journal of Quantitative Research and Modeling International Journal of Ethno-Sciences and Education Research Euclid Jurnal Matematika Integratif In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Riaman Riaman
Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Padjadjaran
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Determining Pure Premium of Motor Vehicle Insurance with Generalized Linear Models (GLM) Tyrenia Rahmawati; Dwi Susanti; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 4 No. 4 (2023): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v4i4.492

Abstract

Motor vehicle insurance guarantees protection, coverage, and compensation for the risks of accidents, damages, and loss of motor vehicles. It is crucial for companies to determine appropriate insurance premium rates as a preventive measure to avoid difficulties in meeting claims filed by policyholders. This research aims to determine the pure premium of motor vehicle insurance using the Generalized Linear Models (GLM) method, which utilizes the concept of a general linear relationship between independent variables and the dependent/response variable, as well as identifying motor vehicle characteristics that influence the determination of pure premiums. The data used in this study is from Swedish motor vehicle insurance. The research aims to determine the pure premium in the data by modeling claim frequency using the Poisson distribution and claim severity using the Gamma distribution, depending on the significantly influential characteristics. The Maximum Likelihood Estimation method is employed for parameter estimation. After conducting the research, the estimated parameters , , and the pure premium of motor vehicle insurance are found to be 35,572,223.27 kr, with the characteristics influencing the pure premium being the distance traveled by the vehicle, the insured's geographic zone, and the no-claim bonus.
Application of Single Index Model to Determine Optimal Stock Portfolio (A Case Study on IDX30 in 2022) Emmanuel Parulian Sirait; Kankan Parmikanti; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 4 No. 3 (2023): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v4i3.493

Abstract

Stock represent proof of ownership or participation of an individual or entity in a company. Investors gain profits from shares through capital gains and dividends. The difficulty in selecting an optimal composition of a stock portfolio is a major concern for investors. This study aims to determine the optimal composition of a stock portfolio, calculate the expected returns in the future, and assess the potential risks that investors may encounter later on. The data for this research consists of stocks listed on the IDX30 Index throughout the year 2022, which consistently appear in every six-month evaluation. The analysis is conducted using a single-index model. Based on the findings of this study, the following ten stocks are identified as the optimal portfolio constituents: KLBF with a weight of 17.20%, BBRI with a weight of 17.18%, BBCA with a weight of 17.08%, PTBA with a weight of 12.46%, BBNI with a weight of 9.89%, UNVR with a weight of 8.33%, INKP with a weight of 8.66%, ICBP with a weight of 5.56%, BMRI with a weight of 3.25%, and UNTR with a weight of 0,39%. The expected return from the formed portfolio is 0,1% per day, with a corresponding risk of 0,004%.
Pricing of Aquaculture Industry Microinsurance Premiums with Standard Deviation Principle Approach (Case Study: Tasikmalaya) Anang Muhajirin; Dwi Susanti; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 4 No. 4 (2023): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v4i4.542

Abstract

Aquaculture is a rapidly growing industry and has enormous potential to increase the income and welfare of fish farmers. The majority of aquaculture businesses in Indonesia are small-scale cultivators, low productivity and limited business accessibility. As a result, there is an aquaculture industry that does not understand the use of aquaculture-specific financial risk management tools. Therefore, an insurance instrument is needed to manage losses that occur so as to achieve financial and income benefits, namely Micro Insurance. This study aims to calculate premium prices with a standard deviation principle approach. The data used is loss data if aquaculture cultivators do not pay in accordance with the initial capital in Tasikmalaya obtained through primary data based on the results of field surveys through questionnaires. The method of analyzing the number of event data uses the Poisson distribution, while the loss data uses the Exponential distribution. Next, calculate the parameter estimation using the Maximum Likelihood Estimation method. The results of parameter estimation are used to find a collective risk model. From the calculation results in this study, a premium price of IDR  was obtained.
Determination of Life Microinsurance Premium Using the Commercial Rate Method Azizah Rini Widyani; Riaman Riaman; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol. 4 No. 4 (2023): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v4i4.544

Abstract

Microinsurance is insurance that is intended for people who have low incomes which is made with the aim that all levels of society can have insurance with affordable prices. Life insurance is a protection program for families in the event of unwanted things, such as death or permanent disability, to policy holders. This study aims to determine the life microinsurance premium. The data sample used is data on claim and benefit paid by life insurance company obtained from the official website of Otoritas Jasa Keuangan (OJK) Indonesia, which is assumed to have a log-normal distribution. The research method is to test the distribution of claims from the sample data using the Kolmogorov-Smirnov test. Then determine the value of the claim distribution parameter, and then calculating life microinsurance premium using the Commercial Rate method. The results obtained in the form of premium for life microinsurance that are payable by low-income people.
Analysis of Pet Owners' Willingness to Pay for Pet Insurance Premiums in DKI Jakarta Using Logistic Regression Model Andhita Zahira Adib; Riaman Riaman; Betty Subartini
International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i2.578

Abstract

Pets provide many benefits to their owners, both physically and mentally. Pet lovers are increasingly aware of the importance of proper health and care for their beloved animals. This has led pet enthusiasts to consider pet insurance. In participating in insurance, there are factors that influence the willingness of pet owners to pay premiums. The objective of this research is to determine the premium for pet insurance and analyze the factors influencing the Willingness To Pay (WTP) of pet owners. This study utilizes choice modeling format by conducting surveys to identify the factors influencing the purchase of pet insurance. Subsequently, binary logistic regression model analysis using the Maximum Likelihood Estimation (MLE) method and the Newton-Raphson Iteration approach is employed to analyze the factors influencing the magnitude of WTP. The research results show that the average willingness to pay for pet insurance premiums is IDR128,574.76 per year. Factors influencing the decision of pet owners include the number of family dependents and awareness of the importance of participating in pet insurance. The likelihood of cat owners being willing to pay pet insurance premiums is 0.8691 or 86.91%.
Calculation of Term Life Insurance Premium Reserves with Fackler Method and Canadian Method Khalilah Razanah Zakirah; Betty Subartini; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 5 No. 1 (2024): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i1.589

Abstract

Every individual around the world goes through the life cycle of birth and continues their journey with unique experiences. The uncertainty of the future, which includes both happiness and calamity, is a universal aspect of human life. Life risks, such as illness and death, are an unavoidable reality for every individual in this world. Life insurance is one of the solutions to manage these risks, with term life insurance being one of the options. The focus of this research lies on term life insurance, with the aim of calculating premium reserves using the Fackler and Canadian methods. This research is concerned with the process of calculating premium reserves, and the results show that the Fackler method produces a larger premium reserve value compared to the Canadian method. Recommendations are given to companies to use the Fackler Method in calculating term life insurance premium reserves to avoid potential losses that could occur if using the Canadian method. The choice of premium calculation method is a strategic key in effective risk management for the company.
Optimal Portfolio Using Single Index Model (SIM) For Health Sector Stocks Silvia Wijaya; Betty Subartini; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 5 No. 1 (2024): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i1.591

Abstract

Investment is one of the fund management activities with the aim of obtaining future profits. In addition to profits, investors also need to consider the risks that will be faced by diversifying. Diversification is done by forming an optimal portfolio. This research aims to determine the proportion of stocks in the optimal portfolio and calculate the expected return and risk value of the optimal portfolio. The object used to form the optimal portfolio is health sector stock group for the period January 2020 - December 2022. The method used to form the optimal portfolio is Single Index Model (SIM). The results showed that there were 6 combinations of health sector stock in the optimal portfolio, such as IRRA, PRDA, SAME, SILO, MERK, and HEAL stocks of 8.94%, 9.24%, 9.34%, 11.92%, 27.15%, and 33.41% respectively with expected return of 2.68% and a risk value of 1.85%.
Comparison of the Zillmer Method with the Adjusted Ohio Method in Calculation of Premium Reserve Value in Dwi-Purpose Life Insurance Aldino Reisnanda; Betty Subartini; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 5 No. 1 (2024): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i1.592

Abstract

Life insurance is one of protections in society by providing economic protection for insurance users who experience an adverse event. The insured who is an insurance user has an obligation to pay the premium at the time that is determined by the insurance company and the policyholder. Insurance companies need funds to fulfill claims from policyholders, so premiums that have been paid are stored in the form of premium reserves. Premium reserves need to be managed by the company properly so that the company does not experience losses. The purpose of this research is to provide information to determine the appropriate value of premium reserves in dual-life insurance. In this study, the calculation of premium reserves is done using the Zillmer Method and the adjusted Ohio Method, with the Prospective Method as the basis for the calculation. Based on the research results of premium reserve calculations in this study, both the Zillmer method and the Ohio method show premium reserve values that are directly proportional to the policyholder’s age. The premium reserve calculations also indicate that the Zillmer method and the Ohio method yield the same results when the insurance coverage period ends. However, there is a significant difference in the premium reserve calculations at the beginning of the insurance coverage period.
Investment Portfolio Optimization in Renewable Energy Stocks in Indonesia Using Mean-Variance Risk Aversion Model Willen Vimelia; Riaman Riaman; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol. 5 No. 1 (2024): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i1.601

Abstract

Climate change is a phenomenon that has been occurring for quite some time. However, the increasingly felt impacts of climate change necessitate human action to mitigate these effects. One way to address this issue is by transitioning from conventional or non-renewable energy sources to renewable energy. This step undoubtedly has implications for various aspects, such as investments. Naturally, investors are beginning to turn their attention to the field of renewable energy as a new target. Investments are inherently associated with risks and returns One approach to maximizing returns is through portfolio optimization. One well-known method in portfolio optimization is the Mean-Variance method, also known as the Markowitz method, as it was first introduced by Harry Markowitz. In this research, an optimal portfolio is generated with weights of 0.1470 for ADRO; 0.1939 for MEDC; 0.2143 for ITMG and 0.4449 for RAJA. With this composition of optimal portfolio weights, the expected return is obtained at 0.002252, and the return variance is 0.000496.
Investment Portfolio Optimization In Infrastructure Stocks Using The Mean-VaR Risk Tolerance Model Arla Aglia Yasmin; Riaman Riaman; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol. 5 No. 1 (2024): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i1.602

Abstract

Infrastructure a crucial role in economic development and the achievement of Sustainable Development Goals (SDGs), with investment being a key activity supporting this. Investment involves the allocation of assets with the expectation of gaining profit with minimal risk, making the selection of optimal investment portfolios crucial for investors. Therefore, the aim of this research is to identify the optimal portfolio in infrastructure stocks using the Mean-VaR model. Through portfolio analysis, this study addresses two main issues: determining the optimal allocation for each infrastructure stock and formulating an optimal stock investment portfolio while minimizing risk and maximizing return. The methodology employed in this research is the Mean-VaR approach, which combines the advantages of Value at Risk (VaR) in risk measurement with consideration of return expectations. The findings indicate that eight infrastructure stocks meet the criteria for forming an optimal portfolio. The proportion of each stock in the optimal portfolio is as follows: ISAT (2.74%), TLKM (33.894%), JSMR (3.343%), BALI (0.102%), IPCC (5.044%), KEEN (14.792%), PTPW (25.863%), and AKRA (14.219%). The results of this study can serve as a foundation for better investment decision-making.
Co-Authors AGUS SUPRIATNA Aldino Reisnanda Alim Jaizul Wahid Alit Kartiwa Anang Muhajirin Andhita Zahira Adib Annisa Aprillia Ariyanti, Devi Arla Aglia Yasmin Arla Aglia Yasmin Ary Robayani Asthie Zaskia Maharani Atha Hukama Aulianda Anisa Putri S. R. Aulya Putri Ayyinah Nur Bayyinah Azizah Rini Widyani Bayyinah, Ayyinah Nur Betty Subartini Betty Subartini Betty Subartini Betty Subartini Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Edi Kurniadi Emmanuel Parulian Sirait Estu Putri Dianti Ghazali, Puspa Liza Hasbullah, Soeryana Herlina Napitupulu Hukama, Atha Iin Irianingsih Jumadil Saputra Kahar, Ramadhina Hardiva kalfin Kalfin Kankan Parmikanti Khalilah Razanah Zakirah Komar Komar Linda Damayanti Putri Luki Setiawan Luki Setiawan Lutfi Praditia Ma’mur Maharani, Asthie Zaskia Ma’mur, Lutfi Praditia MIFTAAHUL JANNAH Moisino, Misel Lindi Nahda Nabiilah Noriszura Ismail Novianti, Saqila Pramudhita, Annisa Pryimak, Evgen Putri Adhira Novalia Putri Chaerunnisa Febryanti Putri, Aulya Putri, Linda Damayanti Qurrotu Aini Radya Pratiwi Serila Raharjanti, Amalia RAHMAWATI, SEPTI Ramdhania, Tya Shafa Ratih Kusumadewi Riadi, Nadia Putri Riza Adrian Ibrahim Saefullah, Rifki Silvia Wijaya Soeryana Hasbullah Subartiny, Betty Sudartianto Sudartianto Sukono Sukono Sukono Sukono Supian, Sudradjat Susanto, Sunarta Sya’imaa.HS, Audrey Ariij Tika Fauzia Tyrenia Rahmawati Ulfatmi, Ristifani Widyani, Azizah Rini Willen Vimelia Willen Vimelia Yasir Salih Yeremia Herry Parulian Yeremia Herry Parulian, Yeremia Herry Yudhi Andriyana Yulianus Brahmantyo Zahra, Ami Emelia Putri