Article Per Year (5 Year)
p-Index From 2021 - 2026
8.581
P-Index
This Author published in this journals
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

Published : 72 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 72 Documents
Search

 4   5   6   7   8 
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.
Optimal Portfolio Using Roy’s Safety-First Method on Primary Consumer Goods Sector Stocks Estu Putri Dianti; 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.v5i1.641

Abstract

Before carrying out investment activities, investors need to form an optimal investment portfolio. This study aims to form an optimal portfolio in primary consumer goods sector stocks that sell the basic needs of the community so that stocks in the sector tend to be stable. The method used in forming the optimal portfolio is Roy's Safety-first method. The portfolio formed produces 6 combinations of stocks consisting of WIIM, DSNG, MRAT, CAMP, SIMP, and MBTO stocks respectively with a proportion of funds of 44.05%, 16.38%, 18.61%, 15.06%, 4.32%, and 1.59% with an expected return portfolio of 3.10% and a portfolio risk of 1.65%.
Comparison of Projected Unit Credit, Entry Age Normal, and Individual Level Premium Methods in Calculation of Normal Retirement on PNS Pension Funds Aulianda Anisa Putri S. R.; Dwi Susanti; Riaman Riaman
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.v5i2.692

Abstract

Every individual’s desire for a prosperous old age lead to the need for a pension fund program to ensure the welfare of every employee in their old age. The calculation of pension fund in this study was carried out using the Projected Unit Credit, Entry Age Normal and Individual Level Premium methods. This study aimed to determine the value of normal cost and actuarial liability using Projected Unit Credit method, Entry Age Normal method, and Individual Level Premium. Then the best method was determined based on the comparison results of the normal cost value and the actuarial liability value obtained using the three methods. The data used in this study is secondary data from PT Taspen (Persero) KCU Bandung. The results showed that the best method among the three methods studied was the Projected Unit Credit method because it produced the highest total normal cost with the lowest actuarial liability value each year.
Mean-Variance Optimal Portfolio Selection with Risk Aversion on Transportation and Logistics Sector Stocks Based on Multi-Criteria Decision-Making Aulya Putri; Riaman Riaman; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol. 6 No. 1 (2025): 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.v6i1.895

Abstract

The importance of the transportation and logistics sector to a country's economy, coupled with the growth of this sector in Indonesia, requires investment support for this sector to continue to grow. Therefore, stocks in the transportation and logistics sector are attractive for investment portfolio consideration. The optimal portfolio selection is to minimize the risk with the expected return. In the formation of an investment portfolio, the problem is how to determine the weight of capital allocation in order to get the maximum return while still considering the risk in each stock, by considering several criteria in decision making. This study was conducted to determine the best stock selection in the transportation and logistics sector listed on the Indonesia Stock Exchange, and determine the optimal weight in the investment portfolio. The method used is Multi-Criteria Decision Making (MCDM), namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) using 15 financial metrics as relevant criteria in stock selection. Furthermore, to determine the allocation weight to form an optimal stock portfolio using the Mean-Variance model with Risk Aversion. The stocks analyzed were 28 stocks in the transportation and logistics sector. The results of research based on MCDM selected 9 stocks, namely MITI, BIRD, HATM, TMAS, JAYA, PPGL, BPTR, ASSA, and RCCC. However, TMAS, PPGL, and BPTR stocks are not included in portfolio formation because they have a negative average return. Based on the optimization results, the allocation weights of the 6 stocks included in the optimal portfolio are BIRD (37.7%), JAYA (24.6%), MITI (12.9%), HATM (9.9%), ASSA (7.5%), and RCCC (7.4%). The results of this study are expected to be a consideration in making investment decisions.
Comparative Analysis of Normal Pension Benefits Using the Attained Age Normal Method and the Individual Level Premium Method Atha Hukama; Kankan Parmikanti; Riaman Riaman
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025): 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.v6i2.946

Abstract

Pension programs are among the most important forms of employee compensation, offering financial security after retirement. This study aims to calculate the company’s initial payroll contributions to determine regular contributions, actuarial liabilities, and pension benefits using two actuarial projection methods: the Attained Age Normal (AAN) and Individual Level Premium (ILP) methods. The analysis is based on employee data from Puskesmas Binjai Estate, including age, salary, and years of service. It includes computations of pension benefits, normal costs, actuarial liabilities, and net benefits received by employees under each method. The results reveal that the length of service significantly affects both the value of contributions and the actuarial liabilities. Employees with longer service periods result in higher contribution requirements and greater liabilities. Moreover, the Attained Age Normal method produces higher pension benefits compared to the Individual Level Premium method for long-serving employees. However, both methods present financial challenges for employers, as they require higher contributions relative to the benefits promised. Consequently, companies must allocate substantial funding to meet their pension obligations. This study provides a comparative perspective that can assist decision-makers in selecting an actuarial method that balances benefit adequacy and financial sustainability.
Analysis of the French Five Factors Fama Model on Excess Return of Stocks Listed on IDXBUMN20 for the Period 2020-2023 Linda Damayanti Putri; Riaman Riaman; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025): 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.v6i2.966

Abstract

Excess return is the difference between the rate of return earned on an investment and the rate of risk-free return in a given period. This shows how much return is received because they are willing to take risks in investing. This study aims to analyze the Fama French Five Factor model on the excess return of stocks listed in IDXBUMN20 2020-2023 period. The factors in the model are market factors, size factors, book to market ratio, profitability, and investment. The population in this study amounted to 20 companies registered in the IDXBUMN20 index, the sample selection in this study used the purposive sampling method and a sample of 12 companies was obtained. The data used in the study are close price, number of shares outstanding, Bank Indonesia (BI) interest rate, and company financial statements. The analysis method used was the Common Effect Model (CEM) panel data regression analysis. Based on hypothesis testing, market factors were obtained which only had an effect on excess returns. This factor shows the influence of the ups and downs of market performance on the price of a stock.
Investment Portfolio Optimization Using Genetic Algorithm on Infrastructure Sector Stocks Based on the Single Index Model Ayyinah Nur Bayyinah; Riaman Riaman; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025): 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.v6i2.977

Abstract

Investment is a strategic step in managing assets to gain profits in the future by allocating some funds in the present. However, behind the promising potential returns, investment also contains risks that cannot be ignored. One way to reduce the level of risk in investing is to implement a portfolio diversification strategy, which is to form an optimal portfolio by allocating investments to various stocks. This study aims to identify the stocks that form the optimal portfolio, determine the optimal weight of each stock, and calculate the expected return and risk of the portfolio. The portfolio optimization process is carried out using Genetic Algorithm, with the calculation of expected return and risk using the Single Index Model (SIM) approach. The data used includes data on stocks in the infrastructure sector for the period July 1, 2023 to June 30, 2024. The results showed that there were six stocks selected in forming the optimal portfolio with the weight of each stock: PGEO 15.0023%, ISAT 32.1522%, GMFI 4.7822%, EXCL 15.3236%, JSMR 29.7379, and OASA 3.0018%. This optimal portfolio provides an expected return of 0.1167% with a portfolio risk of 0.0152%.
Co-Authors AGUS SUPRIATNA Aldino Reisnanda Alit Kartiwa Anang Muhajirin Andhita Zahira Adib Annisa Aprillia Ariyanti, Devi 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 Dewi Ratnasari 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 Hidayana, Rizki Apriva Hukama, Atha Iin Irianingsih Jumadil Saputra Kahar, Ramadhina Hardiva kalfin Kalfin Kankan Parmikanti Khalilah Razanah Zakirah Komar Komar Laksito, Grida Saktian 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 Supian, Sudradjat Susanto, Sunarta Sya’imaa.HS, Audrey Ariij Tika Fauzia Tyrenia Rahmawati Ulfatmi, Ristifani Vimelia, Willen Wahid, Alim Jaizul Waway Tiswaya Widyani, Azizah Rini Willen Vimelia Yasir Salih Yasmin, Arla Aglia Yeremia Herry Parulian Yeremia Herry Parulian, Yeremia Herry Yudhi Andriyana Yulianus Brahmantyo Zahra, Ami Emelia Putri