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Operations Research: International Conference Series
Published by Indonesian Operations Research Association
ISSN : 27231739     EISSN : 27220974     DOI : https://doi.org/10.47194/orics
Core Subject : Economy, Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics
Operations Research: International Conference Series (ORICS) is published 4 times a year and is the flagship journal of the Indonesian Operational Research Association (IORA). It is the aim of ORICS to present papers which cover the theory, practice, history or methodology of OR. However, since OR is primarily an applied science, it is a major objective of the journal to attract and publish accounts of good, practical case studies. Consequently, papers illustrating applications of OR to real problems are especially welcome. In real applications of OR: forecasting, inventory, investment, location, logistics, maintenance, marketing, packing, purchasing, production, project management, reliability and scheduling. In a wide variety of environments: community OR, education, energy, finance, government, health services, manufacturing industries, mining, sports, and transportation. In technical approaches: decision support systems, expert systems, heuristics, networks, mathematical programming, multicriteria decision methods, problems structuring methods, queues, and simulation.
Arjuna Subject : Umum - Umum
Articles 125 Documents
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Calculation of Motor Vehicle Insurance Premiums Through Evaluation of Claim Frequency and Amount Data Bagariang, Elizabeth Irene; Raharjanti, Amalia
Operations Research: International Conference Series Vol. 4 No. 4 (2023): Operations Research International Conference Series (ORICS), December 2023
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v4i4.270

Abstract

Insurance, as a risk control strategy by transferring the burden of risk from one party to another, consists of two main forms: life insurance, which covers financial losses from the risk of death of the policyholder, and general insurance, which involves the transfer of risk against property losses. Motor vehicle insurance has become a common product reflecting the high value and benefits of motor vehicles, which has resulted in an increase in vehicle ownership. Although the increase in the number of vehicles contributes to the increase in road accidents, many owners who suffer losses do not receive the compensation they deserve. In this context, the premium becomes a key factor, where the policyholder pays a certain amount of money to get protection. This research aims to apply risk premium calculation based on claim frequency and claim size data, as conducted by Ozgurel in 2005, especially for each vehicle category and region in XYZ insurance company. The main problem is to optimize the premium calculation to reflect the actual risk, providing a more accurate understanding of the influence of vehicle and regional characteristics in determining a fair and appropriate premium.
Actuarial Calculation of Pension Funds Using Attained Age Normal (AAN) at PT Taspen Cirebon Branch Office: For Normal Pension Amalia, Hana Safrina; Subartini, Betty; sukono, sukono
Operations Research: International Conference Series Vol. 5 No. 3 (2024): Operations Research International Conference Series (ORICS), September 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i3.332

Abstract

The pension program for Civil Servants (PNS) in Indonesia is managed by PT Taspen (Persero), which is responsible for ensuring the welfare of employees after retirement. One of the important components in the management of this pension fund is the actuarial calculation, which serves to determine the amount of normal contributions that must be paid by participants and the actuarial obligations that are the company's dependents. This calculation uses the right actuarial method to maintain the financial stability of the company and ensure that pension benefits can be optimally provided to participants. This study focuses on the use of the Attained Age Normal (AAN) method in calculating pension funds for pension program participants at PT Taspen Cirebon Branch Office. In addition, this study also compares the results of the AAN method calculation with another method, namely Projected Unit Credit (PUC), to see the advantages and disadvantages of each method. The AAN method calculates liabilities based on the current age of the participant, thus providing more conservative results and tending to be stable in the long term. The results showed that the AAN method produced a higher total normal contribution compared to the PUC method. Normal contributions calculated by the AAN method for participants of the PT Taspen pension program at the Cirebon Branch Office showed an increase of 2,095,355.33 rupiah at the age of 32 years. On the other hand, the PUC method produces a lower normal contribution, which is 827,843.62 rupiah for the same age. In terms of actuarial obligations, the AAN method also shows a more significant increase than PUC. These results show that the AAN method is more stable in the calculation of actuarial liabilities, although it requires larger contributions. Thus, although the Attained Age Normal (AAN) method results in higher normal contributions, it provides better assurance in maintaining the company's financial balance in the long term. This study provides a recommendation that PT Taspen can consider the AAN method as a more conservative alternative in pension fund management.
Enhancing Risk Management Strategies: GAM Analysis of Health Insurance Claim Determinants Wahyu, Azkanul; Ramdhani, Muhammad Dhafin Qinthar
Operations Research: International Conference Series Vol. 5 No. 1 (2024): Operations Research International Conference Series (ORICS), March 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i1.277

Abstract

Health insurance plays a crucial role in providing financial protection and ensuring access to necessary healthcare services. The awareness of Indonesian society regarding the importance of health insurance continues to grow, as evidenced by a 22% increase in premium income according to AAJI data as of March 2023. Despite the benefits of health insurance, an increasing number of insurance participants raises risks for insurance companies. The Generalized Additive Models (GAM) P-Spline can overcome these problems. The non-linear relationship between claim amount with age, body mass index, and blood pressure can be modelled with GAM P-Spline. The formed GAM model with PIRLS unable to give a clear information of relationship between variables explicitly, but can be seen by the shape of the function of each predictor associated with the link function used.
Life Insurance Aggregate Claims Distribution Model Estimation Yohandoko, Setyo; Prabowo, Agung; Yakubu, Usman Abbas; Wang, Chun
Operations Research: International Conference Series Vol. 4 No. 4 (2023): Operations Research International Conference Series (ORICS), December 2023
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v4i4.271

Abstract

Risk is a hazard or consequence that can occur in an ongoing process or future events. As the party responsible for assuming and managing risks, the insurance company must be prepared to provide compensation in the event of claims; otherwise, they may face bankruptcy. Hence, it is important to understand the characteristics of risks handled by the insurance company. The risk's characteristics can be analyzed through the distribution model of previous-period claims. The sum of aggregate claims over several periods forms the aggregate claims distribution. The aggregate claims distribution used to determine the amount of pure premium and gross premium that must be obtained by the insurance company. In this research, the determination of distribution model estimation was examined for data cases on aggregate claims of life insurance in Indonesia 2016-2020. The result of this research conduct that the appropriate distribution model is the inverse Gaussian 3P distribution (three parameters).
Determination of Insurance Premium Rates with Aggregation Claims at BPJS with Exponential and Gamma Distributions Zakirah, Khalilah Razanah; Banowati, Puspa Dwi Ayu
Operations Research: International Conference Series Vol. 5 No. 3 (2024): Operations Research International Conference Series (ORICS), September 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i3.329

Abstract

Badan Penyelenggara Jaminan Sosial (BPJS) is a legal entity that has been provided by the government for the community with the aim of providing protection for all workers in Indonesia from certain socio-economic risks. National development, marked by planned and continuous strides, embodies a commitment to engage all societal, national, and state levels in fostering progress. Encompassing political, economic, socio-cultural, and defense and security realms, the development is meticulously designed to be comprehensive, targeted, integrated, gradual, and sustainable. The overarching objective is to catalyze an augmentation of national capabilities, align the standard of living for the Indonesian people with developed nations, and elevate overall welfare. To establish premium rates, a method involves multiplying the conditional expected value of claim frequency by the size of the claim, considering observed risk characteristics. A claim, in this context, constitutes a formal request to the insurance company, seeking payment in accordance with the terms of the agreement. The primary objective of this study is to establish the insurance premium rates applicable to policyholders (the insured) through the estimation of parameters in the distribution governing aggregate claims. This involves the distribution of both the number of claims and the size of the claims, and the estimation is performed using the moment method. Premium computations are executed based on two key principles: the pure premium principle and the expected value principle. This research produces the conclusion that the Poisson-Gamma aggregate claims distribution has a premium amount of 3.61 times greater than Poisson-Exponential due to the application of the anticipated value principle, namely IDR 4,403,542.94 per month and IDR 1,219,878.45 per month, respectively.
Implementing the Variance-Covariance Method for Assessing Market Transaction Risks in Raw Material Sector Stocks Kisti, Vuji Annisa; Haq, Fadiah Hasna Nadiatul; Hidayana, Rizki Apriva
Operations Research: International Conference Series Vol. 5 No. 2 (2024): Operations Research International Conference Series (ORICS), June 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i2.310

Abstract

The capital market plays a crucial role in supporting a country's economic growth. Besides being a funding source, the capital market also serves as an investment avenue for investors, particularly through stocks. Every investor must be willing to bear risks in line with their targeted returns. Risk is defined as the uncertainty of future outcomes due to market condition changes, and VaR (Value at Risk) is used to determine the tolerated loss at a certain confidence level. This study discusses the application of the Value at Risk (VaR) method using the Variance-Covariance approach to mitigate market risks in the portfolio of raw material sector stocks. The study focuses on two raw material sector stocks in Indonesia, assuming a normal distribution of asset price changes. The measurement results indicate that with an investment of Rp. 100,000,000.00, a 95% confidence level, and a 1-day period, the VaR of the portfolio of these five stocks is Rp. 2,769,750.00. This research provides critical insights to assist investors in understanding and managing portfolio risks, making VaR a key indicator to measure potential future risks and laying the foundation for decision-making in risk management.
Optimal Portfolio Risk Analysis Using the Monte Carlo Method Kahar, Ramadhina Hardiva; Kaerudin, Nandira Putri; Vimelia, Willen
Operations Research: International Conference Series Vol. 4 No. 4 (2023): Operations Research International Conference Series (ORICS), December 2023
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v4i4.276

Abstract

Investment is an activity carried out with the expectation of gaining profits in the future through the management of investment assets. Investment assets can include buildings, gold, and stocks. Investment activities are inseparable from the concepts of return and risk. The relationship between the expected rate of return and the level of risk is linear. However, risk can be avoided or reduced through portfolio diversification. Evaluating investment risk is crucial for investors to determine which risky assets to choose. One popular method for assessing the risk of a portfolio is using Value at Risk (VaR). In VaR calculations, Monte Carlo is considered the most effective method. In this paper, a risk analysis of the optimal portfolio is conducted using the Monte Carlo method. The analyzed optimal portfolio consists of shares in BBCA, TLKM, BBRI, BBNI, BMRI, ADRO, GGRM, and UNTR. The results indicate that the potential loss for the investor is no more than IDR 705.634,- with an initial fund of 1 billion. 
The Estimation of relationship between actuarial rate of return, Maturity and Coupon: The case of Tunisia Elmguirhi, Sonia
Operations Research: International Conference Series Vol. 5 No. 3 (2024): Operations Research International Conference Series (ORICS), September 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i3.318

Abstract

The aim of this paper is to study the Estimation of the relationship between the actuarial rate of return, Maturity and Coupon issued by the Tunisian banking and financial institutions knowing that it is a significant component of financing. So, this relationship issue is an essential link of investments. The studying of yield bond is an important first step. For many types of financial research. To  date, this research has focused on the bond yield for institutions, with the exception of works by institution, financial and banking. There regression models are tested by different methods. The first model is based only on relationship between Actuarial Rate of Return, maturity and coupon. The other models are prominent in the published literature on the bond yield.
The Application of Mathematical Analysis in Investment Planning Umar, Ridwan Hasyim; Amirudin, Zidan
Operations Research: International Conference Series Vol. 5 No. 1 (2024): Operations Research International Conference Series (ORICS), March 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i1.293

Abstract

Investment serves as a means to cultivate assets and secure long-term profits. However, inadequate investment planning poses a substantial risk of significant losses. Consequently, precise analysis becomes imperative for making intelligent investment decisions. One effective analytical approach involves the application of mathematical concepts in investment planning. This article conducts a comprehensive review of existing literature pertaining to the utilization of mathematical analysis in investment planning. Common mathematical concepts employed in investment analysis encompass probability theory, statistics, portfolio theory, and options theory. Probability theory and statistics aid investors in comprehending and forecasting potential gains and losses from specific investments. The primary objective of investment planning is profit maximization through effective risk management, necessitating a mature and structured analysis. Mathematical analysis emerges as a valuable method, and its application in investment planning yields more accurate and efficient results. Techniques such as statistical analysis, portfolio theory, and probability analysis contribute to risk minimization and return maximization by considering factors like asset correlation and risk levels. Thus, the incorporation of mathematical analysis proves crucial for well-structured and successful investment planning. The fifth entry in the bibliography emphasizes the importance of careful and planned analysis in making investment decisions. Economic and financial factors affecting market and investment performance are explored, along with portfolio risk diversification techniques and investment control. The article underscores the significance of understanding investment objectives and investor profiles while discussing various investment instruments such as stocks, bonds, and mutual funds. Overall, the article provides insights into managing investment portfolios effectively for optimal profitability.
Analysis of Risk Factors for Dengue Hemorrhagic Fever in Riau Province using Negative Binomial Regression Rangkuti, Aisyah Azhari; Sirait, Haposan
Operations Research: International Conference Series Vol. 4 No. 4 (2023): Operations Research International Conference Series (ORICS), December 2023
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v4i4.280

Abstract

Dengue Hemorrhagic Fever (DHF) is a serious threat in Riau province, Indonesia. To better understand and control the spread of dengue fever, this research aims to analyze the factors that cause dengue fever. This study aims to identify significant risk factors that influence the spread of dengue fever in Riau Province. The Negative Binomial Regression Method was used to identify factors associated with the increase in dengue fever cases in Riau. The variables evaluated include population density of the Aedes aegypti vector , level of environmental cleanliness, prevention practices, and socio-economic factors. In addition, the best model was selected to overcome overdispersion in the data. The results of the analysis show that factors such as population density of the Aedes aegypti vector , environmental cleanliness, and the level of public understanding about dengue prevention practices have a significant influence on the spread of dengue fever in Riau. The best model used to overcome overdispersion in the 2021 dengue fever case data in Riau is Negative Binomial Regression. This research provides a deeper understanding of the factors causing dengue fever in Riau and selects an appropriate statistical model for analyzing data that experiences overdispersion. Negative Binomial Regression proved to be more appropriate in overcoming the problem of overdispersion in the data. These results can be used as a basis for designing more effective dengue prevention and control strategies and provide guidance for more targeted interventions in fighting dengue fever in this region.

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