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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 6 Documents
 1 
Search results for , issue "Vol. 4 No. 4 (2023): Operations Research International Conference Series (ORICS), December 2023" : 6 Documents clear
Comparison of K-Medoids and Clara Algorithm in Poverty Clustering Analysis in Indonesia Ardini, Ananda Rizki Dwi; 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.v4i4.279

Abstract

The Covid-19 pandemic entered Indonesia in March 2020, so the government imposed restrictions on people's movement in various regencies. The imposition of restrictions on people's movement will have an impact on the economy to the point of poverty. Poverty is influenced by several factors such as population, health, education, employment and economic factors. The poverty of a district/city in Indonesia is grouped to assist the government in alleviating poverty more efficiently. The process of grouping data in data mining is to group districts/cities in Indonesia based on factors that affect poverty with the K-Medoids and CLARA algorithms, then compare the two methods based on the average value of the ratio of the standard deviations. The variables used in this study consist of 4 variables, namely human development index (HDI), gross regional domestic product (GRDP), unemployment rate, and population density. The results of this study indicate that using the K-Medoids obtained 2 clusters, while using the CLARA algorithm obtained 3 clusters. Based on the results of grouping the two algorithms, the best algorithm was obtained using cluster validation, namely the CLARA algorithm because it has the average value of the ratio of the smallest standard deviation of 0.106. 
Pricing of Fisheries Microinsurance Premiums using the Poisson-Exponential Aggregate Distribution Approach Fadhilah, Dila Nur; Shahla, Raynita
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.v4i4.272

Abstract

Engaged in pond aquaculture is currently an attractive choice amid the high demand for fish in the market. Entrepreneurial opportunities in the pond fish farming sector are increasingly open, although the risk of crop failure remains, both due to weather factors and livestock processes. Crop failure can have a significant financial impact on pond fishery farmers. Therefore, there is a need for special insurance to protect against financial losses due to risks that can occur, namely Micro Fisheries Insurance. Microinsurance is a type of insurance product specifically designed for people with low income levels, offers features and administration that is simple, easily accessible, has an economical price, and a fast compensation settlement process. The focus of this study is to calculate premium prices by applying an aggregate risk model approach. The data used are the number of events and the magnitude of losses due to crop failure in shrimp pond cultivation in Pandeglang Regency in the period January 1, 2019-January 1, 2021. Data on the number of events follow the Poisson distribution, while data on the magnitude of losses follow the Exponential distribution. Next, it uses the Maximum Likelihood Estimation (MLE) method to calculate parameter estimation. The average and variance of aggregate risk is used to determine the size of the premium. The premium selection results in this study amounted to Rp42,005,600. The amount of the premium reflects the collective premium resulting from the calculation based on the standard deviation principle.
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.
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).
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. 
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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