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International Journal of Global Operations Research

ijgor
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Published by Indonesian Operations Research Association

ISSN : 27231747 EISSN : 27221016 DOI : https://doi.org/10.47194/ijgor

Core Subject : Economy, Science, Education, Engineering,

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

International Journal of Global Operations Research (IJGOR) is published 4 times a year and is the flagship journal of the Indonesian Operational Research Association (IORA). It is the aim of IJGOR 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. Topics Covered: Computational Intelligence Computing and Information Technologies Continuous and Discrete Optimization Decision Analysis and Decision Support System Applied Operations Research in Education Engineering Management Environment, Energy and Natural Resources Financial Engineering Applied Operations Research inGovernment Heuristics Industrial Engineering Information Management Information Technology Inventory Management Knowledge Management Logistics and Supply Chain Management Maintenance Manufacturing Industries Applied Operations Research in Marketing Engineering Markov Chains Mathematics Actuarial Sciences Military and Homeland Security Networks Operations Management Organizational Behavior Planning and Scheduling Policy Modeling and Public Sector Applied Operations Research inPolitical Science Production Management Applied Operations Research inPsychology Queuing Theory Revenue & Risk Management Services management Simulation Applied Operations Research inSociology Applied Operations Research inSports Statistics Stochastic Models Strategic Management Systems Engineering Telecommunications Transportation And so on

Arjuna Subject : Umum - Umum

Articles 174 Documents

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OPTIMIZATION OF PORTFOLIO PERFORMANCE ON THE JAKARTA ISLAM INDEX (JII) STOCK IN DECEMBER 2023 – MAY 204 USING THE MARKOWITZ MODEL Rohman, Aletta Divna Valensia; Fatimah, Siti
International Journal of Global Operations Research Vol. 5 No. 3 (2024): International Journal of Global Operations Research (IJGOR), August 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i3.322

This research aims to optimize the performance of a stock investment portfolio on the Jakarta Islamic Index (JII) during the period from December 2023 to May 2024, using the Markowitz model. This model minimizes portfolio risk by considering expected returns and covariance between stocks. Historical data on stock returns in the JII during the research period will be used to calculate expected returns and covariance. Furthermore, the Markowitz model will be used to determine the optimal investment proportion for each stock in the portfolio. The results of this research are expected to provide information to JII stock investors about the optimal combination of stocks to achieve maximum returns with controlled risk.

Exploring Interest Rate Models: Implications on Bond Value Measures in a Dynamic Financial Landscape Suharto, Istiqomah; Yuningsih, Siti Hadiaty
International Journal of Global Operations Research Vol. 5 No. 2 (2024): International Journal of Global Operations Research (IJGOR)m May 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i2.301

This paper investigates the impact of various one-factor no-arbitrage interest rate models on key bond value measures, specifically effective duration. Employing numerical methods based on binomial or trinomial lattices, the study assesses five prominent interest rate models: Ho and Lee, Kalotay, Williams, and Fabozzi, Black, Derman, and Toy, Hull and White, and Black and Karasinski.The analysis begins by outlining the theoretical foundations and assumptions underlying each model, highlighting their distinctive features and implications for bond valuation. Through a meticulous numerical solution process, the study generates risk metrics for bond portfolios, considering the dynamic nature of interest rates and the complex interactions between price, duration, and convexity.Comparisons across the models reveal nuanced differences in the computed effective duration and convexity measures, shedding light on how the choice of an interest rate model may influence risk assessments in fixed-income portfolios. The paper discusses practical implications for investors and portfolio managers, emphasizing the importance of model selection in navigating the challenges posed by interest rate fluctuations. Additionally, it addresses the potential limitations and challenges associated with each model, offering insights into their relative strengths and weaknesses.By presenting empirical examples and conducting sensitivity analyses, this research contributes to the ongoing discourse on interest rate modeling and its implications for bond markets. The findings offer valuable insights for practitioners seeking to enhance their risk management strategies in fixed-income investments, providing a foundation for future research in this dynamic and evolving field.

Balance Analysis of Operational Risk Through the Aggregate Method in the Loss Distribution Approach Amalia, Hana Safrina; Dhamayanti, Fildha; Salih, Yasir
International Journal of Global Operations Research Vol. 5 No. 2 (2024): International Journal of Global Operations Research (IJGOR)m May 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i2.306

Operational risk is defined as the risk of loss resulting from negligence or failure in an entity's internal processes or due to external problems. Companies (especially financial institutions) also face these risks. Recording operational losses in insurance companies is often not done correctly, resulting in limited data regarding operational losses. In this research, the focus is given to operational loss data recorded from claim payments. In general, the number of insurance claims can be resolved using a Poisson distribution, where the expected value of a claim is proportional to its variance. On the other hand, the negative binomial distribution has an expected value that is definitely smaller than its variance. The analytical method used to measure potential losses is through a loss distribution approach using the aggregate method. In this method, loss data is categorized into frequency distribution and severity distribution. By performing 10,000 simulations, a total claim loss value is generated, which is the accumulation of individual claims in each simulation. Then from the simulation results, the potential loss value (OpVaR) at a certain level of confidence is determined.

Citronella (Cymbopogon nardus (L.) Rendle) Leaves Infusion: Sedative Activity in Swiss-Webster Strain Male Mice Vitamia, Cszahreyloren; Handayani, Wahyuni Mega
International Journal of Global Operations Research Vol. 5 No. 1 (2024): International Journal of Global Operations Research (IJGOR), February 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i1.289

Insomnia is one of the sleep disorders and more severe symptoms can culminate in the onset of stress disorder. The high threat of being affected by COVID-19 causes insomnia, so drugs such as sedatives are required to treat this disorder. Research has been carried out on the sedative activity of infusion of citronella leaves (Cymbopogon nardus (L.) Rendle) in Swiss webster strains of male mice by the traction test method. The study used twenty-five mice randomly divided into five groups. Each group was given different preparations such as negative control given Na CMC 0.5%, the positive control group was given suspension of diazepam and the infusion group of citronella leaves with concentrations of 10% w/v, 30% w/v and 50% w/v as the test groups sequentially. The results showed that citronella leaves infusion had increased sedative activity along with in conjunction with an increment in test concentration. The infusion concentration of citronella leaves that have maximum sedative activity was found at a concentration of 50% w/v in the variations tested and have significantly different results compared to the control group.

Calculating Insurance Premiums for Stroke Patients Using the Multistate Markov Chain Method Aufhar, Ihkam Amalul; Fasya, Emir Shiddiq
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.333

Health insurance premium is one of the important elements in the insurance industry that needs to be calculated correctly so that insurance companies can minimize risks and losses. In this study, insurance premiums for stroke patients are calculated by utilizing the Markov Chain method. This method is used to model the movement of a patient's health condition over time, considering various conditions such as recovery, relapse, or death. Each condition is represented by a state in the Markov Chain model, and the transition between states is calculated based on patient history data and transition probabilities. Based on the modeling results, a more accurate premium estimation is obtained compared to conventional methods, as it is able to consider the dynamics of changing health conditions. This research provides important insights for the insurance industry in risk management as well as more optimal premium calculations for patients with chronic diseases such as stroke.

Bankruptcy Prediction Analysis of Life Insurance Companies Using Altman Z-Score dan Ohlson O-Score Methods Bayyinah, Ayyinah Nur; Helena, Putri Zahra
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.335

Life insurance is one of the non-bank industries that offers guarantees to overcome risks. In its implementation, life insurance companies need to maintain the survival of the company in the midst of increasing economic competition so that they don't face the threat of bankruptcy. Bankruptcy itself is a legal status of a certain entity or company that cannot pay its debts to creditors and the company's operations cannot be continued due to lack of funds. This study aims to compare the accuracy of the Altman Z-Score and Ohlson O-Score methods in predicting the bankruptcy of life insurance companies in Indonesia, such as PT Axa Financial Indonesia, PT Taspen Life, Asuransi Jiwa Bersama (AJB) Bumiputera 1912, PT Avrist Assurance, and PT Reliance Life Insurance Indonesia. The data used in this study is secondary data in the form of financial statements of life insurance companies taken from the official website of the relevant company. The results showed that the comparison between the two models revealed that the Altman method is better in predicting company bankruptcy. This is because the Altman method has a more detailed classification of conditions compared to the Ohlson method.

Bankruptcy Prediction Analysis of General Insurance Companies Using the Ohlson Model Maharani, Asthie Zaskia; Bisyarah, Sania
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.336

General insurance companies play an important role in maintaining economic stability by transferring financial risks from individuals and companies to insurance companies. However, insurance companies are not immune to the risk of bankruptcy that can arise due to factors such as inability to manage claims, premium fluctuations, and insufficient capital. Early detection of potential bankruptcy becomes very important to prevent greater losses. This study aims to analyze the prediction of bankruptcy in general insurance companies in Indonesia using the Ohlson Model. The Ohlson model is based on logistic regression, taking into account several financial variables such as leverage, profitability, and company size to estimate the probability of bankruptcy. The results of the study are expected to provide insights for insurance company management and regulators in identifying bankruptcy risks and taking appropriate preventive measures. In addition, this study contributes to enriching the literature related to the application of bankruptcy prediction models in the context of the insurance industry in emerging markets. From the analysis, it was found that out of 13 general insurance companies listed on the Indonesia Stock Exchange (IDX), the Ohlson value for all companies is below 0.38, which indicates that the sampled companies still have fairly good financial stability. The research results are expected to provide insights for insurance company management and regulators in identifying bankruptcy risks and taking appropriate preventive measures. In addition, this study contributes to enriching the literature related to the application of bankruptcy prediction models in the context of the insurance industry in emerging markets.

Analysis Automobile Insurance Fraud Claim Using Decision Tree and Random Forest Method Wicaksono, Ridwan Lazuardy Bimo; Rohman, Aletta Divna Valensia
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.337

Insurance fraud, particularly in the automobile sector, poses significant financial risks to insurance companies. This study aims to analyze fraudulent claims in automobile insurance using Decision Tree and Random Forest methods. A dataset consisting of 10,000 entries was utilized, containing variables such as vehicle type, claim amount, and claim status. The Decision Tree method was employed for its interpretability, while Random Forest was used for its superior accuracy. Results indicated that the Random Forest model outperformed the Decision Tree model, achieving an accuracy of 51.37% compared to 50.47%. This research highlights the effectiveness of machine learning techniques in detecting insurance fraud and provides insights for insurers to enhance their fraud detection systems.

Financial Distress Analysis of Companies Carrying Out Mass Layoffs Throughout 2023 using the Altman Z-Score Method, Springate Method, and Zmijewski Method Puspitasari, Laras Dwi; Syifana, Hani
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.338

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.

Performance Comparison of Ant Colony Optimization and Artificial Bee Colony in Solving the Capacitated Vehicle Routing Problem Setyawan, Deva Putra; Lianingsih, Nestia; Saputra, Moch Panji Agung
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.339

The Capacitated Vehicle Routing Problem (CVRP) is a combinatorial optimization problem widely applied in logistics and supply chain management. It involves determining the optimal routes for a fleet of vehicles with limited capacity to serve a set of customers with specific demands while minimizing travel costs. This study compares the performance of two popular metaheuristic algorithms, Ant Colony Optimization (ACO) and Artificial Bee Colony (ABC), in solving the CVRP. The research implements both algorithms on standard benchmark datasets, evaluating solution accuracy and computational efficiency. Simulation results indicate that ACO tends to excel in finding high-quality solutions, particularly for problems with high complexity, whereas ABC demonstrates superior computational efficiency on small- to medium-scale datasets. A detailed analysis of algorithm parameters was also conducted to understand their impact on the performance of both methods. This study provides valuable insights into the strengths and limitations of each algorithm in the context of CVRP and paves the way for the development of hybrid approaches in the future.

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Editorial Address Jl. Merkuri Timur VI No. 1, RT. 007, RW. 004, Manjahlega, Rancasari, Kota Bandung, Jawa Barat, INDONESIA

Location Kota bandung, Jawa barat INDONESIA

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Contact Name
-

Contact Email
ijgor.iorajournal@gmail.com

Phone
+6285841953112

Journal Mail Official
ijgor.iorajournal@gmail.com

Editorial Address
Jl. Merkuri Timur VI No. 1, RT. 007, RW. 004, Manjahlega, Rancasari, Kota Bandung, Jawa Barat, INDONESIA

Location
Kota bandung,

Jawa barat

INDONESIA