International Journal of Quantitative Research and Modeling
International Journal of Quantitative Research and Modeling (IJQRM) is published 4 times a year and is the flagship journal of the Research Collaboration Community (RCC). It is the aim of IJQRM to present papers which cover the theory, practice, history or methodology of Quatitative Research (QR) and Mathematical Moodeling (MM). However, since Quatitative Research (QR) and Mathematical Moodeling (MM) are 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 Quatitative Research (QR) and Mathematical Modeling (MM) to real problems are especially welcome. In real applications of Quatitative Research (QR) and Mathematical Moodeling (MM): forecasting, inventory, investment, location, logistics, maintenance, marketing, packing, purchasing, production, project management, reliability and scheduling. In a wide variety of environments: community Quatitative Research (QR) and Mathematical Moodeling (MM), 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 Computational Intelligence Computing and Information Technologies Continuous and Discrete Optimization Decision Analysis and Decision Support Mathematics Education Engineering Management Environment, Energy and Natural Resources Financial Engineering Heuristics Industrial Engineering Information Management Information Technology Inventory Management Logistics and Supply Chain Management Maintenance Manufacturing Industries Marketing Engineering Markov Chains Mathematics Actuarial Sciences Big Data Analysis Operations Research Military and Homeland Security Networks Operations Management Planning and Scheduling Policy Modeling and Public Sector Production Management Queuing Theory Revenue & Risk Management Services Management Simulation Statistics Stochastic Models Strategic Management Systems Engineering Telecommunications Transportation Risk Management Modeling of Economics And so on
Articles
236 Documents
<![CDATA[Best Distribution Selection in Modeling the Interest Rate as a Random Modifier ]]>
<![CDATA[Kusumawati, Fajry Ayu]]>;
<![CDATA[Prabowo, Agung]]>;
<![CDATA[Br. SB, Agustini Tripena]]>;
<![CDATA[Laksito, Grida Saktian]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i2.683
<![CDATA[The interest rate is seen as a random variable because the interest rate has an unpredictable nature or changes over time. This means that the interest rate cannot be anticipated in the future with a certain degree of certainty. Therefore, mathematical models are needed to predict the behavior and value of future interest rates. The models used in this study were interest rate, uniform distribution , and lognormal distribution. The data used in the study were interest rate data for 2014-2015 and sample data for uniform distribution. The resulting model in interest rate modeling as a random variable uses for uniform and lognormal distributions with the application of data and . The interest rate model as a uniformly distributed random variable is considered better with a smaller standard deviation, , and values compared to the lognormal distribution based on the data used.]]>
<![CDATA[Comparison of Agricultural Insurance Premium Prices Based on Rainfall Index and Based on Corn Commodity Production Prediction Index in Grobogan District ]]>
<![CDATA[Rosady, Tiara]]>;
<![CDATA[Prabowo, Agung]]>;
<![CDATA[Guswanto, Bambang Herdriya]]>;
<![CDATA[Saputra, Jumadil]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i2.684
<![CDATA[In running an agricultural business, there is a big risk because farmers' productivity is very dependent on nature, and to reduce the risk of crop failure, the government provides a program to minimize losses from crop failure, namely agricultural insurance, through Law Number 19 of 2013 . This article aims to compare agricultural insurance premium prices based on the rainfall index and the production prediction index for corn commodities in Grobogan Regency. The results of this article are based on the reference used of 3% of compensation, namely IDR 344,872.5, and the results that are close to the reference are the price of insurance premiums based on the 5th simple average method corn production prediction index of IDR 356,433.58 . However, the premium price used as a reference previously was the gross premium price from AUTP, so the insurance premium price for Corn Farmers (AUTJ) was obtained, namely IDR 310,385.25. As a result, we obtained premium price results that were closest to the reference from AUTJ, namely at the 4th percentile, when the agricultural insurance premium price based on the rainfall index was IDR 330,155.76 per planting season.]]>
<![CDATA[Calculation of Motor Vehicle Insurance Premiums by using the Moment Method to Estimate the Aggregate Claim Model ]]>
<![CDATA[Alfaridzi, Sultan Izbik Riska]]>;
<![CDATA[Prabowo, Agung]]>;
<![CDATA[Nurhayati, Nunung]]>;
<![CDATA[Halim, Nurfadhlina Abdul]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i2.685
<![CDATA[The aggregate claim model is a model that can be used to determine the amount of premium billed to the insured by the insurance company. This model consists of a combination of two independent random variables, namely the number of claims that occur and the size of the claim for each claim submitted. In this study, many claims are Poisson distributed and the size of the claim is exponentially distributed. The method of moments is used to estimate the parameters of each distribution. Based on the calculation results, the amount of premium billed to the insured for one year if based on the pure premium principle is Rp. 112,500,000.00 and if based on the expected value principle, variance value principle, and standard deviation principle is Rp. 165,900,000.00.]]>
<![CDATA[Forecasting Indonesian Stock Index Using ARMA-GARCH Model ]]>
<![CDATA[Susanti, Dwi]]>;
<![CDATA[Labitta, Kirana Fara]]>;
<![CDATA[Sukono, Sukono]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i2.686
<![CDATA[The stock market is an institution that provides a facility for buying and selling stocks. Covid-19 is an issue that has affected the stock markets of many countries, including Indonesia. Due to the pandemic, the condition of stocks before and during Covid-19 is certainly different. Stocks can be measured using stock indices. To predict future stock conditions, it is necessary to forecast the stock index. This research aims to predict the Indonesian stock index in the before and during Covid-19 period, using ARMA-GARCH time series model. According to the results obtained for before Covid-19 data, the best predictive model is the ARMA(0,2)-GARCH(1,0), and for the data during Covid-19, it is ARMA(3,3)-GARCH(3,3). Since the MAE is close to zero, it indicates that the model is quite accurate. These findings can help investors make better investment decisions in the future.]]>
<![CDATA[Survival Analysis of Patients with Kidney Failure at Arifin Achmad Hospital, Riau Province using the Kaplan-Meier Method ]]>
<![CDATA[Sanurtillah, Farissa]]>;
<![CDATA[Sirait, Haposan]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i2.689
<![CDATA[The importance of applying advanced mathematical models in bond investing marks a revolutionary step in the modern financial industry, enabling more scalable and adaptive strategies to achieve financial success. The purpose of this talk is to explore and detail the role of advanced mathematical models in changing the bond investment paradigm. The discussion aims to highlight the crucial role of advanced mathematical models in changing the bond investment paradigm, providing a deeper understanding of the optimal potential and risks involved, explaining how this approach can optimize financial outcomes through more detailed analysis. The application of mathematical models involves the use of sophisticated algorithms and statistical analysis to identify optimal investment opportunities. These steps include the use of advanced financial math formulas, such as yield to maturity and duration, to design investment strategies that are adaptive and responsive to bond market dynamics. The application of mathematical models results in a deeper understanding of the bond market, allowing investors to respond quickly to changing market conditions. Thus, the investment strategy formed by this approach can not only improve investment returns, but also reduce the risks that investors may face. The application of advanced mathematical models in bond investing opens the door to smarter and more informed decision-making. By combining data and mathematical analysis, investors can maximize potential investment returns and manage risks more effectively.]]>
<![CDATA[Comparison of Projected Unit Credit, Entry Age Normal, and Individual Level Premium Methods in Calculation of Normal Retirement on PNS Pension Funds ]]>
<![CDATA[Putri S. R., Aulianda Anisa]]>;
<![CDATA[Susanti, Dwi]]>;
<![CDATA[Riaman, Riaman]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i2.692
<![CDATA[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.]]>
<![CDATA[Analysis of Financial Distress using the Altman Z-Score Model, Springate Model, Zmijewski Model, and Grover Model ]]>
<![CDATA[Simatupang, Frido Sarita]]>;
<![CDATA[Waspada, Ikaputra]]>;
<![CDATA[Sari, Maya]]>;
<![CDATA[Yuliawati, Tia]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i2.695
<![CDATA[The tight competition in the business world in the automotive industry that occurs in the current era of technology and development means that companies must have broad and clever thinking to keep the company from the brink of failure. During this research period there was a decline in automotive sales and company profits in the automotive and component sub-sectors listed on the IDX for the 2016-2020 period. This research aims to find out which prediction model is the most accurate and precise in predicting financial difficulties using model accuracy tests. The population in this study was 13 companies, then a purposive sampling technique was used to obtain 10 companies that were included in the research criteria. The results of this research show that the Altman Z-Score, Springate, Zmijewski and Grover models have different results, the Altman model predicts that there are 5 companies that are indicated to be healthy, 3 companies are in the Gray area, and 2 companies are indicated to have the potential to go bankrupt, the Springate model predicts that there are 5 companies healthy and 5 unhealthy companies, the Zmijewski model predicts that there are 9 healthy companies and 1 company that is indicated to have the potential to go bankrupt, the Grover model predicts that there are 7 healthy companies and 3 companies that are indicated to be unhealthy. With these results, the financial distress model with the highest accuracy is the Zmijewski model with an accuracy level of 92%, while the accuracy levels of the Altman Z-Score, Springate, and Grover models are 76%, 44%, and 76% respectively. With these results, the Zmijewski model is the most suitable model for use in automotive and component sub-sector companies in 2016-2020.]]>
<![CDATA[Socialization of Factors that Influence Exclusive Breastfeeding Practices and Their Implications for Stunting Prevention in Tasikmalaya City, West Java, Indonesia ]]>
<![CDATA[Ratnasari, Dewi]]>;
<![CDATA[sidiq, fahmi]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 2 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i2.698
<![CDATA[Stunting is still a national health problem in Indonesia, and one of the contributing factors is the lack of exclusive breastfeeding practices. This research aims to analyze the factors that influence the practice of exclusive breastfeeding in Tasikmalaya City, West Java. The case-control method was used in this research involving 4 Community Health Centers in Tasikmalaya City. Data was collected from mothers with children aged 6-12 months who were exclusively breastfed and those who were not exclusively breastfed. The research results show that husband's support has a significant influence on the success of exclusive breastfeeding practices. Apart from that, maternal knowledge also influences the perception of breast milk insufficiency. Other factors such as IMD practices and media exposure did not show a significant relationship. Re-socialization efforts are needed regarding the importance of exclusive breastfeeding, increasing mothers' knowledge, as well as actively involving fathers' groups in programs to increase exclusive breastfeeding.]]>
<![CDATA[Actuarial Pension Fund Using the Projected Unit Credit (PUC) Method: Case Study at PT Taspen Cirebon Branch Office ]]>
<![CDATA[Amalia, Hana Safrina]]>;
<![CDATA[Subartini, Betty]]>;
<![CDATA[Sukono, Sukono]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 3 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i3.745
<![CDATA[The pension fund program is a program held by the government to ensure the welfare of Civil Servants (PNS) in retirement as old-age security. The pension program for civil servants is managed by a pension fund, PT Taspen (Persero). Actuarial calculations of pension funds need to be carried out to determine the amount of normal contributions and actuarial liabilities that must be paid by pension plan participants and companies. The actuarial calculation of pension funds used by PT Taspen in managing civil servant pension funds is the Accrued Benefit Cost which determines in advance the benefits that will be obtained by participants. The Projected Unit Credit (PUC) method is one part of the Accrued Benefit Cost. This study aims to determine normal contributions and actuarial liabilities using the Projected Unit Credit (PUC) method for civil servant pension program participants of PT Taspen (Persero) Cirebon Branch Office. The calculation results show that the PUC method provides a more accurate calculation of the estimated normal contributions and actuarial liabilities of the company. This study is expected to be a reference for other companies in managing employee pension funds using an actuarial approach.]]>
<![CDATA[Determining the Pure Premium at Jasa Raharja Insurance Company Purwakarta Branch using Fast Fourir Transform (FFT) through Estimated Aggregate Loss Distribution ]]>
<![CDATA[Saefullah, Rifki]]>;
<![CDATA[Ibrahim, Riza Andrian]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v5i4.815
<![CDATA[Insurance is a contractual agreement between two parties, namely the insured party (customer) and the insurer (insurance company), in which the insured party pays a premium to the insurer, then in return, the insurer will provide compensation (claim) to the insured party if an insured event occurs. Each customer is required to pay a premium as an obligation stated in the insurance agreement by paying a premium, the customer fulfills his obligations and is entitled to the benefits stated in the policy. Therefore, the Insurance Company needs to carry out a scheme in the process of paying pure premiums for the sustainability of the insurance company. When determining the premium, it is done by estimating the aggregate loss distribution. This research will calculate thepure premium at the Purwakarta Branch of Jasa Raharja Insurance Company. The model used in this study is the distribution of aggregate loss with a compound distribution of claim frequency and claim size. Many claims follow the Poisson distribution and large claims follow the Lognormal distribution. In the process of estimating the probability of aggregate loss with the compound distribution model, the Inverse method with the Fast Fourier Transform (FFT) algorithm is used. This research will provide understanding and insight to insurance companies in determining the amount of premium that must be charged to customers.]]>
