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
15 Documents
Search results for
, issue
"Vol. 5 No. 2 (2024)"
:
15 Documents
clear
<![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) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
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) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
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) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
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) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
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) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
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.]]>
