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International Journal of Quantitative Research and Modeling
Published by Research Collaboration Community
ISSN : 27225046     EISSN : 2721477X     DOI : https://doi.org/10.46336/ijqrm
Core Subject : Science, Social, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Physics
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
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol 3, No 4 (2022)" : 6 Documents clear
CONSTRUCTION OF MORTALITY TABLES USING UNIFORMLY DISTRIBUTION OF DEATH AND CONSTANT FORCE BASED APPROACHES IN TMI 2019 Nurul Tri Narlitasari; Riri Rioke; Wulan Setyani; Anisa Nurbayti; Agung Prabowo
International Journal of Quantitative Research and Modeling Vol 3, No 4 (2022)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v3i4.356

Abstract

Insurance aims to protect a person from financial losses that may occur due to an unexpected event. On the determination of insurance premiums used mortality tables. However, on the mortality table contains only a round age. While an event cannot be ascertained when it occurs, it could be at the beginning of the year, in the middle, or at the end of the year. Therefore, to determine insurance premiums at an age that is not round, a mortality table that contains fractional age is needed. In this study, the mortality table used is the 2019 Indonesian Mortality Table (IMT) issued by the Indonesian Actuary Association (IAA). The methods used for determining fractional age mortality tables are the Uniform Distribution of Death (UDD) approach and the Constant Force of Mortality (CF) approach. In this study, the results of the 2019 TMI calculation were obtained for fractional ages with male and female genders using two approaches, namely the UDD and CF approaches. In both sexes, the result was obtained that the chance of death calculated using the UDD approach was smaller compared to the CF approach. The resulting graph shows that the 2019 TMI death chances with the UDD and CF approaches did not show significant differences for both men and women, so both approaches can be used to calculate the chance of death at the fractional age of TMI 2019.
Graph Models of Harems and Tournaments in Sports Clubs Mochamad Suyudi
International Journal of Quantitative Research and Modeling Vol 3, No 4 (2022)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v3i4.378

Abstract

By looking at the extension of Hall's marriage theorem to harems, where some people are allowed to have more than one partner, Traditionally in harems any man can have multiple wives but no woman can have more than one husband. then consider the different types of matches by looking at 'round robin tournaments' in sports clubs. An unexpected connection between the two worlds emerged when we were able to use our harem results to deduce theorems about the tournament.
Portfolio Analysis Using the Markowitz Model with Stock Lot Constraints and Target Returns or Without Target Returns Asri Rula Hanifah; Betty Subartini; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol 3, No 4 (2022)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v3i4.358

Abstract

Stock investment activities are inseparable from returns and risk, so an investor needs expertise to minimize investment risk. One way is by forming an optimal portfolio. The purpose of this research is to determine the number of stock lots in the optimal portfolio. This research analyzes the closing prices of stocks during the research period with the criteria of stocks being listed on the IDX30 index consecutively for 20 periods and belonging to the large cap group (the stock market capitalization exceeds $10 billion). Then the number of stock lots is calculated using the Markowitz model with stock lot constraints and target returns or without target returns. From the selected stocks, an optimal portfolio is formed using Microsoft Excel. Based on the research results, a combination of an optimal portfolio with a target return is ASII: 5, BBCA: 10, BBNI: 23, BBRI: 1, BMRI: 23, TLKM: 93, UNVR: 12, where the risk is 0,000149 and the target expected return is 0,00155. Meanwhile, the optimal portfolio without a target return is ASII: 8, BBCA: 7, BBNI: 32, BBRI: 40, BMRI: 9, TLKM: 62, UNVR: 17, where a risk is 0,000147 and the expected return is 0,00148. This research can be used as a consideration for investors in determining investment portfolios.
Investment Portfolio Optimization With Mean-Variance Investment Portfolio Optimization Model Without Risk Free Assets Wilda Nur Rahmalia; Dwi Susanti; Rizki Apriva Hidayana
International Journal of Quantitative Research and Modeling Vol 3, No 4 (2022)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v3i4.360

Abstract

Forming a portfolio is a strategy that is often carried out by investors in risky investment conditions. Five non-risk free stocks were selected, namely PTBA, IPCM, ANTM, BUMI, and ADMF. The purpose of forming this portfolio is to determine the composition of the weight (proportion) of the allocation of funds in each of these shares in forming the optimum portfolio. The method used is the Mean-Variance investment portfolio optimization model without risk-free assets using the Markowitz approach. Based on the results obtained by the optimum portfolio of the Mean-Variance model without risk-free assets, the average return is 0.00105 and the variance is 0.000067 with a portfolio ratio value of 14.65256. The proportion of fund allocation to PTBA shares = 0.28872; IPCM=0.02484; ANTM=0.00016; EARTH=0.13501; and ADMF=0.55126. It is hoped that the formation of this portfolio optimization model will be useful as an alternative for investors in optimizing the investment portfolio to make it more profitable in the future. 
Investment Portfolio Optimization Model with Mean-Std Deviation Nurhadini Putri; Mochamad Suyudi; Ibrahim Mohammed Sulaiman
International Journal of Quantitative Research and Modeling Vol 3, No 4 (2022)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v3i4.359

Abstract

Stock investment is an investment in securities with the hope of getting profits in the future. Investors are expected to make a series of portfolios to get optimal results from investments. This discussion aims to find the weight of the funds invested along with the returns and risks. The method used is the mean + std deviation. The results of this portfolio optimization show that the risk aversion coefficient is 0.1. The optimum weight for investment in each company is KLBF (22.67%), PGAS (8.796%), BBCA (41.77%), ASII (8, 24%), and SMAR (18.52%) with a maximum ratio of 8.8% of a return of 0.0881% and a risk of 1.0009%. The results of this portfolio optimization are expected to help investors by dividing the number of funds to be invested by the return and risk.
De Moivre Law Application for the Construction of Mortality Tables Based on Indonesian Mortality Tables 2019 Elsa Anna Pratiwi; Fitri Indah Ningtyas; Ratna Nur Aini Kamilia; Zahwa Aqila Nabilia Aqila Nabilia; Agung Prabowo
International Journal of Quantitative Research and Modeling Vol 3, No 4 (2022)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v3i4.357

Abstract

The mortality table or often referred to as the life table is the main instrument used by actuaries in building premium and reserve structures for life insurance products, annuities, and pension programs. The mortality table provides a complete description of the mortality rate and life expectancy and shows the pattern of death of a group of people born at the same time based on the age they have reached and plays an important role as a basis for calculating the level of life expectancy in the future. This article aims to find out how to construct a mortality table with reference to the 2019 TMI for men with de Moivre's Law. In the results of the construction with de Moivre's law, the lowest  value occurred at the age of 0 years, namely = 0.00900901, while the highest  value occurred at the age of 110 years, namely  = 1. Based on the construction of the  value in the 2019 TMI for men using de Moivre's law, which is compared with the  value in the 2019 TMI for men, the results tend to be the same.

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