cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
acengs@umtas.ac.id
Phone
+6285841953112
Journal Mail Official
ijqrm.rescollacomm@gmail.com
Editorial Address
Jalan Riung Ampuh No. 3, Riung Bandung, Kota Bandung 40295, Jawa Barat, Indonesia
Location
Kota bandung,
Jawa barat
INDONESIA
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 236 Documents
 20   21   22   23   24 
Annuity in Advance for Rental Properties: Profit and Risk Analysis for Owners of Student Rental Homes Near Campus Sabrina, Amirah Nur; Nabila, Hella Rizwa
International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.830

Abstract

Nowadays, the rental homes business in the area around the campus offers significant profits for its owners, this is due to the large number of students who migrate so they choose to live in rental homess, but on the other hand this can also cause various risks, including fluctuations. Maintenance costs and high occupancy rates. This can make rental homes owners' income unpredictable and make it difficult to create long-term financial goals. Using an upfront annuity model, where the owner receives rental payments at the start of the period, is one way to lower this risk. rental homes owners can guarantee more consistent cash flow and make more accurate income predictions by applying this concept. The aim of this research is to examine how the application of the advance annuity model affects the income and risks of rental homes owners. This study will assess how advance annuities contribute to income stability and reduce the uncertainty that often occurs in rental homes operations by using comprehensive financial techniques. Apart from that, this analysis will also consider various external factors that can influence occupancy levels, such as campus policies and economic conditions. It is hoped that the findings from this research will provide useful insights for rental homes owners in maximizing profits while managing risks more effectively, so that they can adapt to ever-changing market dynamics. Therefore, this strategy can be a smart alternative for rental homes owners in optimizing their business performance around campus.
Feasibility Analysis of Establishing a Gudeg Jogja Business Using the Net Present Value (NPV) Method in the City of Jakarta Putri, Mutiara Silvia; Trianandra, Fiona
International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.831

Abstract

This research aims to analyze the feasibility of establishing a Jogja gudeg business in the city of Jakarta using the Net Present Value (NPV) method. Gudeg, as a typical Yogyakarta culinary specialty, has quite large market potential in Jakarta considering the high public interest in traditional and unique foods. This research will examine various aspects, including technical analysis, financial analysis, and sensitivity analysis. Financial analysis will focus on NPV calculations to measure the added value of investments in the long term. It is hoped that the results of the research will provide a clear picture of the potential success of the Jogja gudeg business in Jakarta and become a reference for prospective entrepreneurs who are interested in the culinary business.
Comparative Analysis: Value at Risk (VaR) with Parametric Method, Monte Carlo Simulation, and Historical Simulation of Mining Companies in Indonesia Darmawan, Muhammad Rizky; Widyono, Fathi Atha Putra
International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.834

Abstract

This study aims to conduct a comparative analysis between three Value at Risk (VaR) calculation methods, namely the Parametric (Variance-Covariance) method, Monte Carlo Simulation, and Historical Simulation, in measuring market risk in mining companies in Indonesia. The mining industry in Indonesia faces the risk of high commodity price volatility, thus requiring an appropriate approach in measuring potential financial losses. This study uses historical stock data from several major mining companies in Indonesia to analyse the difference in results between the three VaR methods. This study found that the smallest VaR value is owned by PTBA company. Along with the level of stability shows that PTBA company is more stable than other companies. This is inversely proportional to the TINS company which has a large VaR value and high volatility.
The Effect of Double Date Discounts on Sales Levels In E-Commerce Shopee (Case Study on Students of Padjadjaran University in Jatinangor) Wahid, Alim Jaizul; Millantika, Salwa Cendikia; Supriatna, Asep Kuswandi
International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.835

Abstract

This study aims to analyze the impact of double date sale discounts on sales levels on the Shopee e-commerce platform, focusing on students from Universitas Padjadjaran in Jatinangor, who are primarily from the millennial and Generation Z cohorts. The method used is simple linear regression, linking discount variables to sales. Additionally, the study conducts classical assumption testing to ensure the models validity and sensitivity analysis to assess the effect of parameter changes on the predicted outcomes. The results show that double date sale discounts significantly influence sales, with the double date sale coefficient (eta_1) being highly sensitive to changes. The regression model yields a low MSE, indicating good prediction accuracy. While changes in the intercept (eta_0) also affect the predictions, the impact is smaller compared to changes in the double date sale coefficient.
Investment Portfolio Optimization on Technology Sector Stocks Using Mean-Variance Model with Asset-Liability Based on ARIMA-GARCH Approach Bisyarah, Sania
International Journal of Quantitative Research and Modeling Vol. 6 No. 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.864

Abstract

In this era of rapid technological advancement, various sectors are experiencing changes, one of which is investment. Investors are starting to turn their attention to technology sector stocks as new investment targets. However, investments are inherently linked to return and risk levels and stock prices can be highly volatile. Therefore, forming an optimal investment portfolio is very important to achieve a balance between return and risk. In addition, coping with volatile stocks is also very important. The ARIMA-GARCH time series model is a method that can be used to deal with such volatility. A popular strategy for portfolio optimization is to use the Mean-Variance model, also known as the Markowitz model. This study aims to form an optimal portfolio consisting of five technology sector stocks in Indonesia with the codes AXIO, DIVA, EDGE, MCAS, and CASH using the Mean-Variance model with assets-liabilities equipped with the ARIMA-GARCH approach. Based on the results of the study, the optimal portfolio is obtained with the composition of each weight is 23.16% of the capital allocated to AXIO; 2.95% for DIVA; 56.48% for EDGE; 6.36% for MCAS; and 11.05% for CASH. The weight allocation composition can generate a portfolio return of 0.0066 and a variance (risk) return of 0.0082.
Investment Portfolio Optimization Using Mean-Variance Model With Data Envelopment Analysis (DEA) Approach on IDX30 Stocks Putrie, Veronica Clasrissa
International Journal of Quantitative Research and Modeling Vol. 6 No. 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.865

Abstract

Globalization and technological advancements are driving the importance of careful financial management, including in investments. Stocks have become a popular investment option as they offer potential profits from dividends and capital gains. However, the large selection of stocks in the Indonesian capital market, especially in the IDX30 index, makes investors face challenges in selecting efficient stocks and compiling optimal portfolios. Therefore, this research combines Data Envelopment Analysis (DEA) and Mean-Variance Model to screen efficient stocks and form an optimal investment portfolio. In this study, DEA is used to assess the efficiency of stocks based on company performance, while the Mean-Variance Model is used to determine the optimal weight in the portfolio by balancing risk and return. Of the 13 stocks analyzed, 9 efficient stocks were identified, namely ADRO, ASII, BBCA, BBNI, BBRI, INDF, KLBF, TLKM, and UNTR. The optimal portfolio is obtained with a risk tolerance value of 0.015, which results in an expected return of 0.00027711 and a variance of 0.00004396.
Determination of Monthly Term Health Insurance Premiums for Individuals Based on Gender Siahaan, Roy Donald Pangeran
International Journal of Quantitative Research and Modeling Vol. 6 No. 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.866

Abstract

Health is one of the important aspects of human life, and protection against health risks is a necessity for every society. Health insurance is a solution in providing protection against financial risks from health. In its implementation, determining premiums is an important factor for insurance companies in order to cover claims from policyholders. Premiums are money paid by policyholders to insurance companies in order to receive benefits in the future. This study aims to determine the monthly premium for term health insurance which adjusted for each gender using actuarial approach. The premium is determined using the 2023 Indonesian Mortality Table and the Indonesian Morbidity Table I "Critical Illness". Based on this study, it was found that the value of the monthly term health insurance premium will increase if the policyholder's entry age and the insurance contract period increase. This study also found that the premium values for men were greater than the premium and reserve values for women if the policy entry age of the man or woman was over 30 years, in addition, the premium and reserve values for women were greater.
Implementation of The Apriori Algorithm on X Cafe Sales Transactions for Product Bundling Package Recommendations Sadiah, Halimah Tus; Purnama, Delta Hadi; Erniyati, Erniyati
International Journal of Quantitative Research and Modeling Vol. 6 No. 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.882

Abstract

Bundling packages are a marketing strategy in which several products are combined at a more attractive price than if purchased separately. This strategy effectively increases sales, attracts new customers, and levels up the average transaction value. Cafe X, located in Bogor, is a coffee shop that has not yet had a product bundling strategy package to increase product sales. This study aims to implement the Apriori algorithm on sales transactions at Cafe X to bundle product recommendations. The research stages consist of data collection, preprocessing, implementation of an apriori algorithm, and extracting association rules. In this study, a website-based apriori algorithm was implemented. Users can enter the minimum support value, minimum confidence value, and the recommended menu for product bundling. Based on the research results, it is produced for data input on the application with menu recommendations in the form of Tsuin Iced Coffee and Chicken Strips menus with a minimum support of 50% and a minimum Confidence of 90% can produce recommendations for 3 product bundling packages, including Package 1 recommendations are Tsuin Iced Coffee, Chicken Strips, Hot Barbeque Chicken. Package 2 recommendations are Tsuin Iced Coffee, Chicken Strips, and Nachos. Package 3 recommendations are Tsuin Iced Coffee, Chicken Strips, Hot BBQ chicken and Nachos.
Strengthening Green Loyalty: How Green Marketing, Green Perceived Value, and Environmental Concern Drive Green Satisfaction (A Study of Uniqlo’s Consumer in Bandung Metropolitan) Septiarini, Eka; Djulius, Horas; Juhana, Dudung
International Journal of Quantitative Research and Modeling Vol. 6 No. 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.883

Abstract

The objective of this study is to identify, examine, and analyze the influence of green marketing on green customer satisfaction, the influence of green perceived value on green customer satisfaction, the influence of environmental concern on green satisfaction, and the influence of green satisfaction on green customer loyalty of Uniqlo consumers in Bandung Metropolitan. Data were collected from respondents aged between 17 and 55 years old, residing in the Bandung Metropolitan area, and having purchased Uniqlo's green products at least twice in the past year. The analysis was performed using Lisrel - Structural Equation Modeling version 8.8. The findings reveal that green marketing, green perceived value, and environmental concern simultaniously contribute 73.6% to green customer satisfaction with Uniqlo in Bandung Metropolitan, while the remaining 26.4% is influenced by other variables. Partially, green marketing contributes 18.5%, green perceived value 24.4%, and environmental concern 30.7% to green satisfaction. Additionally, green satisfaction has been proven to have a significant influence of 79.9% on green loyalty among Uniqlo consumers in Bandung Metropolitans.
Mean-Variance Optimal Portfolio Selection with Risk Aversion on Transportation and Logistics Sector Stocks Based on Multi-Criteria Decision-Making Putri, Aulya; Riaman, Riaman; Sukono, Sukono
International Journal of Quantitative Research and Modeling Vol. 6 No. 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.895

Abstract

The importance of the transportation and logistics sector to a country's economy, coupled with the growth of this sector in Indonesia, requires investment support for this sector to continue to grow. Therefore, stocks in the transportation and logistics sector are attractive for investment portfolio consideration. The optimal portfolio selection is to minimize the risk with the expected return. In the formation of an investment portfolio, the problem is how to determine the weight of capital allocation in order to get the maximum return while still considering the risk in each stock, by considering several criteria in decision making. This study was conducted to determine the best stock selection in the transportation and logistics sector listed on the Indonesia Stock Exchange, and determine the optimal weight in the investment portfolio. The method used is Multi-Criteria Decision Making (MCDM), namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) using 15 financial metrics as relevant criteria in stock selection. Furthermore, to determine the allocation weight to form an optimal stock portfolio using the Mean-Variance model with Risk Aversion. The stocks analyzed were 28 stocks in the transportation and logistics sector. The results of research based on MCDM selected 9 stocks, namely MITI, BIRD, HATM, TMAS, JAYA, PPGL, BPTR, ASSA, and RCCC. However, TMAS, PPGL, and BPTR stocks are not included in portfolio formation because they have a negative average return. Based on the optimization results, the allocation weights of the 6 stocks included in the optimal portfolio are BIRD (37.7%), JAYA (24.6%), MITI (12.9%), HATM (9.9%), ASSA (7.5%), and RCCC (7.4%). The results of this study are expected to be a consideration in making investment decisions.

Page 22 of 24 | Total Record : 236

 20   21   22   23   24 

Filter by Year

2020 2025


Reset
Filter By Issues
All Issue Vol. 6 No. 3 (2025): International Journal of Quantitative Research and Modeling (IJQRM) Vol. 6 No. 2 (2025) Vol 6, No 2 (2025) Vol 6, No 1 (2025) Vol. 6 No. 1 (2025) Vol. 5 No. 4 (2024) Vol 5, No 4 (2024) Vol 5, No 3 (2024) Vol. 5 No. 3 (2024) Vol. 5 No. 2 (2024) Vol. 5 No. 1 (2024) Vol 4, No 3 (2023) Vol 4, No 2 (2023) Vol 4, No 1 (2023) Vol 3, No 4 (2022) Vol 3, No 3 (2022) Vol 3, No 2 (2022) Vol 3, No 1 (2022) Vol 2, No 4 (2021) Vol 2, No 3 (2021) Vol 2, No 2 (2021) Vol 2, No 1 (2021) Vol 1, No 4 (2020) Vol 1, No 3 (2020) Vol 1, No 2 (2020) Vol 1, No 1 (2020) More Issue