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[Robust Optimization for Food Supply Chain Management Problems: A Critical Review and its Novelty ]]>
<![CDATA[Athaya Zahrani Irmansyah]]>;
<![CDATA[Subiyanto Subiyanto]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 2, No 3 (2021) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v2i3.155
<![CDATA[Optimization problems in real life often have problems with data that cannot be known precisely; constraints on the data are commonly referred as errors. This kind of data is called uncertainty. This uncertainty problem can be solved using Robust Optimization (RO). RO is growing rapidly with the participation of various kinds of research, especially the supply chain (distribution of food or goods between regions). It can be seen that RO is very active in providing support and contribution in various aspects of life by providing optimal results for an objective function and dealing with existing limitations and data uncertainty. This article discusses the background of the problem and the purpose of creating an article, provides an overview of bibliometric map analysis methods and discusses literature and studies. Critical review from OR database articles for supply chain problems are used as a reference, so at the end, it can be determined what novelty is an opportunity for further research.]]>
<![CDATA[The Effect of Gender and Household Education Expenditure in Indonesia ]]>
<![CDATA[Tedy Di Oria Salam]]>;
<![CDATA[M. Shabri Abd. Majid]]>;
<![CDATA[Taufiq C Dawood]]>;
<![CDATA[Suriani Suriani]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 2, No 4 (2021) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v2i4.192
<![CDATA[This study empirically examines and analyzes the effect of gender on human capital investment in Indonesia. Using the logistic regression method and data sourced from 315,672 households in Indonesia, this study shows that the number of boys, the number of girls, the working status of the head of the household, and the highest education of the head of the household have a positive and significant impact on human capital investment in Indonesia. The results show that female household heads who work and invest in the cost of children's education are more significant than male household heads who also work. Higher the education level of the head of the household, the higher the income received and also investment for children. This research shows strong evidence of gender inequality in education spending that tends to be more towards girls. Based on the results obtained, development policies can consider gender differences in investment in labor and education. Increasing the school participation rate of women compared to men will increase the differentiation of the workforce by gender but also increase income inequality between men and women. Likewise, investment in education which tends to be more directed to women than men, will reduce income inequality.]]>
<![CDATA[Examining the Long and Short Run Effect of Young Workers on Macroeconomic Variables: An Application of Panel Autoregressive Distributed Lag Approach ]]>
<![CDATA[Rizky Wardhana]]>;
<![CDATA[Vivi Silvia]]>;
<![CDATA[M. Shabri Abd. Majid]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 2, No 4 (2021) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v2i4.180
<![CDATA[The purpose of this research is to analyze the linkage between young workers and macroeconomic variables in Indonesia through a cointegration and causality approach. Multivariate causality between these variables. Using ARDL panel regression (Auto-Regressive Distributed Lag) with data from 2005 – 2019 covering 33 provinces in Indonesia. The results showed that the variable government expenditure on education had no effect on young workers in the short and long term, the variable economic growth only had a positive and significant effect on young workers in the long term. The increase in the minimum wage has a significant negative effect on young workers in the short term, and vice versa, it has a positive and significant effect on the long term. The last variable that has an effect is the investment variable which has a negative and significant effect in the short term on young workers. The results of multivariate causality testing between the variables above have the result that young workers have a two-way causal relationship with the minimum wage and have a one-way relationship with government spending on education.]]>
<![CDATA[Principal Component Regression in Statistical Downscaling with Missing Value for Daily Rainfall Forecasting ]]>
<![CDATA[M Dika saputra]]>;
<![CDATA[Alfian Futuhul Hadi]]>;
<![CDATA[Abduh Riski]]>;
<![CDATA[Dian Anggraeni]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 2, No 3 (2021) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v2i3.151
<![CDATA[Drought is a serious problem that often arises during the dry season. Hydrometeorologically, drought is caused by reduced rainfall in a certain period. Therefore, it is necessary to take the latest actions that can overcome this problem. This research aims to predict the potential for a drought to occur again in the Kupang City, Indonesia by developing a rainfall forecasting model. Incomplete daily local climate data for Kupang City is an obstacle in this analysis of rainfall forecasting. Data correction was then carried out through imputed missing values using the Kalman Filter method with Arima State-Space model. The Kalman Filter and Arima State-Space model (2,1,1) produces the best missing data imputation with a Root Mean Square Error (RMSE) of 0.930. The rainfall forecasting process is carried out using Statistical Downscaling with the Principal Component Regression (PCR) model that considers global atmospheric circulation from the Global Circular Model (GCM). The results showed that the PCR model obtained was quite good with a Mean Absolute Percent Error (MAPE) value of 2.81%. This model is used to predict the daily rainfall of Kupang City by utilizing GCM data.]]>
<![CDATA[Fuzzy Time Series Application in Predicting the Number of Confirmation Cases of Covid-19 Patients in Indonesia ]]>
<![CDATA[Lintang Patria]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 2, No 4 (2021) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v2i4.194
<![CDATA[Forecasting is a statistical method that can use historical data patterns to predict future events. This article discusses the prediction of the number of new confirmed cases of Covid-19 patients in Indonesia. The data used is from January 1, 2021 to August 7, 2021. The methods used are Fuzzy Time Series (FTS) Chen (2014) and Cheng et al. (2008). FTS is a forecasting method that uses rules and logic on fuzzy sets. The level of prediction accuracy is then calculated based on the Mean Absolute Percentage Error (MAPE) value. The MAPE values of these two methods are then compared to know which method is more suitable in this case study. The results showed that FTS Chen produced an accuracy of 12.75% and FTS Cheng produced an accuracy of 14.27%. The results of this study indicate that FTS Chen and FTS Cheng produce good accuracy and can be used to predict new confirmed cases of Covid 19 sufferers in Indonesia.]]>
<![CDATA[Potential classification of Smart Village – Smart Economy with Deep Learning methods ]]>
<![CDATA[Runanto Runanto]]>;
<![CDATA[Muhammad Fahmi Mislahudin]]>;
<![CDATA[Fauzan Azmi Alfiansyah]]>;
<![CDATA[Maudy Khairunnisa Maisun Taqiyyah]]>;
<![CDATA[Eneng Tita Tosida]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 2, No 3 (2021) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v2i3.147
<![CDATA[Development gap in the city and village is still happening on Indonesia. It happened because of the massive urbanization factors. Poverty in the Indonesian villages are relatively higher than on the urbans. In order to reach the maximal city development, Ministry of Village, Development of Disadvantaged Regions and Transmigration of Indonesia created a sustainable village development program namely Village’s Sustainable Development Goals (SDGs) and optimized the village potential data. This study aimed to design the smart village – smart economy classification system by using deep learning methods on village potential data on Indonesia at 2020. The method used in this study is data mining processes namely KDD (Knowledge Discovery and Data mining). The result in this study showed the best models were obtained which consisting of 2 hidden layers and each layer is 128, 128 layers which using target class from the process of calculating the score is able to reach 94.93% of the accuracy from the training process and 96% on the testing process and succeeded to classify the potentials of smart village – smart economy.]]>
<![CDATA[IDX30 Stocks Clustering with K-Means Algorithm based on Expected Return and Value at Risk ]]>
<![CDATA[Ahmad Fawaid Ridwan]]>;
<![CDATA[Subiyanto Subiyanto]]>;
<![CDATA[Sudradjat Supian]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 2, No 4 (2021) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v2i4.157
<![CDATA[Stocks are one of the investment instruments available in the capital market. Several indices show the characteristics of stocks listed on the Indonesia Stock Exchange. IDX30 is one of several indications that show the combined stocks are stocks with large market capitalization, high liquidity, and good fundamentals. The selection of assets to be allocated in the portfolio is an important factor in investing where the purpose of investing is to maximize returns and minimize risk. This study aims to classify stocks that have certain characteristics based on the expected return and value at risk of the stocks incorporated in IDX30 with a clustering algorithm. The clustering algorithm used is the K-Means algorithm. K-Means is a non-hierarchical clustering algorithm by groups each object based on its proximity to the cluster center. The method used in this research is a clustering simulation study using the K-Means algorithm on IDX30 stock data. By identifying the characteristics of the stock based on the characteristics of the cluster formed, it is hoped that it can be considered in choosing the assets to be used in the formation of an optimal portfolio.]]>
<![CDATA[Transmission of Special Autonomic Funds in the Economy through Mediation Variables ]]>
<![CDATA[Sri Wulan Wijayanti]]>;
<![CDATA[Abd. Jamal]]>;
<![CDATA[Putri Bintusy Syathi]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 2, No 3 (2021) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v2i3.174
<![CDATA[This study analyzes the effect of special autonomy funds on physical infrastructure, education, health, and poverty as well as its effect on economic growth in Aceh Province. The effect seen is the direct or indirect effect that occurs between the realization of special autonomy funds on economic growth in Aceh Province. The physical infrastructure variables represented by the length of the road, education represented by the average length of schooling, health represented by life expectancy, and poverty represented by the percentage of poor population were intervening variables. The intervening variable is a variable that is considered capable of mediating between the independent variables and the dependent variable. The analysis model used in this study is path analysis so as to be able to see the direct and indirect effects of an independent variable on the dependent variable. The results found in this study are the realization of special autonomy funds has a direct effect on economic growth. While the indirect effect is given by the variable realization of special autonomy funds on economic growth through the length of the road, life expectancy, and the percentage of poor people. The variable of average length of schooling does not have an indirect effect between the realization of special autonomy funds on the economic growth of Aceh Province.]]>
<![CDATA[Factors Influencing Philippines Tourist’ Revisit Intention: The Role and Effect of Destination Image, Tourist Experience, Perceived Value, and Tourist Satisfaction ]]>
<![CDATA[Angelo Libre]]>;
<![CDATA[Aldaba Manalo]]>;
<![CDATA[Grida Saktian Laksito]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 3, No 1 (2022) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v3i1.260
<![CDATA[The Philippines is an agrarian-based tourism country, millions of tourists come to visit every year. However, most of the first-time visitors leave the question of why so few people decide to return for a tour of the Philippines' tourist destinations. This study aims to determine how the influence of the image of the destination, the experience of tourists on the intention to revisit through the value received and the satisfaction of tourists at tourist destinations in the Philippines. The research method used is quantitative, the sampling technique uses non-probability sampling and a sample of 287 respondents is obtained, the analytical tool used is Path Analysis and the hypothesis uses a significance test using SEM AMOS and SPSS analysis tools. The results of this study indicate that direct testing of the tourist experience variable affects revisit intention in tourist destinations in Philippines, then for direct testing the perceived value variable has a significant effect on tourist satisfaction at tourist destinations in the Philippines, then tourist satisfaction is able to mediate the relationship between tourist experience and revisit intention.]]>
<![CDATA[The Selection of Learning Platforms to Support Learning Using Fuzzy Multiple Attribute Decision Making ]]>
<![CDATA[Vensy Vydia]]>;
<![CDATA[Susanto Susanto]]>;
<![CDATA[Sri Handayani]]>;
<![CDATA[Maulana Bahrul Alam]]>
<![CDATA[ International Journal of Quantitative Research and Modeling Vol 3, No 1 (2022) ]]>
Publisher : <![CDATA[Research Collaboration Community (RCC) ]]>
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DOI: 10.46336/ijqrm.v3i1.257
<![CDATA[The utilization of information technology in learning has functioned as a tool in the teaching and learning process during the Covid-19 pandemic. The need for the availability of a learning platform using LMS (Learning Management System) or free e-learning that is easily obtained from the public network (internet) makes the utilization of the learning platform indispensable for the teaching and learning process. Learning platforms available on the internet can also be used independently by students. However, not all existing learning platforms can be used as the appropriate means to improve the quality of education. The educator policies are needed to utilize the existing learning platforms so that learning objectives can be achieved. This study will analyze how to choose the right learning platform for an educational institution using SAW (Simple Additive Weighting)-based Fuzzy Multiple Attribute Decision Making (FMADM) method. FMADM is a method used to find the optimal alternative from a number of alternatives with certain criteria. The purpose of this study is to assist educators in deciding the most appropriate learning platform that can be used to support the teaching and learning process during the Covid 19 pandemic.]]>
