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
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<![CDATA[The Effects of Monetary Variables on the Growth of Small and Medium Industry in Aceh Province ]]>
<![CDATA[Ade Habya Fijay]]>;
<![CDATA[Vivi Silvia]]>;
<![CDATA[Chenny Seftarita]]>
<![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.v2i3.175
<![CDATA[This study aims to analyze the effect of inflation, bank credit, and SMI investment on the growth of small and medium industries in Aceh Province. This study uses panel data consisting of 23 districts/cities in Aceh Province during the period 2014 to 2020. The analysis model used in this study is a panel data regression model. The results found in this study are variables that have a significant effect on the growth of SMIs in Aceh Province are inflation and investment in SMIs. Meanwhile, the banking credit variable has not had a statistically significant effect on the growth of SMIs. The inflation variable has a negative and significant effect on the growth of SMIs so that uncontrolled inflation will have a negative impact on the growth of SMIs. Meanwhile, SMI investment has a positive and significant impact on the growth of SMIs so that various targeted investment policies are needed so that they can support the development of SMIs in Aceh Province.]]>
<![CDATA[The Effect of Energy Consumption, Energy Resources, Economic Growth, and Road Infrastructure on Co2 Emissions in Indonesia ]]>
<![CDATA[Zulfikar Zulfikar]]>;
<![CDATA[Sofyan Syahnur]]>;
<![CDATA[M. Shabri Abd. Majid]]>
<![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.v2i3.173
<![CDATA[This study aims to analyze the effect of energy resources, energy consumption, and road infrastructure on economic growth and their effect on CO2 emissions in Indonesia. This study uses time series data in Indonesia for the period 2000 to 2019 and the analytical model used is the Auto Regressive Distributed Lag (ARDL) model. The results found in this study are variables that have a significant effect on economic growth in the short term are road infrastructure in the same period, in the previous period, as well as in the previous 2 periods and resources. Meanwhile, the ones that have a significant effect in the long term are road infrastructure and energy resources. Variables that have a significant effect on CO2 emissions in the short term are road infrastructure, energy consumption in the previous period, economic growth in the previous period, energy consumption and energy resources. While the variables that influence in the long term are economic growth and energy resources.]]>
<![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[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[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[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.]]>
