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International Journal of Global Operations Research

ijgor
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Published by Indonesian Operations Research Association

ISSN : 27231747 EISSN : 27221016 DOI : https://doi.org/10.47194/ijgor

Core Subject : Economy, Science, Education, Engineering,

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Mathematics

International Journal of Global Operations Research (IJGOR) is published 4 times a year and is the flagship journal of the Indonesian Operational Research Association (IORA). It is the aim of IJGOR to present papers which cover the theory, practice, history or methodology of OR. However, since OR is 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 OR to real problems are especially welcome. In real applications of OR: forecasting, inventory, investment, location, logistics, maintenance, marketing, packing, purchasing, production, project management, reliability and scheduling. In a wide variety of environments: community OR, 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. Topics Covered: Computational Intelligence Computing and Information Technologies Continuous and Discrete Optimization Decision Analysis and Decision Support System Applied Operations Research in Education Engineering Management Environment, Energy and Natural Resources Financial Engineering Applied Operations Research inGovernment Heuristics Industrial Engineering Information Management Information Technology Inventory Management Knowledge Management Logistics and Supply Chain Management Maintenance Manufacturing Industries Applied Operations Research in Marketing Engineering Markov Chains Mathematics Actuarial Sciences Military and Homeland Security Networks Operations Management Organizational Behavior Planning and Scheduling Policy Modeling and Public Sector Applied Operations Research inPolitical Science Production Management Applied Operations Research inPsychology Queuing Theory Revenue & Risk Management Services management Simulation Applied Operations Research inSociology Applied Operations Research inSports Statistics Stochastic Models Strategic Management Systems Engineering Telecommunications Transportation And so on

Arjuna Subject : Umum - Umum

Articles 174 Documents

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Analysis of the Influence of Inflation on the Real Value of Deposits on Property Purchase Accessibility Zuhri, Mukholifatun Azizah; Ammarilia, Fidela Wanda
International Journal of Global Operations Research Vol. 6 No. 1 (2025): International Journal of Global Operations Research (IJGOR)
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i1.362

Inflation is an economic phenomenon that has a significant impact on people's purchasing power. When the inflation rate increases, the real value of money saved in the form of savings, including deposits, tends to decrease. However, when inflation exceeds the deposit interest rate, the real value of these savings will be eroded, affecting customers' ability to invest, including in purchasing property. The increase in property prices that has continued to occur in recent years has added to the challenges for people in obtaining a house or other property. Uncontrolled inflation can affect the accessibility of property purchases, because property prices often rise faster than the growth rate of deposit savings. Therefore, this study was conducted which aims to analyze the relationship between inflation and deposit interest rates offered by banks and how inflation affects the real value of money saved in the form of deposit savings over a certain period of time. This study uses a quantitative method with descriptive analysis techniques and multiple linear regression for analysis purposes. The results of the study show that high inflation reduces people's purchasing power and reduces the real value of deposit savings, while deposit interest rates that are lower than the inflation rate can reduce people's ability to buy property. This study suggests that people consider inflation in planning long-term investments, especially in the form of property.

Indofood CBP Sukses Makmur Tbk Stock Price Prediction Using Long Short-Term Memory (LSTM) Saputra, Moch Panji Agung; Saputra, Renda Sandi; Dwiputra, Muhammad Bintang Eighista
International Journal of Global Operations Research Vol. 6 No. 1 (2025): International Journal of Global Operations Research (IJGOR)
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i1.363

Fluctuating stock price movements are a challenge in the investment world, so an accurate prediction model is needed to assist decision making. This study aims to evaluate the ability of the LSTM model to predict ICBP stock prices based on historical data and will compare the results of the LSTM model predictions with actual stock price movements to determine the extent to which this model is able to capture trends and patterns of ICBP stock prices. The results show a comparison of the original price and the predicted price indicating that the model can follow market trends, although there are still deviations at some points, especially when volatility is high. Residual analysis shows a distribution of prediction errors that is close to normal, indicating that the model does not experience significant bias. In addition, evaluation of the loss function on the training and validation data confirms that the model has converged well. In the performance evaluation, the model is able to capture stock movement patterns quite well, indicated by the Mean Absolute Error (MAE) value of 0.0231, Root Mean Squared Error (RMSE) of 0.0305, and Mean Absolute Percentage Error (MAPE) of 19.21%.

Implementation of Open Jackson Queueing Network on Customer Service and Ticket Service at Pasar Senen Train Station Jakarta Anisa Kisti, Vuji; Supian, Sudradjat; Nahar, Julita
International Journal of Global Operations Research Vol. 6 No. 1 (2025): International Journal of Global Operations Research (IJGOR)
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i1.344

The increase in the number of users of train services causes a buildup in various service facilities, which affects the quality and efficiency of services. This study aims to optimize the service system at Pasar Senen Station by applying the open Jackson queueing network model using the First Come First Serve discipline. The data used includes external arrival times, service times, and cost components at three main facilities: customer service locket, ticket counter locket, and ticket vending machine locket. The results showed that optimal performance was achieved at the ticket counter (M/M/3) and ticket vending machine (M/M/2) with a busy level of 82.14% and 62.66% respectively. Simulation of reducing the number of servers in customer service to two (M/M/2) results in a busy level of 77.95% and lower total costs.

Premium Sufficiency Reserve of Last Survivor Endowment Life Insurance Using Exponentiated Gumbel Distribution Putri, Viona Sephia; Sirait, Haposan
International Journal of Global Operations Research Vol. 6 No. 1 (2025): International Journal of Global Operations Research (IJGOR)
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i1.365

Life insurance is a protection eﬀort provided by the insurer against risks to the insured’s life that will arise from an unpredictable event. Insurance companies are required to prepare reserves to fulﬁll the sum insured when a claim occurs. Premium suﬃciency reserves are modiﬁed reserves whose calculations use gross premiums that contain administrative maintenance costs. The purpose of this study is to determine the amount of premium suﬃciency reserves of endowment life insurance for two insurance participants aged x years and y years using the exponentiated Gumbel distribution. The parameters of the exponentiated Gumbel distribution are estimated using the maximum likelihood method and then determined by a Newton-Raphson iteration method. The solution of the problem is obtained by determining the initial life annuity term, single premium, and annual premium so as to obtain the reserve formula of the premium suﬃciency of the last survivor status endowment life insurance using the exponentiated Gumbel distribution. The results of the calculation of reserves premium suﬃciency of endowment life insurance last survivor status using the exponentiated Gumbel distribution is slightly smaller than premium suﬃciency reserve for endowment life insurance using the Indonesian Mortality Table 2019.

Comparison of Grid Search and Random Search Effectiveness in Parameter Tuning on Electric Car Sentiment Analysis Saputra, Moch Panji Agung; Dwiputra, Muhammad Bintang Eighista
International Journal of Global Operations Research Vol. 6 No. 2 (2025): International Journal of Global Operations Research (IJGOR), May 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i2.371

The increasing use of electric cars in Indonesia has prompted many public discussions recorded on various digital platforms. This study aims to classify public sentiment towards the implementation of electric cars through comment analysis using the XGBoost Classifier model. The data used were obtained from the Kaggle platform, in the form of public comments that have gone through pre-processing stages, such as removing empty data, label encoding, and visualizing class distribution. Furthermore, the data was divided into training, validation, and test data using stratification techniques, and data imbalance was handled using the SMOTE method. Modeling was carried out using the XGBoost Classifier algorithm, then hyperparameter tuning was carried out using two approaches, namely Random Search and Grid Search. The parameters tested included learning_rate, max_depth, n_estimators, subsample, colsample_bytree, gamma, alpha, and lambda. The experimental results showed that the model without tuning produced an accuracy of 67%. After tuning, Random Search increased its accuracy to 68%, while Grid Search achieved the highest accuracy of 69%. Based on evaluation using precision, recall, f1-score, and accuracy metrics, tuning with Grid Search is proven to provide more optimal results compared to other methods. This study shows that systematic hyperparameter tuning can improve the performance of sentiment classification models.

Queue System Using Single Channel Single Phase For Gas Station Customers With An Arena Simulation Approach Arsal, Muhammad; Maulana, Ihsan; Firdaus, Afdal Asyuri
International Journal of Global Operations Research Vol. 6 No. 2 (2025): International Journal of Global Operations Research (IJGOR), May 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i2.372

The efficiency of the queuing system at a Public Fuel Filling Station (SPBU) is one of the crucial factors in maintaining smooth operations and increasing customer satisfaction. This study specifically analyzes the performance of the queuing system with a single channel single phase model at a gas station using a simulation approach assisted by Arena Simulation Software. The main focus of this study is to evaluate a number of performance indicators, such as average customer waiting time, queue length, server utilization rate, and service capacity that can be achieved under existing conditions and after the improvement scenario is implemented. Primary data was collected through direct observation in the field during peak hours, which were then processed and analyzed using probability distributions to model customer arrivals and service times. The simulation results show that the existing system has a very high server utilization rate, approaching 100%, indicating a potential risk of overload, although the average customer waiting time is relatively minimal. However, this performance can only be maintained under certain conditions and is at risk of decreasing significantly if there is a surge in customers beyond predictions. Simulation of the improvement scenario by significantly increasing the number of servers and operators succeeded in reducing the server utilization rate to the optimal level, shortening service time, and increasing the service capacity of the gas station. This proves that managerial intervention through the addition of service resources is a strategic step to increase operational efficiency.

Prediction Of Asteroid Hazard Distance Through Earth's Orbit Using K-Neirest Neighbor Method Firdaus, Syahrul; Witanti, Wina; Melina; Hadiana, Asep Id
International Journal of Global Operations Research Vol. 6 No. 2 (2025): International Journal of Global Operations Research (IJGOR), May 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i2.373

The National Aeronautics and Space Administration (NASA) is the U.S. government agency that is responsible forspace program. NASA observes objects in space, including asteroids. Asteroids are small, rocky objects that orbit thesun with irregular shapes and are also called planetoids. The Government agencies observe space objects includingasteroids. In terms of the infinite number of objects in space that will cross Earth's orbit, prediction is needed todetermine the danger and its level when they are crossing Earth's orbit. Prediction is a process to know what willhappen in the future which is aimed to find out the approximate asteroids that will cross the earth in the future. In thisstudy, data mining classification techniques and the K-Nearest Neighbor algorithm are used to create a predictionsystem for the threat of asteroids while crossing the earth. Classification is a grouping by classifying items intodesignated class labels, building a classification model from the data set, building a model that is used to predict futuredata. To determine the distance of the asteroid's threat throughout the earth, data mining classification techniques andthe K-Nearest Neighbor algorithm are used. The results are 57.71% accuracy, 54.89% precision, 81.42% recall, and47.45% missclassification rate.

Application of Registration Queue System Simulation with Multi Chanel-Multi Phase Method at Royal Prima General Hospital with Promodel Falleryan, Muhammad; P.S, Axel Juanito; Tosida, Eneng Tita; Sugara, Victor Ilyas; Nurcahya, Dimas; Subandi, Kotim
International Journal of Global Operations Research Vol. 6 No. 2 (2025): International Journal of Global Operations Research (IJGOR), May 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i2.374

Royal Prima General Hospital often faces the problem of patient accumulation, especially at the initial registration stage, which results in increased waiting time and decreased service quality. To overcome this problem, this study implemented a multi-channel multi-phase queuing system using Promodel simulation software. This method allows the distribution of patients into multiple lanes and service stages, thereby reducing congestion and shortening waiting times. The research data was taken from a simulation that included 500 patients in the first phase (registration) and 100 patients each in the second phase (internal medicine polyclinic) and third phase (neurology polyclinic). The simulation results show that the multi-channel multi-phase queuing system is able to handle the flow of patients effectively with an average waiting time of 1.75 minutes before receiving service. Facility utilisation rates show that the internal medicine and neurology polyclinic areas operate almost at full capacity (above 90%), while the admission area has an underutilised capacity (31.8%).

Dynamic System Simulation Design Projected Growth and Shrinkage of to Food Production in Sukabumi Rezaghani; Baskoro, Arif Dwi; Aprido, Eka; Tosida, Eneng Tita; Subandi, Kotim; Sugara, Victor Ilyas
International Journal of Global Operations Research Vol. 6 No. 2 (2025): International Journal of Global Operations Research (IJGOR), May 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i2.375

A rapid increase in population along with limited agricultural land can lead to shrinkage of paddy fields, which risks threatening food production and the sustainability of the agricultural sector in the region. This research uses a simulation modeling method with a dynamic system approach. The simulation model was designed based on data related to population growth and the decline in rice field area, as well as other factors that influence it. The dynamic system approach is often applied to analyze systems with many interdependent components. The iteration process in this system shows how changes in one element can affect other elements in the future through complex cause-and-effect relationships. Increased demand for land has contributed to the shrinkage of paddy fields, which in turn has reduced food production. In Sukabumi district, population growth increases land demand, thus accelerating the shrinkage of paddy fields and reducing food production in the region. Projections show that the population of Sukabumi District will grow by around 29% per year, reflecting the huge challenge of providing adequate services and infrastructure to the population.

MODELING OF QUEUES AT 3 KG LPG FILLING AND TRANSPORTATION STATIONS (SPPBE) WITH OPTIMIZATION OF PROMOTIONAL SERVICE STATIONS Zabrina, Siti; Nasyifa, Hesti; Febryand, Calvin
International Journal of Global Operations Research Vol. 6 No. 2 (2025): International Journal of Global Operations Research (IJGOR), May 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i2.376

Queues are a common problem that often arises from an imbalance between the arrival rate and the service capacity or facilities. Queues occur because customers (users) arrive at a service facility when the available service capacity is insufficient to handle the incoming demand. Queues often occur in the Single Channel - Single Phase queue system, which is observed at SPPBE (Filling and Transportation Stations for Bulk LPG). In the Single Channel - Multi Phase queue structure, queues also occur due to the accumulation of waiting time required for each service stage. Therefore, this research aims to explain the model and analyze the queue system that occurs at SPPBE, provide an explanation of the analysis results of the Single Channel - Single Phase queue model for two service locations, and use the Kolmogorov-Smirnov method for data conformity testing. The SPSS program was used to analyze the Single Channel - Single Phase queue model for two service locations and to use the Multi Channel - Multi Phase queue model for the two service locations.

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Editorial Address Jl. Merkuri Timur VI No. 1, RT. 007, RW. 004, Manjahlega, Rancasari, Kota Bandung, Jawa Barat, INDONESIA

Location Kota bandung, Jawa barat INDONESIA

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Contact Name
-

Contact Email
ijgor.iorajournal@gmail.com

Phone
+6285841953112

Journal Mail Official
ijgor.iorajournal@gmail.com

Editorial Address
Jl. Merkuri Timur VI No. 1, RT. 007, RW. 004, Manjahlega, Rancasari, Kota Bandung, Jawa Barat, INDONESIA

Location
Kota bandung,

Jawa barat

INDONESIA