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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 10 Documents

Search results for , issue "Vol. 6 No. 2 (2025): International Journal of Global Operations Research (IJGOR), May 2025" : 10 Documents clear

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.

The Application of Dynamic Simulation for Determining Competitive Sales Strategies of Cassava Chips Using iThink Falleryan, Muhammad; Juanito, Axel; Nurcahya, Dimas; 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.v6i2.377

This study aims to determine sales strategies for cassava chips through a dynamic simulation approach using iThink software. The simulation is used to model the factors influencing sales performance, such as fluctuations in raw material prices, operational costs, and market demand patterns. By employing a CLD (Causal Loop Diagram) model and dynamic simulation, this research evaluates various strategies, including product diversification, digital promotion, and distribution efficiency. The simulation results indicate that implementing strategies such as flavor variant diversification and increased promotion through social media can significantly improve sales and profits. Validation was carried out through sensitivity testing on cost and sales parameter changes, demonstrating that dynamic simulation can be an effective tool to support data-driven strategic decision-making

Forecasting the Unseen: A Stationary Distribution Approach to Earthquake Magnitude Prediction in Bengkulu Megantara, Tubagus Robbi; Hidayana, Rizki Apriva
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.v6i2.379

Long-term forecasting of earthquake magnitudes plays a vital role in seismic hazard assessment and disaster mitigation, particularly in highly active seismic regions such as Bengkulu, Indonesia. This study introduces a probabilistic framework based on the stationary distribution of discrete-time Markov chains to predict the likelihood of various earthquake magnitudes over an extended period. Historical earthquake records from Bengkulu are categorized into discrete magnitude classes to form the states of the Markov chain. Transition probabilities between these states are estimated from the data, allowing for the construction of a transition matrix that accurately reflects the temporal dynamics of seismic activity. By analyzing the stationary distribution of this Markov chain, we derive the long-term probabilities of occurrence for each magnitude class, revealing inherent patterns in earthquake magnitudes that are otherwise difficult to capture with traditional methods. The stationary distribution serves as a stable, time-independent descriptor of the seismic regime, providing insights into the expected distribution of earthquake magnitudes in the future. The results indicate that this approach not only captures the probabilistic behaviour of seismic magnitudes but also offers a computationally efficient and interpretable model for earthquake forecasting. This modelling technique complements existing seismic hazard assessments and has practical implications for risk management and emergency preparedness in Bengkulu and other seismically active areas. Future research will explore the integration of spatial factors and earthquake depth to further enhance prediction accuracy.

Investment Strategy in the Banking Sector: Probability Ratio Analysis and Comparison of Financial Performance in Core Bank Group 4 (BCA, BRI, BNI, Mandiri) Wardoyo, Chess Satriya; Suryadi, Joanes Ferdienand
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.v6i2.380

This study aims to analyze performance bank finances in KBMI group 4 (Bank BCA, BRI, BNI, and Mandiri ) with a focus on the ratio profitability as a foundation taking decision investment . Using the method descriptive comparatively , this study analyzes financial data in five year period Lastly , with a focus on the Return on Assets (ROA), Return on Equity (ROE), Net Interest Margin (NIM), and Cost of Goods (Cash) indicators . Operational to Income Operational (BOPO). Research results show that there is difference significant in profile profitability the four banks, with BCA showing consistency highest in profitability and efficiency operational . BRI shows superiority in NIM, while Mandiri and BNI show improvement stable performance . Investment strategy model formulated based on analysis risk -return, cycle economy , and trends industry banking . This research provides different investment strategy recommendations based on profile investor risk , taking into account special to impact digital transformation and change regulation in the sector Indonesian banking .

Comparison of Activation Functions in Recurrent Neural Network for Litecoin Cryptocurrency Price Prediction Yuningsih, Siti Hadiaty; Ismail, Muhammad Iqbal Al-Banna
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.v6i2.381

The rapid advancement of information technology and digitalization has significantly transformed the financial sector, particularly with the emergence of cryptocurrencies characterized by high price volatility and complex movement patterns. Accurate price prediction of these crypto assets is essential to support investment decision-making and risk management. This study aims to compare the performance of six activation functions ReLU, Tanh, Sigmoid, Softplus, Swish, and Mish in a Simple Recurrent Neural Network (RNN) model for predicting the price of Litecoin, a widely traded cryptocurrency. Using historical daily closing price data from May 2020 to April 2025, the data were preprocessed through Min-Max normalization and sliding window sequence formation to fit the RNN input requirements. Each activation function was applied in the RNN model under consistent training conditions, and model performance was evaluated using Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and coefficient of determination (R²). Results indicate that the Swish activation function outperforms others by achieving the lowest RMSE of 4.58 and the highest R² score of 0.9578, demonstrating superior prediction accuracy and stable convergence. Tanh also showed competitive results, while Sigmoid and Softplus performed less effectively. In conclusion, Swish is recommended as the most suitable activation function for RNN-based cryptocurrency price forecasting due to its balance of accuracy and computational efficiency.

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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