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Operations Research: International Conference Series

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Published by Indonesian Operations Research Association

ISSN : 27231739 EISSN : 27220974 DOI : https://doi.org/10.47194/orics

Core Subject : Economy, Science, Education, Engineering,

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

Operations Research: International Conference Series (ORICS) is published 4 times a year and is the flagship journal of the Indonesian Operational Research Association (IORA). It is the aim of ORICS 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.

Arjuna Subject : Umum - Umum

Articles 131 Documents

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Generational Analysis of Financial Decision- Making Among Gen-X, Gen-Y, and Gen-Z Sudaryo, Yoyo; Suryaningprang, Andre; Sumawidjaja, Riyandi Nur; Febriyanti, Diah; Zulfiqar, Mochammad
Operations Research: International Conference Series Vol. 6 No. 3 (2025): Operations Research: International Conference Series (ORICS) September 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i3.397

This study aims to examine the influence of demographic factors on the financial decision-making behavior of three generational cohorts Gen-X, Gen-Y, and Gen-Z in urban Indonesia, focusing on Jakarta, Bandung, and Surabaya. Using a quantitative approach, data were collected through an online survey with 381 respondents and analyzed using ANCOVA and Kruskal- Wallis tests. The findings reveal that income significantly impacts financial decision-making, with higher-income individuals making more informed choices. Women and Gen-Y demonstrate stronger saving discipline and cost-optimization strategies, while city- specific patterns highlight differences in financial behaviors, such as timely payments and discount awareness. Gender and occupation show no significant overall effects, though some variations exist in specific behaviors. These results provide theoretical insights into behavioral accounting, particularly in understanding the role of income and demographic contexts in shaping financial behaviors. Practically, the study informs financial advisors and policymakers to design tailored education and advisory programs for different demographic groups. The study offers a novel contribution by utilizing ribbon chart visualizations to uncover intergenerational and intercity financial behavior patterns in Indonesia.

Analysis of Treatment Period for TB Patients Using The Kaplan-Meier Method Andini, Kiki Andini; Marsanda, Mareta; Wahyuni, Olivia Nindi; Prabowo, Agung
Operations Research: International Conference Series Vol. 6 No. 3 (2025): Operations Research: International Conference Series (ORICS) September 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i3.398

This study aims to analyze the duration of treatment for tuberculosis (TB) patients using the Kaplan-Meier method, a non-parametric approach in survival analysis. The research data comes from the Banyumas Regency Health Office for the period March 2023 to November 2023, with a total of 25 patients. The variables analyzed include gender, age, and treatment completion status. The results of the study showed that the chance of incomplete treatment was higher in male patients than in female patients, and the chance of incomplete treatment in patients aged >40 years was higher than in the age group ≤40. The Kaplan-Meier method was used to calculate the survival function, hazard function, and survival time distribution, which provides an in-depth understanding of the dynamics of TB treatment. These findings can assist policymakers in improving the effectiveness of TB treatment in Banyumas Regency.

Implementation of a Web-Based Water Quality Control System for Koi Ponds Using Mamdani Fuzzy Logic and the Laravel Framework Maulana, Muhamad Arif
Operations Research: International Conference Series Vol. 6 No. 3 (2025): Operations Research: International Conference Series (ORICS) September 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i3.399

This study presents the design and implementation of a web-based water quality control system for koi ponds using Mamdani fuzzy logic and the Laravel framework. The system integrates pH, TDS, and temperature sensors with an ESP32 microcontroller to monitor water conditions in real-time. The fuzzy logic controller processes sensor inputs and automatically activates pumps to inject acid or base solutions, thereby maintaining optimal water quality. Test results show that the pH sensor achieved an average accuracy of 95.27% with an error rate of 4.73%, while the TDS and temperature sensors recorded accuracies of 97.95% and 98.35%, respectively. The fuzzy control system demonstrated a very low error rate of 0.93%, ensuring precise decision-making. The Laravel-based web application successfully displayed and recorded monitoring data with only a 1–2 second delay, providing a user-friendly interface for farmers. Overall, the system effectively improves aquaculture productivity and reduces the risk of fish mortality by offering automated and accurate water quality management.

Analysis of Non-Performing Loans at PT Bank BRI Tbk (2019–2023) Musadat, Irfan Achmad; Putra, Okta Eka; Kusumawardhani, Aninditha Putri
Operations Research: International Conference Series Vol. 6 No. 3 (2025): Operations Research: International Conference Series (ORICS) September 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i3.400

This study aims to analyze the Non-Performing Loan (NPL) ratio of PT Bank BRI Tbk during the 2019–2023 period by applying a descriptive approach combined with horizontal financial analysis. The research relies on secondary data obtained from the bank’s published financial statements on the Indonesia Stock Exchange (IDX). The analysis focuses on NPL as a key indicator of credit risk without exploring causal relationships among variables. The findings show that Bank BRI’s NPL ratio remained below the regulatory threshold of 5% set by Bank Indonesia, indicating that the bank was in a relatively stable condition. However, annual fluctuations highlight the importance of strengthening credit risk management, particularly in periods of economic uncertainty and aggressive credit expansion. The results emphasize that while the overall performance remains within a safe limit, proactive strategies are required to sustain long-term credit quality.

Implementation of Inclusive Closed Loop in Improving Production Efficiency and Sustainability Endarwan, Hendy; Rasyid, Aliy; Etwanto, Gary Putra
Operations Research: International Conference Series Vol. 6 No. 3 (2025): Operations Research: International Conference Series (ORICS) September 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i3.401

Amidst increasing external pressures related to sustainability, such as international regulations, stakeholder expectations, and global consumer demands, the rubber industry is required to develop internal strategies that are not only operationally efficient but also adaptive to the transformation towards environmentally friendly production and supply chain practices. This study aims to analyze the implementation of an inclusive closed-loop supply chain as a strategic approach for companies to integrate production efficiency, waste reduction, and respond to institutional pressures for sustainability. The novelty of this study lies in the integration of an inclusive closed-loop approach that goes beyond the traditional concept of recycling, prioritizing the active participation of all internal actors (production, procurement, sustainability) and strengthening cross-functional relationships within the organization as the basis for the transition to a green supply chain. This research is built on a combined theoretical framework: the Natural Resource-Based View (NRBV) to explain internal capabilities in creating a competitive advantage based on sustainable resources; Institutional Theory to identify the influence of external pressures on organizational behavior; and Stakeholder Theory to explore the dynamics of expectations and the involvement of key actors in the value chain. The method used is a quantitative explanatory approach, with data collection through a survey of managers at rubber processing companies in Indonesia. Data were analyzed using Structural Equation Modeling - Partial Least Squares (SEM-PLS) to examine the relationships between inclusive closed-loop dimensions, operational efficiency, green supply chains, and companies' strategic adaptation to sustainability pressures. The expected results indicate that inclusive closed-loop supply chains contribute significantly to achieving operational efficiency and waste reduction, while strengthening companies' capabilities in building environmentally friendly supply chains and production processes. These findings are expected to provide theoretical contributions to the development of resource- and institutional-based sustainability strategies, as well as practical implications for companies responding to global challenges through inclusive and sustainable business model transformations.

Bankruptcy Probability Analysis of PT XYZ Using a Heavy-Tail (Pareto) Discrete Surplus Model Laila, Aliffatul; Janitha, Asrie Putri
Operations Research: International Conference Series Vol. 6 No. 4 (2025): Operations Research International Conference Series (ORICS), December 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i4.420

The insurance industry plays a strategic role in maintaining societal financial stability by providing protection mechanisms against unforeseen risks. However, the risk of bankruptcy remains a real threat when policyholder claims exceed the company's reserve funds and collected premiums. This necessitates a quantitative approach capable of projecting bankruptcy probability more accurately. This study is designed to analyze the bankruptcy probability of PT XYZ by utilizing a discrete surplus model based on the heavy-tail Pareto distribution. This model was selected due to its characteristics, which can effectively represent large, infrequent claims that nonetheless have a significant impact on the company's financial condition. The research data will be sourced from the company's financial reports and used in the bankruptcy probability modeling process employing the Pareto distribution approach. This research is expected to provide a theoretical contribution by enriching actuarial literature, particularly concerning the application of heavy-tail surplus models in bankruptcy risk analysis. It also aims to offer practical benefits for insurance companies in designing more comprehensive risk management strategies. Furthermore, the study's findings are hoped to provide valuable input for regulators in strengthening policyholder protection policies and supporting the stability of the national insurance industry. Keywords: Bankruptcy, Insurance, Surplus model, Heavy-tail, Pareto Distribution

Comparison of Maximum Likelihood Estimation and Median Rank Regression Methods in Weibull Distribution Parameter Estimation Timothy, Andreas; Akmal, Fatahillah
Operations Research: International Conference Series Vol. 6 No. 4 (2025): Operations Research International Conference Series (ORICS), December 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i4.421

The Weibull distribution is widely used in reliability analysis and risk management due to its flexibility in modeling failure patterns. This study aims to compare two methods for estimating Weibull distribution parameters, namely Maximum Likelihood Estimation (MLE) from Median Rank Regression (MRR). The data used consists of simulation data with varying parameters and sample sizes, as well as case study data.shock absorber dataset from the library weibulltools containing failure time and censored data. Parameter estimation with MLE is performed using the Newton–Raphson algorithm, while MRR is performed through linear transformation and regression. Performance evaluation is performed using bias measures and Mean Squared Error (MSE) on simulated data, as well as Kolmogorov–Smirnov and Anderson–Darling tests on case study data.

Investigating Long-Run and Short-Run Dynamics of Palm Oil Production with Key Factors Using the VECM Method Lathifah Zahra; Gustriza Erda
Operations Research: International Conference Series Vol. 6 No. 4 (2025): Operations Research International Conference Series (ORICS), December 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i4.429

This study investigates the long-run and short-run relationships among palm oil production, rainfall, the number of bunches per palm (NOB), and average bunch weight (BTR) using the Vector Error Correction Model (VECM). Monthly data from 2015 to 2024 obtained from PT Perkebunan Nusantara IV (PTPN IV) Regional III, Sei Rokan Estate, were analyzed. Descriptive statistics indicate high variability in rainfall and relatively balanced distributions for production, NOB, and BTR. The Augmented Dickey-Fuller (ADF) test confirmed that all variables became stationary after first differencing, and the Johansen cointegration test identified three cointegrating relationships, suggesting both short-run and long-run linkages among variables. The VECM estimation results reveal positive long-run relationships for palm oil production (ECT = 0,052), rainfall (ECT = 0,090), and NOB (ECT = 0,042), indicating that these variables move toward long-run equilibrium in the same direction. In the short run, previous rainfall significantly affects both current palm oil production and NOB, with coefficients of 0,203 and 0,178, respectively, highlighting the critical role of rainfall fluctuations in influencing short-term productivity and fruit development. Model evaluation using the Root Mean Square Error (RMSE) shows low prediction errors across all variables, with rainfall having the highest RMSE (1,334) and NOB the lowest (0,962), confirming the model’s strong predictive performance. Overall, the findings demonstrate that the VECM approach effectively captures both long-run equilibrium and short-run dynamics among key determinants of palm oil productivity in the Sei Rokan plantation.

Palm Oil Production Forecasting Using the SARIMA Model at the Terantam Plantation of PTPN IV Regional III in 2025 Eky; Erda, Gustriza
Operations Research: International Conference Series Vol. 6 No. 4 (2025): Operations Research International Conference Series (ORICS), December 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i4.430

Palm oil is one of the important plantation commodities that plays a major role in the Indonesian economy because it contributes to state revenues, making palm oil production crucial. Forecasting palm oil production is essential to support effective planning and decision-making in plantation management. This study aims to forecast palm oil production at the Terantam Plantation of PTPN IV Regional III for the year 2025 using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The data used consist of monthly production data based on volume (kg) from January 2014 to December 2024. The results of the analysis indicate that the best model obtained is SARIMA(0,1,4)(0,1,1)12 with the smallest Akaike Information Criterion (AIC) value. Diagnostic tests show that the model residuals behave as white noise and are normally distributed, indicating that the model is suitable for forecasting. The Mean Absolute Percentage Error (MAPE) value of 8.02% indicates a very good level of accuracy. The forecasting results reveal a seasonal pattern in palm oil production, with the highest production in September 2025 amounting to 15,108,145 kg, and the lowest in February 2025 at 9,347,573 kg. Overall, the SARIMA model is able to capture both trend and seasonal patterns effectively, making the forecast results useful as a reference for production planning and operational management at the Terantam Plantation. Furthermore, the findings of this study are expected to serve as a reference for applying similar forecasting methods to other plantation commodities.

Design of Mobile Robot Transporter Prototype Using Sensor Vision and Fuzzy Logic Method Setiawan, Aan Eko; Mardiati, Rina; Firdaus, Haddy
Operations Research: International Conference Series Vol. 6 No. 4 (2025): Operations Research International Conference Series (ORICS), December 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i4.437

The industrial field has experienced significant developments in the automation process, especially robots play an important role in the world of automation. One type of robot used in industry is a transporter robot. This research designs and develops a prototype mobile robot transporter that uses Pixy camera as a visual sensor and Mamdani fuzzy logic control method to control the speed of DC motor. This robot is able to move objects based on color using Arduino UNO as a microcontroller, motor driver shield L298N, two DC motors, and gripper module as actuators. The distance and speed of the robot are determined to ensure the ability to approach and move objects based on color appropriately. Testing of the robot system is done with X position value and area as parameters. Simulation of the experiment was carried out with a case study of the X position value of 73 and an area of 1012. Robot testing is done using simulation software and Arduino IDE which is then calculated manually for comparison. The results obtained in testing with simulation software are 88.70 PWM for the right DC motor and 76.10 PWM for the left DC motor. Based on the data obtained from simulation software, testing with Arduino IDE, and manual calculations, an error value of 0.158% for the right DC motor and 0.092% for the left DC motor was found. Additional tests were carried out with variations in the distance of the object being moved as well as the transfer of the object to the destination. These results show that Mamdani fuzzy logic control is effective in controlling the transporter robot, allowing accurate maneuvering and adaptive to environmental changes.

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

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Contact Name
-

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orics.iorajournal@gmail.com

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+6285841953112

Journal Mail Official
orics.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