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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 125 Documents

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A Study of Public Opinion on the 2024 Regional Elections Using Cosine Similarity and TF-IDF Algorithms Hidayat, Ari; Qurania, Arie; Iqbal, Mohamad
Operations Research: International Conference Series Vol. 6 No. 1 (2025): Operations Research International Conference Series (ORICS), March 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i1.364

The organization of general and regional head elections is an essential aspect of implementing an indirect democracy system. The primary objective of regional elections is to ensure that leaders are elected democratically and act on behalf of the people. The simultaneous holding of regional head elections has become a major topic of public discussion, giving rise to diverse opinions, particularly among Twitter users. This study aims to classify public opinion regarding the 2024 regional head elections using TF-IDF weighting, followed by a classification process with the Cosine Similarity algorithm. Of the 1,000 data points successfully scraped, 34.9% were classified as positive sentiment, 23.5% as negative sentiment, and 37.1% as neutral sentiment

SIGNAL App Review Sentiment Analysis using Support Vector Machine (SVM) on Google Play Store Comments Saputra, Moch Panji Agung; Dwiputra, Muhammad Bintang Eighista
Operations Research: International Conference Series Vol. 6 No. 1 (2025): Operations Research International Conference Series (ORICS), March 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i1.366

The SIGNAL (National Digital Samsat) application is a digital innovation that makes it easier to pay motor vehicle taxes in Indonesia. This study aims to analyze user sentiment towards the SIGNAL application through reviews on the Google Play Store, using Support Vector Machine (SVM) as a classification method. The analysis process includes the stages of review data collection, pre-processing (text cleaning, tokenization, stopword removal, and stemming), text transformation to numeric features using Term Frequency-Inverse Document Frequency (TF-IDF), and SVM model training. The dataset is taken from 10,000 of the latest reviews consisting of reviews classified into three sentiment categories: positive, negative, and neutral. The evaluation results show that the SVM model has a high accuracy of 91%, with consistent precision, recall, and F1-score values in each sentiment category. Positive sentiment dominates reviews (59%), followed by negative sentiment (33.8%) and neutral (7.2%). This analysis provides valuable insights for developers to improve the quality of applications, especially in understanding user needs and expectations.

Dynamic Modeling of Catfish Farming Development Using iThink Software Febrian, Muhamad Zidane; Saka, Bima Ariya; Werdaya, Rangga Kusumah Putra Marsha; Tosida, Eneng Tita; Subandi, Kotim; Sugara, Victor Ilyas
Operations Research: International Conference Series Vol. 6 No. 1 (2025): Operations Research International Conference Series (ORICS), March 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i1.367

This study analyzes the development of catfish farming in the Special Region of Yogyakarta (DIY) using a dynamic systems approach with iThink software. The model evaluates the relationships between local production, demand, external supply, and market prices over a 10-year period. The results indicate that local production can only partially meet demand, leading to a high dependency on external supply, primarily from Boyolali Regency and East Java. Simulations identify optimal strategies to enhance production efficiency, maximize land utilization, and reduce reliance on external supply. Model validation demonstrates that the simulation results align with historical data, making it a reliable tool for supporting sustainable strategic policy planning. This study is expected to provide solutions for food security and strengthen the self-sufficiency of the fisheries sector in DIY.

Dynamic Simulation Model of Garlic Availability in Bali Using iThink Software Hafizi, Muhamad; Hafiz, Syauqi Abyan; Sugiharto, Bambang; Tosida, Eneng Tita; Subandi, Kotim; Sugara, Victor Ilyas
Operations Research: International Conference Series Vol. 6 No. 1 (2025): Operations Research International Conference Series (ORICS), March 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i1.368

Fluctuations in local production, increasing demand, and dependence on garlic supplies from outside the island make it difficult for Bali Province to maintain a stable garlic supply. iThink software is used to model the dynamic garlic availability system in this study. This simulation method involves creating a Causal Loop Diagram (CLD), creating a mathematical model based on differential equations, and conducting table and graphical analysis of the simulation results. The simulation results show that the linear increase in garlic demand of 6,289.08 tons per year can be offset by local production increasing to 31,071.73 in 2024 and an off-island supply of 4,176 tons per year. The projection of garlic availability until 2024 is 122,895.71 tons. The results show that maintaining a stable supply of off-island garlic is the main way to ensure sustainable garlic availability in Bali.

Prediction of Chicken Meat Availability in Cilegon City Using iThink Dynamic Simulation Model Firdaus, Muhamad Haikal; Sauri, Ahmad Sopyan; Turrohman, Syaifa; Tosida, Eneng Tita; Subandi, Kotim; Sugara, Victor Ilyas
Operations Research: International Conference Series Vol. 6 No. 1 (2025): Operations Research International Conference Series (ORICS), March 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i1.369

The availability of chicken meat is a crucial factor in maintaining price stability and food security in Cilegon City. The increasing demand, influenced by population growth and consumption patterns, must be balanced with optimal supply from farmers and distributors. This study aims to predict the availability of chicken meat using a dynamic simulation model based on iThink. This model is built with a stocks and flows approach and causal loop diagrams to understand the dynamics of the system involving production, import, distribution, consumption, and external factors such as government policies and weather conditions. The simulation results show that the balance of supply and demand is greatly influenced by the level of local production, per capita consumption levels, and import policies. The simulation scenario also reveals that increasing production efficiency and optimizing distribution can increase the availability of chicken meat in the market by 15-20% in the next five years. This model is expected to be a tool for stakeholders in formulating more adaptive policies to maintain the stability of supply and prices of chicken meat in Cilegon City.

Dynamic Simulation of Doctor Needs in East Java Province By Using iThink Zabrina, Siti; Nasyifa, Hesti; Febryan, Calvin; Tosida, Tita; Subandi, Kotim; Sugara, Victor Ilyas
Operations Research: International Conference Series Vol. 6 No. 1 (2025): Operations Research International Conference Series (ORICS), March 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i1.370

This study compares the calculation of doctor needs in East Java Province using two dynamic simulations, namely iThink and Python. The purpose of this study is to identify differences in results between the two simulation platforms in estimating the need and availability of doctors based on population growth and the number of medical graduates. The methodology used involves modeling population dynamics and the flow of active doctors by considering the inflow of medical students and the WHO ratio. The results of the iThink simulation show an increase in the number of active doctors from 42,000 to 63,793 in 10 years, approaching the ideal WHO ratio, while the Python simulation shows a significant gap between the need and the number of doctors, with the need reaching 257,680 doctors in 2029, but the number of active doctors only reaching 21,686. This difference is due to variations in the methodology and approach of each platform. The conclusion of this study shows the importance of policy interventions to meet the need for doctors in the future and reduce the gap between the need and availability of doctors.

Implementing EfficientNetB0 for Facial Recognition in Children with Down Syndrome Pirdaus, Dede Irman; Dwiputra, Muhammad Bintang Eighista; Saputra, Moch Panji Agung
Operations Research: International Conference Series Vol. 6 No. 2 (2025): Operations Research International Conference Series (ORICS), June 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i2.383

Early detection of Down Syndrome in children is crucial to provide more appropriate medical and educational interventions. This study aims to build and evaluate a deep learning-based classification model using the EfficientNetB0 architecture to distinguish facial images of children with Down Syndrome and healthy children. The dataset used consists of two classes (Down Syndrome and healthy), which have gone through an augmentation process to increase data diversity and prevent overfitting. The model was trained using the Adam algorithm with a learning rate of 0.0001 and a sparse categorical crossentropy loss function for 10 epochs. The training results showed that the model achieved a validation accuracy of 93.94%, with the lowest validation loss value of 0.2390. Further evaluation was carried out using a confusion matrix, which showed that the model was able to properly classify 312 out of 333 Down Syndrome images and 309 out of 330 healthy children images, resulting in an overall accuracy of 94%. In addition, the precision, recall, and f1-score values for both classes were in the range of 0.94, indicating a balanced and strong performance. Visual analysis of the misclassified images indicates that some misclassifications occur on healthy children’s faces with certain expressions, angles, or lighting conditions that resemble Down syndrome. Conversely, some children with Down syndrome are also predicted as healthy when their facial features are not too prominent or similar to normal children under certain lighting conditions. This shows that despite the high performance of the model, sensitivity to facial feature variations remains a challenge.

Estimation of the Three-Parameter Inverse Rayleigh Distribution Parameters for Guinea Pig Survival Data Faradila, Eky; Utari, Farah Asyifa; Zahra, Lathifah; Novitasari, Ratna; Astuti, Syaftiani Dwi; Sirait, Haposan
Operations Research: International Conference Series Vol. 6 No. 2 (2025): Operations Research International Conference Series (ORICS), June 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i2.384

The Generalized Transmuted Inverse Rayleigh Function (GTIR) distribution is an extension of the inverse Rayleigh distribution, which is commonly used to model reliability and survival data. By incorporating an additional shape parameter (α) and a transmutation parameter (λ) alongside the scale parameter (σ), this distribution offers greater flexibility in handling skewed data or data with a non-monotonic hazard function. The parameters of the GTIR distribution are estimated using the Maximum Likelihood Estimation (MLE) method; however, they must be solved implicitly through numerical procedures. In this study, the GTIR distribution was employed to analyze the survival data of guinea pigs infected with tuberculosis. The primary objective of this analysis was to estimate the distribution parameters and to provide an overview of the survival pattern. The application of the GTIR distribution to the survival and hazard functions demonstrated that guinea pigs experience a sharp decline in survival probability at the onset of tuberculosis infection, followed by a gradual decrease in the risk of mortality over time. The hazard rate pattern, which initially increases and then decreases, indicates that the most critical period occurs immediately after infection. Parameter estimation of the GTIR distribution using the MLE approach yielded estimates of λ = 0.781, α = 10.135, and σ = 12.319, confirming that this model effectively captures the complex survival pattern with high accuracy.

Indirect Methods for Personalized Mean-CVaR Portfolio Optimization Setyawan, Deva Putra; Salih, Yasir
Operations Research: International Conference Series Vol. 6 No. 2 (2025): Operations Research International Conference Series (ORICS), June 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i2.385

This study presents a reformulation of the Personalized Mean-CVaR model into an unconstrained optimization problem, which is then solved using iterative methods, including steepest descent and Newton’s method. The reformulation introduces challenges related to feasibility region checking, convexity of the feasible set and objective functions, and the use of Lagrange multipliers to handle constraints. Additionally, Taylor expansion is utilized to approximate the objective function in each iteration. The research evaluates the effectiveness of iterative optimization techniques in solving the Personalized Mean-CVaR problem, while addressing key challenges in convergence and stability of the solution.

Failure Mode and Effect Analysis (FMEA) for Improving the Efficiency of a Two Combustion Chamber Downdraft Gasification Stove Suryaman; Zakaria, Kiki; Yuningsih, Siti Hadiaty
Operations Research: International Conference Series Vol. 6 No. 2 (2025): Operations Research International Conference Series (ORICS), June 2025
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v6i2.387

The growing energy demand in areas lacking access to modern infrastructure drives the development of biomass-based thermal technologies, such as the dual-chamber downdraft gasification stove. This stove offers higher efficiency and lower emissions compared to direct combustion but still poses failure risks in various system components. This study aims to identify critical failure modes affecting the thermal efficiency of the stove through the Failure Mode and Effect Analysis (FMEA) approach. The analysis involved mapping the system's structure and functions, followed by evaluating failure modes using three parameters: Severity (S), Occurrence (O), and Detection (D) to obtain the Risk Priority Number (RPN). Results indicate the highest risk occurs in the combustion system (RPN 180), followed by the air control system (RPN 160). Key causes include suboptimal secondary air distribution and valve blockage. Other systems such as insulation, maintenance access, safety, and fabrication had lower RPNs but still require design and quality control improvements. Recommendations focus on improving airflow design, using high-temperature-resistant materials, and adopting precision fabrication procedures. Using the FMEA approach, the gasification stove can be enhanced in terms of reliability, efficiency, and user safety, making it more feasible as a small-scale renewable energy solution for communities.

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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
orics.iorajournal@gmail.com

Phone
+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