Jurnal Optimasi Sistem Industri: Announcements
type: channel
description: Jurnal Optimasi Sistem Industri (JOSI) with ISSN: 2442-8795 (online medium) and 2088-4842 (print medium), translated as Journal on Optimization of Systems in Industries, is a distinguished peer-reviewed, open-access scholarly periodical. Since its inception in 2001, JOSI has been dedicated to publishing high-quality research papers, technical papers, conceptual papers, and case study reports that undergo a rigorous peer-review process, ensuring the highest standards of scholarly integrity. The journal's publication frequency is 2 issues/year: June & December. Published by the Industrial Engineering Department at Universitas Andalas, Padang, West Sumatra, Indonesia, JOSI focuses on optimising soft systems aspects of industrial operations and engineering. While we welcome discussions on hard systems, these must clearly optimise soft system aspects as outlined in our focus and scope. Our commitment to interdisciplinary approaches is aligned with the United Nations' Sustainable Development Goals, particularly in quality education, decent work and economic growth, industry innovation, and responsible consumption and production. JOSI ensures unrestricted access to all articles under open licenses, promoting the free dissemination of knowledge without charging any publication fees. This approach supports the global academic community by making research accessible to everyone. We accept manuscripts in English and facilitate the translation of articles submitted in other languages, subject to a translation fee before publication acceptance, ensuring inclusivity and accessibility for authors worldwide. JOSI is indexed by Scopus, Q3 in Scimago Journal Rank, the DOAJ, and Sinta, attesting to our quality and impact in the field of industrial engineering. We maintain strong collaborations with The Institution of Engineers Indonesia (Persatuan Insinyur Indonesia) and BKSTI (Badan Kerjasama Penyelenggara Pendidikan Tinggi Teknik Industri), which provide editorial members, peer revi…
language: en-US
items: General information: Article Processing Charge Policy
items: General information: New Issue Published (Vol. 24 No. 2, 2025)
items: Notes: System of Systems Engineering - Enhancing Industrial Integration and Optimization
items: Notes: Metaheuristic Algorithms: Solving Complex Industrial Challenges
items: General information: Happy 80th Independence Day, Indonesia
items: Notes: Simulation-Based Optimization: Unlocking Industrial Efficiency
items: General information: JOSI Vol. 24 No. 1 (June 2025)
items: Notes: The Internet of Things and Connectivity: Transforming Industrial Optimization
items: Notes: Sustainable Manufacturing Practices: Shaping the Future of Industrial Systems
items: General information: JOSI Reaches Q3 in SCImago Journal Rankings
items: Notes: Advanced Automation and Robotics: Redefining Industrial Efficiency
items: Notes: Artificial Intelligence and Machine Learning: Transforming Industrial Optimization
items: Notes: Optimizing Industrial Systems - The Expected Future Trends
items: General information: Volume 23, Issue 2 is Now Live!
items: Notes: Jurnal Optimasi Sistem Industri: Scopus-Indexed Diamond Open Access Journal
items: Notes: The Future of Industrial Optimization with GPT: Bridging Innovation, Ethics, and Sustainability
items: Notes: How GPT Aligns with the United Nations' Sustainable Development Goals (SDGs)
items: Notes: Interdisciplinary Applications of GPT: Bridging the Gap Between Technology and Industrial Engineering
items: Notes: How GPT Enhances Soft Systems Methodologies in Industrial Engineering
items: Notes: New article series: Relevance of GPT in Industrial Engineering
items: General information: Exciting Updates: New Server Launch and Important Information for Users
items: Notes: Sustainability in Industrial Systems: The Role of Soft Systems
items: Notes: The Role of Technology in Supporting Soft Systems Optimization
items: Notes: Building a Culture of Continuous Improvement Through Soft Systems Optimization
items: Notes: Understanding Industrial Systems: A Focus on Soft Systems
items: Notes: The Journey Toward Optimal Solutions – How Gradients and Convexity Shape Optimization

General information: Article Processing Charge Policy
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description: Effective Date: March 1, 2026 In order to maintain high publication quality, improve editorial and production processes, and ensure long‑term sustainability, Jurnal Optimasi Sistem Industri (JOSI) will begin implementing an Article Processing Charge (APC) for accepted manuscripts. Key Points of the Policy The APC applies only to manuscripts accepted for publication, starting with submissions received on March 1, 2026. Manuscripts submitted before this date will not incur any APC, regardless of their acceptance date. Details regarding the payment procedure will be provided in a separate announcement and updated on the JOSI website. Article Processing Charge (APC) Overseas authors: USD 300 Indonesian authors: IDR 5,000,000 This policy supports: Continuous improvement of editorial and peer-review processes Enhanced digital publishing services Long‑term sustainability of open access operations We appreciate the continued support and contributions from authors, reviewers, and readers. Your engagement helps JOSI maintain its mission to disseminate high‑quality research in industrial systems optimization. For further information, please contact: Email: editor_josi@eng.unand.ac.id
creator: Jurnal Optimasi Sistem Industri
date: 2026-02-10

General information: New Issue Published (Vol. 24 No. 2, 2025)
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description: Jurnal Optimasi Sistem Industri (JOSI) has published Vol. 24 No. 2 (2025), released on December 31, 2025. This issue includes 11 articles that address practical industrial and systems problems across operations, human factors, product design, sustainability, and digital adoption. The articles examine facility layout decisions that account for safety distances and geometric constraints, inbound scheduling for resource-constrained warehouses, and EV route planning that considers charging stops and recharging time. The issue also includes research on human factors in railway maintenance, such as ergonomic risk assessment, what makes people wear hearing protectors, and how to use fNIRS to measure cognitive load. In product and design engineering, the issue includes a study on the design of luxury train seats that integrates emotional perception and local wisdom, as well as a systematic review on flexible FDM 3D-printed insoles for flatfoot treatment. Several papers connect sustainability and digital behavior to industrial outcomes, including consumer responses to greenwashing in single-use plastics, acceptance of food waste mobile applications, and a conceptual model of digitalization and sustainability indicators for SMI resilience. Authors in this issue come from Indonesia, Australia, Germany, Malaysia, the Netherlands, Brazil, Canada, and the United States. We thank all authors who contributed to this issue of Jurnal Optimasi Sistem Industri (JOSI) for sharing their research and for their careful work in preparing manuscripts that advance industrial engineering and systems optimization. Their studies strengthen the evidence base for decision-making in operations, human factors, design, and sustainability, and they help connect rigorous methods with practical needs in industry and society. We also invite our readers to submit their best research reports to JOSI. We welcome original studies, applied casework, and well-designed reviews that offer clear methods, transpar…
creator: Jurnal Optimasi Sistem Industri
date: 2025-12-31

Notes: System of Systems Engineering - Enhancing Industrial Integration and Optimization
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description: In modern industrial operations, complexity is increasing as organizations manage multiple interconnected systems that must work together seamlessly. Traditional optimization approaches often focus on improving individual components, but in reality, industries operate as interdependent networks where changes in one system influence the performance of others. This is where System of Systems Engineering (SoSE) emerges as a transformative approach, enabling industries to optimize large-scale, interconnected systems holistically rather than in isolation. System of Systems Engineering extends beyond traditional engineering methodologies by focusing on how distinct subsystems interact and contribute to overall industrial efficiency. This approach is particularly valuable in industries such as manufacturing, logistics, and energy, where multiple systems—such as supply chains, production facilities, and distribution networks—must be synchronized for maximum efficiency and resilience. One of the core benefits of SoSE is its ability to manage complexity by integrating disparate subsystems under a unified framework. By leveraging advanced modeling techniques, industries can simulate interactions between systems, anticipate bottlenecks, and optimize resource allocation. For example, in large manufacturing ecosystems, integrating production scheduling with real-time inventory tracking and logistics operations allows companies to minimize downtime and reduce costs. In the energy sector, SoSE plays a crucial role in optimizing power generation and distribution networks. By integrating renewable energy sources, smart grids, and real-time demand forecasting, energy providers can achieve greater sustainability and reliability. The ability to manage multiple energy systems dynamically is essential in transitioning toward greener and more efficient energy infrastructures. Another key advantage of SoSE is its role in enhancing resilience. In industries where supply chains span multiple …
creator: Jurnal Optimasi Sistem Industri
date: 2025-12-01

Notes: Metaheuristic Algorithms: Solving Complex Industrial Challenges
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description: In an increasingly data-driven world, industries face optimization problems that are too complex for traditional mathematical methods to address. Whether it is scheduling production, optimizing supply chains, or managing logistics, the complexity of these challenges requires advanced problem-solving techniques. Metaheuristic algorithms have emerged as a powerful solution, enabling industries to identify near-optimal answers to problems that are otherwise computationally intractable. These algorithms mimic natural or evolutionary processes to efficiently search for solutions, making them a cornerstone of industrial optimization. Metaheuristic algorithms are particularly effective in solving large-scale combinatorial problems that involve multiple variables and constraints, which must be balanced simultaneously. Metaheuristics, in contrast to exact algorithms, explore a vast solution space to identify high-quality answers within a reasonable time frame. Industrial settings widely apply techniques like genetic algorithms, particle swarm optimization, simulated annealing, and ant colony optimization to enhance efficiency and productivity. One of the most prominent applications of metaheuristic algorithms is production scheduling. Manufacturers must coordinate machinery, labor, and resources to minimize downtime and maximize throughput. Traditional scheduling methods struggle with dynamic environments and complex dependencies. Metaheuristic approaches, however, allow for flexible, adaptive scheduling that responds in real time to demand fluctuations and operational constraints, leading to improved efficiency and cost savings. Supply chain management also benefits significantly from metaheuristic techniques. Companies must optimize transportation routes, inventory levels, and supplier relationships while minimizing costs and meeting delivery deadlines. Metaheuristic algorithms analyze vast amounts of data to generate near-optimal logistics strategies, reducing inefficienc…
creator: Jurnal Optimasi Sistem Industri
date: 2025-11-20

General information: Happy 80th Independence Day, Indonesia
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description: Today we celebrate Indonesia’s 80 years of independence and the promise behind this year’s theme, Unity, Sovereignty, Prosperous People, Advanced Indonesia. At the Jurnal Optimasi Sistem Industri (JOSI), we translate that promise into practice. Unity is the coordination of people, data, and decisions. Sovereignty is supply chains designed for our archipelago so local industries can stand on their own. Prosperity is productivity that cuts waste while protecting the environment. Advancement is everyday choices made smarter by evidence. Optimization turns ideals into outcomes. Energy-aware scheduling lowers bills and emissions. Robust multi-port networks keep goods moving when disruptions strike. On shop floors and in service systems, clear dashboards make quality, lead time, and safety visible, so SMEs can learn faster and grow stronger. What matters to us is not buzzwords but results that managers can implement and policymakers can scale. If your research drives measurable impact in Indonesia, on energy efficiency, supply-chain resilience, or SME performance, JOSI is your home! Read the current issue at https://josi.ft.unand.ac.id/index.php/josi/issue/current and submit your manuscript at https://josi.ft.unand.ac.id/index.php/josi/about/submissions. Merdeka!
creator: Jurnal Optimasi Sistem Industri
date: 2025-08-17

Notes: Simulation-Based Optimization: Unlocking Industrial Efficiency
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description: In the fast-paced world of industrial systems, efficiency is the cornerstone of competitiveness. Companies are continually seeking ways to streamline operations, reduce waste, and enhance productivity. One of the most powerful tools enabling this transformation is simulation-based optimization, a technique that allows industries to test, refine, and implement strategies in a virtual environment before deploying them in real-world settings. This approach not only minimizes risk but also leads to data-driven, high-impact decision-making. Simulation-based optimization combines computational models with optimization algorithms to evaluate different scenarios and identify the most effective solutions. By replicating industrial processes in a simulated space, companies can analyze various variables, constraints, and uncertainties, leading to improved operational efficiency. This method has found applications across multiple sectors, from manufacturing and logistics to energy management and supply chain operations. A key advantage of simulation-based optimization is its ability to mitigate risks and reduce costs. Traditional trial-and-error methods are expensive and time-consuming, often requiring significant resources to test improvements. With simulations, industries can model complex systems, test different configurations, and optimize processes without interrupting ongoing operations. This proactive approach guarantees the refinement, efficiency, and sustainability of real-world implementations. Manufacturing industries, for instance, leverage simulation-based optimization to enhance production scheduling, reduce machine downtime, and optimize workflow layouts. Logistics companies use these techniques to improve fleet routing, warehouse efficiency, and distribution strategies. Meanwhile, energy firms deploy simulations to refine power grid management, maximize renewable energy integration, and enhance overall sustainability. Another compelling aspect of simulation-base…
creator: Jurnal Optimasi Sistem Industri
date: 2025-08-05

General information: JOSI Vol. 24 No. 1 (June 2025)
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description: We are pleased to present Volume 24, Issue 1 of the Jurnal Optimasi Sistem Industri, officially published on June 30, 2025. This issue comprises a diverse and compelling selection of articles that reflect the journal’s commitment to advancing the science and practice of industrial systems optimization, particularly through interdisciplinary and data-driven approaches. The articles featured in this issue originate from researchers across Indonesia, Thailand, Malaysia, China, and Belgium, affirming JOSI’s role as a scholarly platform with growing international reach and collaboration. The topics covered in this issue are closely aligned with JOSI’s core focus—namely, operations research, supply chain management, sustainable systems, ergonomics, decision support systems, and soft systems thinking—while also contributing meaningfully to the United Nations Sustainable Development Goals (SDGs), especially SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 3 (Good Health and Well-being). One article introduces a hybrid framework that combines Ergo-VSM, the Analytic Hierarchy Process (AHP), and a Traffic Light System to assess ergonomic performance in peanut processing lines. Conducted in Indonesia and Taiwan, this work highlights the practical integration of lean tools and human factors engineering to improve worker well-being and operational efficiency. Another study from Thailand and Belgium proposes a heuristic algorithm for full-truckload vehicle routing in intermodal logistics under time window constraints. By quantifying the impact of temporal characteristics such as concentration and specialization, the research enhances the understanding of transportation planning under uncertainty—a critical area in sustainable logistics optimization. An interdisciplinary collaboration from Indonesia and Malaysia offers a robust model for sustainable supplier selection in healthcare. By integrating fuzzy multi-criteria decisi…
creator: Jurnal Optimasi Sistem Industri
date: 2025-07-01

Notes: The Internet of Things and Connectivity: Transforming Industrial Optimization
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description: The rapid advancement of the Internet of Things (IoT) is revolutionizing industrial systems, bringing unprecedented levels of connectivity, automation, and efficiency. In an era driven by data, IoT-enabled technologies empower industries to monitor, analyze, and optimize operations in real time, significantly improving productivity and decision-making processes. As industrial ecosystems evolve, the integration of IoT into manufacturing, logistics, and infrastructure is becoming a defining factor in industrial optimization. At its core, IoT connects devices, machines, and systems through a vast network of sensors and smart components. These interconnected devices collect and transmit real-time data, allowing industrial operations to detect inefficiencies, predict equipment failures, and improve resource utilization. The ability to track performance and analyze trends in real time enables industries to make informed decisions, reducing downtime and increasing overall efficiency. One of the most impactful applications of IoT in industrial settings is predictive maintenance. Traditional maintenance strategies often lead to excessive costs and unexpected failures, whereas IoT-powered predictive maintenance leverages real-time data and machine learning algorithms to forecast potential issues before they escalate. This approach allows industries to transition from reactive maintenance to proactive strategies, minimizing disruptions and maximizing asset longevity. Beyond predictive maintenance, IoT-driven automation is transforming supply chain management. Smart logistics solutions use connected sensors and RFID technology to optimize inventory tracking, transportation efficiency, and warehouse operations. By ensuring real-time visibility into supply chain processes, IoT reduces inefficiencies, prevents stock shortages, and enhances delivery accuracy. Industries can now streamline their logistics operations while reducing costs and improving customer satisfaction. Energy ef…
creator: Jurnal Optimasi Sistem Industri
date: 2025-06-20

Notes: Sustainable Manufacturing Practices: Shaping the Future of Industrial Systems
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description: As industries seek to balance profitability with environmental responsibility, sustainable manufacturing practices have become an essential focus of industrial optimization. The growing urgency to reduce waste, conserve energy, and minimize carbon footprints is driving researchers and practitioners to develop innovative solutions that align with both economic and environmental objectives. In the coming years, sustainable manufacturing will play a pivotal role in shaping the future of industrial systems, offering a pathway to long-term resilience and competitiveness. At the heart of sustainable manufacturing lies the adoption of cleaner production methods that enhance efficiency while reducing resource consumption. Companies are increasingly incorporating circular economy principles, where materials are reused, recycled, or repurposed instead of being discarded. By closing the loop on material usage, industries can significantly reduce waste generation and lower their environmental impact. Moreover, the integration of energy-efficient technologies, such as smart grids and renewable energy sources, is transforming industrial operations into more sustainable and cost-effective processes. Advancements in sustainable materials are also revolutionizing manufacturing practices. The development of biodegradable polymers, bio-based composites, and low-impact alternatives to traditional materials is enabling industries to minimize environmental degradation. By leveraging these materials, manufacturers can reduce dependency on finite resources while meeting regulatory and consumer demands for greener products. In addition to material innovations, digitalization is playing a crucial role in sustainable manufacturing. Industry 4.0 technologies, including the Internet of Things (IoT), big data analytics, and artificial intelligence, are optimizing resource management and energy efficiency. Real-time monitoring of industrial processes allows manufacturers to detect inefficiencies,…
creator: Jurnal Optimasi Sistem Industri
date: 2025-06-06

General information: JOSI Reaches Q3 in SCImago Journal Rankings
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description: In the dynamic world of academic publishing, every step forward tells a story of collective dedication, peer collaboration, and quiet perseverance. For Jurnal Optimasi Sistem Industri (JOSI), that journey has reached an encouraging milestone: its inclusion in the Q3 quartile of Industrial and Manufacturing Engineering in the SCImago Journal & Country Rank (SJR). This recognition comes not overnight, but after years of structured growth. Since being indexed in Scopus in 2019, JOSI has consistently published high-quality research that explores the evolving challenges and innovations in industrial systems. With a clear focus on optimization, operations research, reliability, and applied statistics, the journal gradually carved out its space among regional and international scholars. Its selection for indexing by SCImago—one of the world’s most respected databases for scientific journal performance—marks an important stage in that growth. The Q3 placement in Industrial and Manufacturing Engineering stands as the journal’s highest-ranking category to date—a sign of its increasing relevance to the field it serves. With an SJR score of 0.174 and a CiteScore of 0.8, the journal continues to demonstrate steady academic progress. Behind the metrics lies a consistent rhythm. Each year, JOSI publishes two issues containing research that blends theory and practice—often centered on real-world problems faced by manufacturing industries, service operations, and logistics systems. The editorial team has remained committed to maintaining the quality and timeliness of peer review, working closely with authors to uphold academic standards. Over time, these efforts have begun to yield citations in peer-reviewed literature, marking the gradual growth of the journal’s scholarly influence. Still, perhaps more important than numerical rankings is what this recognition symbolizes. It reflects the trust of researchers who choose JOSI as a home for their work, the thoughtful assessments of re…
creator: Jurnal Optimasi Sistem Industri
date: 2025-04-09

Notes: Advanced Automation and Robotics: Redefining Industrial Efficiency
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description: Industrial automation and robotics are driving a new era of efficiency, precision, and adaptability in manufacturing and operations. As industries strive to optimize processes, reduce operational costs, and enhance productivity, advanced automation technologies and robotics are becoming indispensable. These innovations are not only transforming how industries function but also redefining the role of human workers in the production environment. The rise of smart factories is a testament to the power of automation. Through the integration of robotics, artificial intelligence, and real-time data analytics, industries can achieve levels of efficiency and accuracy that were previously unattainable. Autonomous robotic systems can now handle intricate tasks with remarkable speed and consistency, minimizing errors and reducing material waste. With machine vision and advanced sensors, robots can adapt to dynamic work environments, ensuring that industrial processes remain flexible and scalable. Collaborative robots, or cobots, represent a significant shift in industrial robotics. Unlike traditional robotic systems that operate in isolated environments, cobots are designed to work alongside human workers, enhancing safety and productivity. These intelligent machines can perform repetitive or physically demanding tasks, allowing human workers to focus on more complex decision-making processes. By bridging the gap between automation and human expertise, cobots facilitate a more efficient and harmonious work environment. Another breakthrough in industrial automation is the deployment of autonomous mobile robots (AMRs). These robots navigate factory floors, warehouses, and logistics centers using sophisticated algorithms and sensor-based mapping. By optimizing material handling and logistics, AMRs improve supply chain efficiency, minimize downtime, and enhance workflow continuity. With AI-driven decision-making capabilities, these robots can adapt to unforeseen challenges, ensuri…
creator: Jurnal Optimasi Sistem Industri
date: 2025-03-25

Notes: Artificial Intelligence and Machine Learning: Transforming Industrial Optimization
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description: The integration of artificial intelligence (AI) and machine learning (ML) into industrial systems is rapidly reshaping the way industries operate, optimize, and innovate. As industries grow more complex and data-driven, the ability to harness AI and ML technologies offers unprecedented efficiency, precision, and adaptability. In the pursuit of optimization, these technologies are no longer just experimental tools but have become essential drivers of transformation. At the heart of this revolution is AI’s ability to analyze massive datasets, recognize patterns, and make predictive decisions in real time. Manufacturing plants, supply chain operations, and quality control processes now rely on AI-powered systems to anticipate failures before they occur, reducing downtime and operational disruptions. Machine learning algorithms continuously improve through data feedback, refining their accuracy and effectiveness without human intervention. This self-learning capability enables industrial systems to evolve, adapt to changing conditions, and maintain peak performance with minimal manual oversight. One of the most significant applications of AI in industrial systems is predictive maintenance. Traditional maintenance models often lead to either unnecessary repairs or unexpected breakdowns, both of which contribute to financial losses and inefficiencies. AI-driven predictive maintenance, however, utilizes sensor data and real-time analytics to identify potential issues before they escalate. By analyzing trends and anomalies, ML algorithms forecast equipment failures, allowing companies to schedule maintenance proactively and prevent costly downtimes. Beyond predictive maintenance, AI and ML are also redefining quality control. Automated vision systems powered by deep learning algorithms can detect minute defects in products at a level of precision far beyond human capability. These systems not only improve quality assurance but also enhance speed and consistency, enabling ma…
creator: Jurnal Optimasi Sistem Industri
date: 2025-03-03

Notes: Optimizing Industrial Systems - The Expected Future Trends
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description: In the rapidly evolving landscape of industrial systems, innovation continues to shape the future of optimization. Over the next five years, groundbreaking advancements will redefine efficiency, sustainability, and intelligence in industrial operations. As researchers push the boundaries of knowledge, the Jurnal Optimasi Sistem Industri (JOSI) remains at the forefront, providing a platform for cutting-edge studies that drive meaningful impact. This blog series explores the pivotal trends poised to revolutionize industrial systems optimization and invites researchers to contribute their insights to JOSI. Optimization has always been central to industrial engineering, forming the bridge between theoretical advancements and practical applications. With the integration of emerging technologies, industries are poised to enhance productivity, minimize waste, and elevate operational resilience. The demand for data-driven decision-making is now stronger than ever, compelling industries to refine their processes to maintain a competitive edge. Researchers, with their continuous pursuit of knowledge, play a crucial role in shaping this transformation. By contributing their work to JOSI, they actively engage in critical discourse on sustainable and intelligent optimization. Among the most influential research trends driving this evolution, artificial intelligence and machine learning are revolutionizing the way industries manage quality control, predictive maintenance, and process optimization. At the same time, advanced automation and robotics are redefining precision and adaptability in industrial operations, making workflows more efficient and resilient. Sustainability is also taking center stage, with a heightened focus on environmentally friendly manufacturing practices and circular economy principles that minimize resource waste. Meanwhile, the Internet of Things (IoT) is connecting industrial systems in unprecedented ways, allowing real-time monitoring and decision-maki…
creator: Jurnal Optimasi Sistem Industri
date: 2025-02-19

General information: Volume 23, Issue 2 is Now Live!
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description: We are pleased to announce that Volume 23, Issue 2 of the Jurnal Optimasi Sistem Industri (JOSI) is now available on our website. We appreciate your patience during our recent server issues, which delayed this publication by a month. Our technical team worked diligently to resolve the problem by migrating to a new server, and we are delighted to have overcome the challenges to bring you this latest edition. This issue features a diverse collection of cutting-edge research that addresses critical challenges in industrial systems across the globe. With contributions from experts in Indonesia, Taiwan, Palestine, Brazil, Malaysia, Egypt, and Japan, this edition embodies the power of interdisciplinary and cross-national collaboration. The articles cover a wide range of topics—from machine learning applications in supply chain management and hybrid multi-criteria decision-making frameworks to the implementation of advanced techniques such as Statistical Process Control (SPC), Failure Mode and Effects Analysis (FMEA), and Mixed Integer Linear Programming (MILP). A significant theme throughout this issue is the balance between industrial efficiency and sustainability. You will find innovative studies on optimizing recycling networks for electric vehicle batteries in Southeast Asia and developing sustainable assessment models for plywood manufacturing. Additionally, traditional industries, such as Indonesian batik production, are explored with modern quality control practices that preserve cultural heritage while enhancing competitiveness. Our contributors also tackle important subjects such as demand forecasting with machine learning, sustainable logistics service quality, and the selection of open-source ERP systems for SMEs. Each study not only enriches the field of industrial engineering but also reinforces our commitment to promoting sustainable development in alignment with the United Nations Sustainable Development Goals. We extend our sincere gratitude to the authors…
creator: Jurnal Optimasi Sistem Industri
date: 2025-02-01

Notes: Jurnal Optimasi Sistem Industri: Scopus-Indexed Diamond Open Access Journal
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description: Jurnal Optimasi Sistem Industri, a Scopus-indexed diamond open-access journal, has become a trusted platform for researchers in the field of industrial systems optimization. Published by the Department of Industrial Engineering, Faculty of Engineering at Universitas Andalas, this journal is committed to providing free access to high-quality research. By adopting a diamond open-access model, the journal eliminates financial barriers for both authors and readers, ensuring that knowledge remains accessible and equitable. Since its inclusion in Scopus on the 1st of October 2023, the journal has consistently advanced its reputation in academia. With a 2023 CiteScore of 0.8 and a Source Normalized Impact per Paper (SNIP) of 0.238, Jurnal Optimasi Sistem Industri demonstrates its growing influence in the scholarly community. The 2024 CiteScore Tracker, currently at 0.9 based on 50 citations and 54 documents, highlights the journal’s upward trajectory in academic engagement. These metrics reflect the high standard of research published and its relevance to the global scientific community. The journal’s achievements extend beyond academic indexing. Analyzing data from Google Search Console reveals how Jurnal Optimasi Sistem Industri maintains a strong online presence. The journal’s articles consistently appear in search results, particularly around publication dates, reflecting their discoverability and relevance. Readers actively engage with this content, as shown by a steady flow of clicks, which mirrors the growing citations recorded in Scopus. The click-through rate (CTR) for the journal has improved over time, signaling that the titles and abstracts of its articles effectively attract readers searching for industrial systems research. Additionally, the journal’s competitive ranking in search results ensures that its content remains accessible to a global audience. Figure: The Click-Through Rate and Position since November 2024. As a diamond open-access journal, Jurnal O…
creator: Jurnal Optimasi Sistem Industri
date: 2025-01-25

Notes: The Future of Industrial Optimization with GPT: Bridging Innovation, Ethics, and Sustainability
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description: The world of industrial engineering stands on the cusp of transformative change, with technologies like Generative Pre-trained Transformers (GPT) offering unprecedented opportunities to optimize systems, enhance decision-making, and drive innovation. Over this series, we have explored how GPT contributes to key areas in industrial systems—its relevance to operational efficiency, its role in soft systems methodologies, its interdisciplinary applications, its alignment with Sustainable Development Goals (SDGs), and the ethical considerations essential for its responsible use. In this concluding post, we reflect on the broader implications of GPT for industrial optimization and highlight the importance of research that bridges innovation, ethics, and sustainability. Industrial systems are becoming increasingly complex, with interconnected supply chains, evolving workforce dynamics, and growing environmental pressures requiring sophisticated solutions. In this context, GPT demonstrates its potential to tackle challenges that previously seemed insurmountable. Its ability to process and generate natural language provides industries with a powerful tool for improving communication, enhancing decision support systems, and fostering collaboration across disciplines. By integrating GPT into production planning, supply chain optimization, human-computer interaction, and knowledge management, organizations can unlock efficiencies and innovations that redefine the industrial landscape. However, as with any transformative technology, GPT’s adoption must be approached with a sense of responsibility. While its applications can accelerate progress toward goals such as SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 12 (Responsible Consumption and Production), these outcomes are not automatic. They require deliberate effort to align technological advancements with ethical principles and sustainability objectives. Researchers, practit…
creator: Jurnal Optimasi Sistem Industri
date: 2025-01-12

Notes: How GPT Aligns with the United Nations' Sustainable Development Goals (SDGs)
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description: The United Nations' Sustainable Development Goals (SDGs) provide a global framework for addressing critical challenges such as economic growth, innovation, and sustainability. Industrial engineering plays a pivotal role in achieving these goals, particularly by optimizing systems, improving operational efficiency, and fostering innovation. Generative Pre-trained Transformers (GPT), as a cutting-edge artificial intelligence (AI) technology, are uniquely positioned to support industries in making meaningful progress toward these objectives. In this blog post, we explore how GPT applications align with specific SDGs that resonate with the focus and mission of Jurnal Optimasi Sistem Industri (JOSI). GPT’s Contribution to Sustainable Development GPT technology has immense potential to transform industrial systems by leveraging natural language processing (NLP) for smarter decision-making, enhanced collaboration, and streamlined operations. Below, we discuss how GPT directly contributes to three key SDGs that align with JOSI’s commitment to addressing global challenges: 1. SDG 8: Decent Work and Economic Growth The goal of SDG 8 is to promote sustained, inclusive economic growth, full and productive employment, and decent work for all. GPT supports this goal by: Improving Operational Efficiency: GPT-powered tools can analyze complex industrial data, identify inefficiencies, and recommend strategies to streamline operations. This leads to improved productivity and reduced workload for employees. Enhancing Decision-Making: GPT enables more accurate and data-driven decisions by processing and summarizing large datasets, allowing managers to focus on strategic goals. Creating Better Working Environments: By automating routine administrative tasks, such as report generation or data entry, GPT reduces the burden of repetitive work. This enables employees to focus on higher-value, creative tasks, improving job satisfaction, and fostering a more fulfilling work environment. Throu…
creator: Jurnal Optimasi Sistem Industri
date: 2024-12-27

Notes: Interdisciplinary Applications of GPT: Bridging the Gap Between Technology and Industrial Engineering
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description: In today’s rapidly evolving technological landscape, the ability to bridge diverse fields of study is crucial for tackling the multifaceted challenges faced by industries. Generative Pre-trained Transformers (GPT), a breakthrough in artificial intelligence, exemplify this interdisciplinary potential. By seamlessly connecting industrial engineering, computer science, and other disciplines, GPT is driving innovation in areas where collaboration and integration are essential. In this blog post, we will explore how GPT-based systems enable interdisciplinary applications, with a focus on their impact in human-computer interaction (HCI) and knowledge management. These applications align with Jurnal Optimasi Sistem Industri’s (JOSI) mission to foster interdisciplinary research and promote system optimization. The Interdisciplinary Nature of GPT GPT-based AI systems are inherently interdisciplinary. Their core strength lies in natural language processing (NLP), a capability rooted in computer science, but their applications extend far beyond this field. By interpreting and generating human language, GPT enables industries to streamline operations, enhance decision-making, and improve human-machine interactions. These systems can function as a bridge between technological tools and human users, making them particularly valuable for industrial engineering applications. Let’s dive into two key areas where GPT demonstrates its interdisciplinary capabilities: 1. Human-Computer Interaction (HCI) Human-Computer Interaction (HCI) is a critical field that focuses on designing systems that are intuitive, user-friendly, and efficient for human operators. In industrial engineering, HCI plays an essential role in ensuring that advanced technologies, such as automation and control systems, are accessible and effective for users at all levels of expertise. GPT enhances HCI by: - Facilitating Natural Language Interfaces: GPT enables machines to understand and respond to user commands in na…
creator: Jurnal Optimasi Sistem Industri
date: 2024-12-17

Notes: How GPT Enhances Soft Systems Methodologies in Industrial Engineering
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description: Industrial systems are rarely straightforward. They often involve complex, ill-structured problems influenced by human factors, organizational culture, and decision-making dynamics. These types of challenges, often addressed through soft systems methodologies, require innovative approaches to bridge gaps between technology, people, and processes. Generative Pre-trained Transformers (GPT), with their advanced natural language understanding capabilities, have emerged as a promising tool for optimizing soft systems in industrial engineering. In this post, we explore how GPT can support soft systems methodologies by enhancing decision-making and facilitating effective communication among stakeholders. Understanding Soft Systems Methodologies Soft systems methodologies focus on addressing problems that lack clear definitions or solutions. Unlike hard systems, which are heavily quantitative and structured, soft systems emphasize human-centric issues, such as decision-making processes, organizational behavior, and the dynamics between stakeholders. In industrial engineering, these methodologies are critical for tackling challenges like aligning organizational goals with operational systems, improving collaboration in decision-making, and navigating the complex relationships between various stakeholders in a system. GPT technology offers significant potential to enhance these processes, enabling smarter and more adaptive approaches to problem-solving. Applications of GPT in Soft Systems Methodologies 1. Decision Support Systems (DSS) One of the core tools in soft systems optimization is Decision Support Systems (DSS). These systems help managers and decision-makers explore potential strategies, evaluate outcomes, and make informed choices. GPT can enhance DSS in several key ways: Summarizing Large Datasets: GPT can process and condense extensive data into concise, actionable insights, allowing decision-makers to focus on what matters most. Scenario Simulation: By generating…
creator: Jurnal Optimasi Sistem Industri
date: 2024-12-11

Notes: New article series: Relevance of GPT in Industrial Engineering
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description: In recent years, artificial intelligence (AI) has emerged as a transformative force across various industries, including industrial engineering. Generative Pre-trained Transformers (GPT) is one of the most important advances in artificial intelligence. It is a powerful natural language processing (NLP) model that can analyze, generate, and understand human language with amazing accuracy. In this blog post, we will delve into the relevance of GPT in industrial engineering and its potential to drive innovation in system optimization, aligning with the mission of Jurnal Optimasi Sistem Industri (JOSI). What is GPT, and Why Does it Matter? GPT models are advanced AI systems designed to process and generate natural language efficiently. GPT models are different from traditional rule-based systems because they learn from very large datasets to find patterns, understand complicated text, and make outputs that make sense. These capabilities make GPT particularly valuable in addressing the multifaceted challenges of industrial systems, where decision-making often involves interpreting large volumes of data and optimizing processes. Key Applications of GPT in Industrial Engineering GPT technology offers numerous applications in industrial engineering, many of which directly align with JOSI’s focus on operational improvement and system optimization. Below are some notable examples: 1. Production Planning and Scheduling Efficient production planning and scheduling are critical for maintaining operational excellence in manufacturing and industrial processes. GPT-based tools can assist decision-makers by: Analyzing historical production data to identify patterns and bottlenecks. Predicting trends and potential disruptions in workflows. Generating optimized resource allocation strategies that reduce delays and enhance productivity. By providing actionable insights, GPT can help organizations achieve more streamlined production cycles and better allocate resources. 2. Supply Chain …
creator: Jurnal Optimasi Sistem Industri
date: 2024-12-02

General information: Exciting Updates: New Server Launch and Important Information for Users
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creator: Jurnal Optimasi Sistem Industri
date: 2024-11-19

Notes: Sustainability in Industrial Systems: The Role of Soft Systems
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description: Introduction In recent years, sustainability has become a central concern for industries worldwide. The drive toward eco-friendly practices, reducing environmental impact, and adopting long-term environmental responsibility has led to the rethinking of industrial systems. While much attention is given to the technical innovations that reduce waste and improve efficiency, the role of soft systems—such as leadership, team collaboration, and decision-making—is equally important in promoting sustainability. Soft systems provide the human-driven elements that guide an organization’s sustainability efforts, ensuring that eco-friendly practices are not only implemented but sustained over time. This post explores how optimizing soft systems can play a key role in fostering sustainable industrial operations. Decision-Making for Sustainable Operations Sustainability requires conscious decision-making at all levels of an organization. Decisions that affect energy consumption, resource management, waste reduction, and overall environmental impact must be made with a sustainability mindset. Soft systems optimization ensures that sustainability is integrated into the decision-making process, allowing teams to make choices that align with both operational goals and environmental responsibility. In an industrial setting, decisions are often data-driven and influenced by technical systems. However, human factors such as judgment, experience, and values play an equally important role, particularly when it comes to sustainability. Leaders and managers must assess not only the financial or operational outcomes of their decisions but also the long-term environmental impact. This requires a culture of sustainability, where every decision—whether it involves sourcing materials, adjusting production schedules, or managing waste—takes into account its effect on the planet. By optimizing soft systems, organizations can foster a decision-making process that prioritizes sustainability. For exa…
creator: Jurnal Optimasi Sistem Industri
date: 2024-11-12

Notes: The Role of Technology in Supporting Soft Systems Optimization
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description: Technology’s Impact on Decision-Making One of the most significant ways technology enhances soft systems is by improving the quality and speed of decision-making. In industrial settings, decisions need to be made quickly, often in response to complex and rapidly changing conditions. This is where technology, particularly AI and data analytics, comes into play. AI-driven decision support systems have revolutionized the way managers and teams approach problem-solving in industrial environments. By analyzing vast amounts of data in real-time, these systems provide actionable insights that would be impossible for humans to gather at the same speed (Lepri et al., 2021). AI algorithms can predict equipment failures, optimize production schedules, or even suggest operational changes based on patterns in data (Giugliano et al., 2023). This allows decision-makers to rely not only on their intuition but also on precise, data-backed insights, leading to more informed and confident decisions (Shneiderman, 2022). Moreover, automation tools allow for real-time monitoring of operations, identifying bottlenecks or inefficiencies, and providing instant feedback to decision-makers (Xie, 2023). This reduces the cognitive load on leaders and managers, who can focus on higher-level strategic decisions while trusting that the technology is managing operational details effectively (Fantini et al., 2020). In this way, technology supports both tactical and strategic decision-making, allowing for smoother operations and improved outcomes (Villani et al., 2018). The integration of human-centered design principles into these technologies ensures that they complement rather than replace human judgment, thereby fostering a more effective decision-making environment (Sigfrids et al., 2023). Enhancing Communication with Collaboration Tools Communication lies at the heart of any successful industrial operation, and the rise of collaboration tools has significantly improved the way teams communicate…
creator: Jurnal Optimasi Sistem Industri
date: 2024-11-05

Notes: Building a Culture of Continuous Improvement Through Soft Systems Optimization
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description: A culture of continuous improvement is vital for the long-term success of any industrial system. While hard systems can be improved through technology upgrades and process optimizations, it is the soft systems—human behaviors, feedback mechanisms, and organizational mindset—that drive ongoing progress. When soft systems are optimized, employees feel empowered to contribute ideas, suggest improvements, and identify potential issues before they escalate. This proactive environment helps organizations refine both their hard and soft systems regularly, resulting in increased efficiency, innovation, and adaptability. Continuous improvement thrives on open communication and feedback loops. By encouraging workers at all levels to share their insights and suggest improvements, organizations create a culture where positive changes can occur more frequently. This leads to faster problem-solving, better alignment between departments, and an overall more agile organization. When teams work in a system that values their input, they are more likely to engage deeply with both the technical and human aspects of the business, driving innovation and refinement in all areas. The Role of Leadership in Soft Systems Optimization Leadership is a driving force behind the successful optimization of soft systems. Effective leaders understand that industrial success doesn’t solely depend on technology and processes; it also relies on creating a supportive and adaptable organizational culture. By fostering open communication, encouraging collaboration, and focusing on employee development, leaders can cultivate a system where continuous improvement becomes second nature. Strong leadership also ensures that teams are equipped to deal with complex challenges. Leaders who emphasize training, build transparent decision-making structures, and promote a positive working environment enable their organizations to respond more effectively to change. Leadership development programs that focus on interpe…
creator: Jurnal Optimasi Sistem Industri
date: 2024-11-05

Notes: Understanding Industrial Systems: A Focus on Soft Systems
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description: Introduction In the world of industrial optimization, systems are at the heart of everything—both technical and human. While we often think of machines, production lines, and data-driven processes, soft systems—the human and organizational elements—are just as critical. These systems, rooted in decision-making, communication, and collaboration, play a key role in ensuring industrial processes run smoothly. This post will explore what soft systems are and why they matter in optimizing industrial systems. The Role of Industrial Systems An industrial system consists of interdependent components that work together to achieve specific goals, such as manufacturing products or delivering services. These systems can be divided into hard systems, like machines and technology, and soft systems, which involve human behavior and organizational dynamics. While hard systems are easier to quantify and optimize, soft systems require a more nuanced approach. What Are Soft Systems? Soft systems refer to the human-centered aspects of an industrial environment. These include the interactions between people, their decision-making processes, and the way organizations manage change. Unlike hard systems, which follow predictable patterns, soft systems are complex and involve subjective elements such as leadership, communication, and team dynamics. One way to understand and manage these human factors is through Soft Systems Methodology (SSM), a framework developed by Peter Checkland. SSM provides a structured approach to solving complex problems by considering multiple perspectives, recognizing that human behavior and organizational culture cannot always be quantified. Why Soft Systems Matter Soft systems are crucial because they directly influence decision-making, teamwork, and the ability of organizations to adapt to change. In any industrial environment, humans are responsible for making key decisions and solving problems. Even the most advanced machines and technologies depend on how we…
creator: Jurnal Optimasi Sistem Industri
date: 2024-11-05

Notes: The Journey Toward Optimal Solutions – How Gradients and Convexity Shape Optimization
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description: Introduction In our previous post, we explored the fundamental aspects of optimization, focusing on the objective function, constraints, and the distinction between local and global optima. Now, we will build on that foundation by introducing two powerful concepts: gradients and convexity. These ideas play a central role in many optimization problems, determining how efficiently and effectively we can find the optimal solution. Understanding these tools will help you approach optimization challenges with greater precision and confidence. Gradients: The Direction to Improvement When working with continuous optimization problems, knowing which direction to move becomes crucial. This is where the concept of a gradient comes into play. The gradient of an objective function tells us the direction of the steepest ascent or descent, depending on whether we’re trying to maximize or minimize the function. Imagine you’re climbing a hill, and you want to find the quickest path to the top. The gradient points you in the direction that leads uphill most steeply. In optimization, particularly when minimizing a function, you move in the opposite direction of the gradient to find the lowest point. This process, called gradient descent, iteratively moves the solution closer to the optimum with each step. It’s a core technique in machine learning and many other areas that involve optimization. Gradients provide an intuitive and mathematically rigorous way to guide the search for optimal solutions. In practice, algorithms use the gradient to adjust variables in a way that improves the objective function step by step. This method allows for continuous improvement and often converges to the best possible solution in a relatively short time. Convexity: Ensuring Simplicity in Optimization While gradients help us navigate the solution space, the structure of the problem itself also influences how difficult it is to find the optimal solution. Convexity is a property of certain optimization …
creator: Jurnal Optimasi Sistem Industri
date: 2024-11-05