Journal of Renewable Engineering (JORE) is a peer-reviewed open access international journal established for the dissemination of cutting-edge knowledge in the field of Renewable Engineering. All submitted manuscripts will be reviewed by the editors and then evaluated by a minimum of two International Reviewers through a double-blind review process. This is to ensure the quality of manuscripts published in the journal. The journal, which has been published since 2024, is published four times each year in February, April, June, August. Journal title : Journal of Renewable Engineering Initials : JORE Frequency : 4 (four) times a year (February, April, June, August) DOI : 10.62872 ISSN Online : 3046-7624 Editor in Chief :Dr. Yulia Panca Asmara Managing Editor : Dr. Kamran Yeganegi, PH.d Assistant Editor : Dr. Muhammad Roil Bilad Publisher : PT. Anagata Sembagi Education Accreditation : On Process
Analysis of Factors Affecting Labor Productivity in Small and Medium-Sized Industries
Labor productivity remains one of the most decisive determinants of competitiveness and survival for small and medium-sized industries (SMIs), yet the factors that shape it are dispersed across a fragmented body of literature spanning manufacturing, construction, and service contexts. This article synthesizes findings from twenty-five peer-reviewed studies published between 2021 and 2026 to identify, categorize, and interpret the principal drivers of labor productivity in SMIs. Using a narrative literature review method, factors are grouped into four thematic clusters: human capital and workforce competence, capital and technology adoption, work environment and managerial practice, and institutional or policy context. The synthesis shows that human capital consistently exerts the strongest and most stable positive influence, followed by technology adoption, whose effect is conditional on firm size and absorptive capacity. Work environment and compensation factors matter most in labor-intensive small industries, while institutional support determines whether productivity gains are sustained over time. The novelty of this article lies in integrating evidence across sectors and regions into a single comparative framework rather than treating each determinant in isolation. The findings offer practical guidance for SMI owners and policymakers seeking to prioritize interventions, and they identify gaps for future empirical research, particularly on the interaction effects between human capital and digital technology in resource-constrained small industries.
Copyright (c) 2026 Kimberly Febrina Kodrat (Author) https://creativecommons.org/licenses/by-sa/4.0
The Hybrid Specialization Model: Navigating Bureaucratic Rigidity through GovTech Co-creation in Indonesia
This study investigates how GovTech firms navigate bureaucratic rigidity to accelerate digital maturity in Indonesian local government. It examines the evolution of client needs, the operationalization of collaborative governance, and the structural design of a "Hybrid Specialization Model" within the Electronic-Based Government System (SPBE) framework. Utilizing a qualitative single-case study of the partnership between PT 4nesia Digital Solution and Cirebon City, data were triangulated through semi-structured interviews, field observations, and longitudinal SPBE evaluation reports. Results indicate a shift from technical procurement toward institutional legitimacy, driven by compliance with national SPBE indicators. Success depends on facilitative leadership to bridge sectoral silos. The proposed Hybrid Specialization Model boosted the SPBE Index from 3.17 to 4.13, though a sustainability gap persists requiring the codification of digital workflows into local policy. This research provides empirical evidence for value co-creation and offers a strategic blueprint for shifting from transactional relations to institutionalized partnerships.
Copyright (c) 2026 Ajeng Amalia Andi, Dodie Tricahyono, Agus Salim Andi (Author) https://creativecommons.org/licenses/by-sa/4.0
Systematic Literature Review: The Implementation of Smart Manufacturing to Enhance Production Process Efficiency
The emergence of smart manufacturing in the Industry 4.0 era has transformed traditional production systems into interconnected, data-driven environments aimed at enhancing efficiency and flexibility. However, conventional manufacturing systems continue to face challenges such as planning errors, bottlenecks, machine downtime, and limited technological integration. This study aims to systematically analyze the implementation of smart manufacturing technologies in improving production process efficiency. The research employs a systematic literature review (SLR) with a qualitative approach, utilizing secondary data from peer-reviewed journals and academic publications. Data collection follows structured stages of identification, screening, eligibility, and inclusion, while data analysis is conducted through thematic and content analysis to identify patterns, technologies, and efficiency outcomes. The findings reveal that key technologies such as Cyber-Physical Systems (CPS), Internet of Things (IoT), Artificial Intelligence (AI), big data analytics, and digital twins significantly contribute to improving production efficiency through real-time monitoring, predictive maintenance, and optimized decision-making. These technologies effectively reduce downtime, minimize waste, and enhance overall system performance. In conclusion, smart manufacturing represents a transformative approach that addresses inefficiencies in conventional systems and supports sustainable industrial development through integrated and intelligent production processes.
Copyright (c) 2026 Taryana Taryana (Author) https://creativecommons.org/licenses/by-sa/4.0
Smart Manufacturing: Integration of Industry 4.0 Technologies to Enhance Engineering System Productivity
The transformation of manufacturing systems in the era of Industry 4.0 has led to the emergence of smart manufacturing, which integrates advanced technologies such as Internet of Things (IoT), cyber-physical systems (CPS), artificial intelligence (AI), and digital twins to enhance engineering system productivity. This study aims to analyze how the strategic integration of these technologies improves productivity by addressing system complexity, integration challenges, and human factors. The research employs a qualitative approach using a systematic literature review (SLR) method, with data collected from reputable international journals published between 2020 and 2025. The analysis is conducted through thematic and comparative synthesis to identify key patterns and relationships. The findings indicate that the integration of Industry 4.0 technologies significantly improves operational performance, including increased efficiency, reduced downtime, enhanced product quality, and improved system responsiveness. However, challenges such as integration complexity, legacy systems, and workforce skill gaps remain critical barriers. The study concludes that a holistic and strategic integration approach, supported by strong data governance and workforce development, is essential to achieve sustainable productivity improvements in engineering systems.
Copyright (c) 2026 Gusman Simon, Bramono Wangsa Wedono (Author) https://creativecommons.org/licenses/by-sa/4.0
Machine Learning-Based Automation in Production Processes: Enhancing Efficiency and System Accuracy in Industry
The integration of Machine Learning (ML) in production automation has become a key driver in transforming industrial systems into smart and adaptive manufacturing environments. This study aims to analyze the role of ML in improving efficiency and accuracy within production processes. The research employs a qualitative approach with a descriptive-analytical design, using library research and document analysis of reputable scientific sources. Data were analyzed through an interactive model consisting of data reduction, data display, and conclusion drawing. The findings reveal that ML significantly enhances operational efficiency through predictive maintenance, optimized scheduling, and real-time decision-making, while also improving accuracy in quality control through advanced algorithms such as deep learning, Support Vector Machines, and Artificial Neural Networks. Furthermore, ML enables process optimization by analyzing complex production variables and identifying optimal parameters. However, challenges such as data quality, system integration, and model interpretability remain critical barriers. The study concludes that a holistic integration of ML, supported by advanced technologies such as IIoT and Digital Twin, is essential for achieving higher efficiency, improved accuracy, and sustainable competitiveness in modern industrial systems.
Copyright (c) 2026 Amali Amali, Amalia Tasya (Author) https://creativecommons.org/licenses/by-sa/4.0
Human-Centered Engineering: Integrating Human Factors in Modern Engineering System Design
This study explores the integration of human factors into modern engineering systems through a human-centered engineering approach that emphasizes safety, usability, and long-term socio-technical sustainability. The increasing complexity of engineering systems, driven by digitalization and automation, necessitates a shift from technology-centered design toward approaches that prioritize human interaction and well-being. The study employs a mixed-method approach, combining a systematic literature review, expert interviews, and case study analysis across industrial, healthcare, and digital system contexts. Data were analyzed using thematic analysis, content analysis, and comparative evaluation to identify key dimensions of human-centered engineering, including physical, cognitive, and organizational ergonomics, as well as Human-Centered Design (HCD) and Human Systems Integration (HSI). The results indicate that integrating human-centered components significantly enhances system performance, particularly in terms of safety, usability, efficiency, and adaptability. The discussion reveals that the synergy between human factors and digital technologies, such as human modeling and simulation, plays a critical role in optimizing system design. However, challenges remain in terms of late integration, interdisciplinary collaboration, and limited representation of human factors in digital engineering frameworks. In conclusion, the development of modern engineering systems requires a comprehensive human-centered strategy that aligns technological innovation with human needs to achieve resilient, efficient, and sustainable systems.
Copyright (c) 2026 Bramono Wangsa Wedono (Author) https://creativecommons.org/licenses/by-sa/4.0
Integrating Large Language Models into Decision Support Systems for Objective Student Competition Participant Selection
The selection process for competition participants in the Informatics Engineering Department at Gorontalo State University is still carried out manually, potentially leading to subjectivity and suboptimal identification of deserving students. This study developed an artificial intelligence-based selection system using a Large Language Model (LLM) integrated with the Retrieval-Augmented Generation (RAG) approach. The developed system, named Scout, recommends competitions that match student profiles based on academic data, interests, experience, and achievements. The system evaluation used the Precision@K and Hit@K metrics to measure recommendation accuracy, and RAGAS to assess the quality of retrieval and chatbot responses. Test results showed that the Scout system obtained a Precision@3 score of 0.87 and a Faithfulness score of 0.91, indicating high recommendation relevance and factual consistency. Thus, the implementation of LLM and RAG has proven effective in increasing the objectivity and efficiency of the selection process and has the potential to become the basis for the development of an AI-based academic decision support system in higher education
Copyright (c) 2026 Eka V. Dangkua, Fazrul Anugrah Sahi, Nikmasari Pakaya, Indhitya R. Padiku, Muchlis Polin, Rahmat Taufik R. L Bau (Author) https://creativecommons.org/licenses/by-sa/4.0
Integration of Industry 5.0 Principles in Sustainable Manufacturing Systems: A Literature Review on the Role of Human–Machine Collaboration and Its Impact on Productivity
The transition from Industry 4.0 to Industry 5.0 represents a paradigm shift from technology-driven efficiency toward human-centric, sustainable, and resilient manufacturing systems. Human–machine collaboration is increasingly recognized as a core mechanism for achieving productivity while simultaneously addressing social and environmental objectives. This study aims to systematically review the integration of Industry 5.0 principles in sustainable manufacturing, with particular emphasis on the role of human–machine collaboration and its impact on productivity. A Systematic Literature Review (SLR) was conducted using peer-reviewed journal articles published between 2021 and 2025 from major academic databases. Thematic analysis was applied to synthesize key concepts related to human-centric smart manufacturing, human–robot collaboration, cyber-physical systems, digital twins, and sustainability performance indicators. The findings indicate that collaborative human–machine architectures enhance operational efficiency, quality consistency, adaptability, and resilience, while also supporting worker well-being, skill development, and environmental performance. However, gaps remain regarding long-term empirical validation, standardized sustainability measurement frameworks, and implementation in diverse industrial contexts. In conclusion, Industry 5.0 provides an integrative socio-technical framework in which human–machine collaboration functions as a strategic bridge between productivity enhancement and sustainable manufacturing performance.
Copyright (c) 2026 Rahmat Purnomo, Bramono Wangsa Wedono (Author) https://creativecommons.org/licenses/by-sa/4.0
Development of High-Performance Engineered Textiles for Medical Applications: A Quality Function Deployment (QFD) Study
The rapid growth of biomedical applications and the increasing demand for advanced healthcare solutions have intensified the need for high-performance engineered textiles in medical contexts. These textiles must simultaneously fulfill stringent clinical, mechanical, biological, and regulatory requirements. This study aims to develop and analyze a Quality Function Deployment (QFD) framework to systematically translate clinical and user requirements into prioritized engineering specifications for medical textile development. A quantitative–descriptive approach was employed using stakeholder surveys, expert interviews, and literature analysis to identify the Voice of Customer (VoC). The House of Quality matrix was constructed to evaluate relationships between customer needs and technical characteristics. The results indicate that biocompatibility, mechanical durability, and antimicrobial performance are the highest-priority customer requirements. Correspondingly, fiber material composition, fabric structure, and surface functionalization emerged as the most critical technical characteristics. The discussion demonstrates that QFD effectively reduces overdesign, enhances cross-disciplinary alignment, and improves resource allocation in product development. In conclusion, QFD provides a structured and strategic framework for optimizing the development of high-performance medical textiles, ensuring alignment between clinical expectations and engineering feasibility while supporting innovation sustainability.
Copyright (c) 2026 Miko Mei Irwanto, Akhmad Fauzi Pane, Atiek Ike Wijayanti (Author) https://creativecommons.org/licenses/by-sa/4.0
Improving Textile Production Efficiency Through the Implementation of Lean Manufacturing in the Weaving Department
This study examines how a customized Lean Manufacturing approach can improve production efficiency in the weaving department of a textile company. Weaving operations frequently experience inefficiencies due to machine downtime, waiting time, excessive operator movement, and product defects, which create a gap between targeted and actual output. A quantitative case study design was applied using direct observation, time study, Value Stream Mapping, production records, and maintenance logs. Lean tools including 5S, Total Productive Maintenance, layout improvement, line balancing, poka yoke, and Kaizen were implemented in a pilot weaving area. The results indicate a significant reduction in machine downtime by 53 percent, waiting time by 59 percent, operator movement by 39 percent, and defect rate by 50 percent. Value Stream Mapping analysis further shows that non value added time decreased substantially while value added time remained stable, leading to a 24 percent reduction in total lead time and a 22 percent increase in daily production output. These findings confirm that Lean Manufacturing, when customized to the characteristics of weaving processes, effectively eliminates waste and enhances workflow. The study concludes that integrating Lean with maintenance and process standardization provides a practical strategy to bridge the gap between production targets and actual performance in textile weaving units.
Copyright (c) 2026 Miko Mei Irwanto (Author) https://creativecommons.org/licenses/by-sa/4.0
Performance and Emission Assessment of Tree-Based Biofuel Additives in Compression Ignition Engines: A Review
This study reviews the performance and emissions of compression ignition (CI) engines using Calophyllum inophyllum (CIME/tamanu)-based biofuel additives through a narrative review of the latest international literature. Inclusion criteria encompassed CI engine test studies reporting efficiency metrics (BTE, BSFC) and key emissions (CO, HC, NOx, smoke/PM) for CIME blends (B10–B100) both without and with additive/mitigation strategies. In general, compared to diesel, CIME reduced CO, HC, and smoke/PM, with a trade-off increase in NOx. The addition of oxygenated additives (e.g., n-pentanol, dimethyl carbonate) and ignition improvers (e.g., DTBP) tends to improve combustion quality, reduce BSFC, and suppress CO/HC; while the application of approximately 10% EGR effectively reduces NOx with a moderate penalty on HC/CO/smoke. Nano-additives (graphene/MWCNT) show potential for increasing BTE and reducing smoke, but present issues of dispersion stability and safety/environment. The most balanced performance generally occurs at low–medium blends (≈B10–B20) combined with oxygenated additives and EGR-based NOx control, accompanied by proper injection calibration. From a sustainability perspective, C. inophyllum—as a non-food source with high FFA pretreatment requirements—has the potential to support transportation decarbonization, although industrial-scale success depends on supply chains, policies, and LCA/TEA results. Further studies are recommended on real-world test cycles, long-term durability, aftertreatment compatibility, and comprehensive environmental assessment.
Copyright (c) 2026 Ilmi Ilmi , Tulus Burhanuddin Sitorus, Parulian Siagian, Roland Sihombing (Author) https://creativecommons.org/licenses/by-sa/4.0
Utilization of AR & VR for the Development of Safety Training and Risk Mitigation
This study examines how Augmented Reality (AR) and Virtual Reality (VR) can be utilized to develop safer and more effective safety training while supporting performance assessment and behavioral change for risk mitigation in high-risk work environments. The background of the study arises from persistent workplace accidents in sectors such as construction, mining, healthcare, emergency response, and industrial processing, where conventional training methods often fail to provide realistic experiential preparation. This research employs a qualitative library research design by analyzing recent accredited journal studies on AR/VR applications in safety training. Data were collected through systematic documentation and analyzed using thematic content analysis focusing on immersive simulation, experiential learning, performance measurement, and behavioral outcomes. The findings show that AR/VR create zero-risk training environments that significantly improve hazard recognition, procedural skills, emergency readiness, and safety awareness compared to traditional approaches. In addition, AR/VR systems enable data-driven performance assessment by tracking user errors, response times, and compliance with safety protocols, fostering continuous improvement. The study concludes that AR and VR function as integrated systems for simulation, evaluation, and behavioral reinforcement, positioning them as strategic technologies for proactive risk mitigation in modern occupational safety management.
Copyright (c) 2026 Dwi Puspita Anggraeni (Author) https://creativecommons.org/licenses/by-sa/4.0
SWOT Analysis of the Application of Battery-Free Sensor Systems for Smart Infrastructure: A Literature Review on Micro Energy Technology
The development of smart infrastructure requires sensor systems that can operate autonomously without relying on conventional batteries. This study analyzes the strengths, weaknesses, opportunities, and challenges (SWOT) of implementing battery-free sensor systems based on energy harvesting technology for smart infrastructure through a systematic literature study. The research methodology uses a literature review approach by analyzing 85 indexed international journal articles from the IEEE Xplore, ScienceDirect, SpringerLink, and MDPI databases for the period 2019-2024. The results of the SWOT analysis show that battery-free sensor systems have the main advantages of continuous operation, reduced maintenance costs by up to 60%, and are environmentally friendly. The main disadvantages include the limited energy that can be harvested (0.1-100 µW), dependence on environmental conditions, and the complexity of energy management. The greatest opportunities lie in the growth of the smart city market, which will reach $2.5 trillion by 2025, and the development of low-power communication technologies. Key challenges include fluctuations in environmental energy sources, electromagnetic interference, and data security regulations. This study provides strategic guidance for the development and implementation of battery-free sensor systems in smart infrastructure with energy harvesting efficiency that can be increased up to 85% through design optimization and adaptive energy management algorithms
Copyright (c) 2025 Dwiyanto Dwiyanto (Author) https://creativecommons.org/licenses/by-sa/4.0
Exploration of Stakeholder Perceptions on the Application of Biomining for Mining Waste Management
Mining waste management is a major challenge, resulting in water pollution, ecosystem degradation, and heavy metal accumulation. Biomining, the use of microorganisms to extract and stabilize metals, is seen as an innovative solution that is more environmentally friendly than conventional methods. This study aims to explore the perceptions of stakeholders regulators, mining companies, local communities, and academics on the application of biomining in mining waste management. The study employed a descriptive qualitative approach with a case study design. Data were obtained through in-depth interviews, focus group discussions, field observations, and document reviews. Analysis was conducted manually through transcription, coding, theme grouping, and source triangulation to ensure data validity. The results show that academics and regulators have positive perceptions of biomining because it supports the principles of a circular economy and sustainable development. Local communities welcome biomining with cautious optimism, influenced by negative experiences with conventional methods, but still demand transparency and safety assurance. Conversely, mining companies are more skeptical, considering technical risks, initial investment costs, and the uncertainty of long-term profitability. The study's conclusions emphasize that the success of biomining depends on convincing technical evidence, regulatory certainty, and social legitimacy through community engagement. Triple helix synergy between government, industry, and academia is needed to accelerate the adoption of biomining technology in Indonesia.
Copyright (c) 2025 Rafiuddin (Author) https://creativecommons.org/licenses/by-sa/4.0
The Application of Artificial Intelligence in Industrial Supply Chain Optimization and Its Implications for Business Performance
The digital transformation occurring in the global industrial landscape has driven the need for more adaptive, efficient, and resilient supply chain systems. Amid increasing market complexity, demand fluctuations, and delivery time pressures, the integration of Artificial Intelligence (AI) technology has become a crucial strategy in addressing these challenges. This study aims to evaluate the strategic role of AI in industrial supply chain optimization and its impact on business performance. Using a qualitative approach using a systematic literature review method, various scientific publications from 2019 to 2024 were analyzed. The study results indicate that AI contributes significantly to demand planning, inventory management, distribution optimization, and data-driven decision-making. Positive impacts include increased operational efficiency, predictive accuracy, delivery reliability, and business productivity. However, implementation challenges remain, such as infrastructure limitations, a lack of expertise, organizational resistance, and regulatory and ethical issues. Therefore, successful AI adoption requires a comprehensive approach, encompassing technological readiness, human resource development, and sustainable data governance. This study recommends the need for a collaborative and inclusive digital transformation roadmap to realize an intelligent and competitive industrial supply chain in the digital economy era.
Copyright (c) 2025 Arie Wahyu Prananta, Amelia Hayati (Author) https://creativecommons.org/licenses/by-sa/4.0
Industrial Revolution 4.0 In Mechanical Engineering: A Literature Review On The Application Of Iot And Automation In Production Systems
The Industrial Revolution 4.0 has revolutionized the mechanical engineering production paradigm through the integration of digital technologies such as the Internet of Things (IoT), cyber-physical systems (CPS), and intelligent automation. This study aims to evaluate the strategic role of IoT and automation in realizing an adaptive, efficient, and sustainable mechanical engineering production system. Using a qualitative approach with a literature review method, this study analyzes the latest findings from relevant scientific sources over the past five years. The results of the review indicate that the implementation of IoT contributes to increased efficiency through predictive maintenance, reduced downtime, and real-time data-driven decision-making. On the other hand, the evolution of automation includes precision robotics, cloud-based CNC, and intelligent PLCs that enhance production flexibility and quality. However, several challenges have been identified, such as limited digital human resources, inadequate infrastructure, and system interoperability issues. Therefore, adaptive strategies such as continuous technical training, cross-sector collaboration, and strengthening industrial digitalization policies are needed. This study concludes that the integration of IoT and automation is a key foundation for the transformation of mechanical engineering towards inclusive and sustainable smart manufacturing, and emphasizes the importance of synergy between technology, people, and policies in supporting a systemic and contextual industrial revolution.
Copyright (c) 2025 Arie Wahyu Prananta, Dwiyanto Dwiyanto (Author) https://creativecommons.org/licenses/by-sa/4.0
Literature Review: Integration of Hybrid Renewable Energy Systems in Remote Areas
The availability of equitable and sustainable energy in remote areas is a major challenge for national development, primarily due to limited infrastructure and electricity access from conventional grids. Hybrid energy systems that combine renewable energy sources such as solar, wind, and microhydro with energy storage or diesel backup have emerged as an adaptive solution to address energy needs in off-grid areas. This study uses a qualitative approach based on literature to explore relevant hybrid energy system integration practices, challenges, and models across various geographic and social contexts. The study identifies that the success of hybrid system implementation is determined not only by its technological configuration but also by local social, economic, and institutional factors. Technological advances such as the Internet of Things (IoT) and smart energy management systems have contributed to improving system efficiency and reliability. However, obstacles remain in the form of limited funding, low public energy literacy, and weak supporting policies at the regional level. Through a thematic synthesis of the literature from the past five years, this study formulates a local energy ecosystem-based integration model that encompasses modular technology, multilevel policies, and community empowerment. These results are expected to serve as a strategic reference in promoting a just and sustainable energy transition in underdeveloped regions.
Copyright (c) 2025 Sulaiman A, Minarti Minarti, Rahmad Surya Hadi Saputra (Author) https://creativecommons.org/licenses/by-sa/4.0
Literature Review of the Development of Sensor Technology for Monitoring Civil Engineering Infrastructure
This study aims to examine the development of sensor technology in civil engineering infrastructure monitoring systems through a literature study approach with a qualitative descriptive method. The need for accurate, real-time, and sustainable monitoring systems is increasingly urgent as the complexity and age of public infrastructure increases. This study highlights the evolution of sensors such as strain gauges, accelerometers, and Wireless Sensor Network (WSN)-based systems that are now integrated with the Internet of Things (IoT) and edge computing. This technology enables early detection of structural damage and efficient data processing, thereby increasing the effectiveness of structural maintenance and safety. However, implementation in the field still faces challenges such as initial costs, extreme environmental conditions, and limitations of existing structures. Through content analysis of various scientific publications over the past decade, it was found that the success of the Structural Health Monitoring (SHM) system is not only determined by the quality of the sensor, but also by the data integration strategy and analytical-based decision making. This study provides academic contributions in mapping trends and challenges of sensor technology and offers practical insights for the development of adaptive and sustainable monitoring systems, especially in developing countries like Indonesia.
Copyright (c) 2025 Eric Eric (Author) https://creativecommons.org/licenses/by-sa/4.0
Optimization of Solar and Wind Hybrid Energy System with IoT Integration for Remote Areas in Indonesia
Limited access to electricity in remote areas of Indonesia reflects complex structural issues, including geographic constraints, policy inequalities, and the low effectiveness of centralized approaches. Thousands of villages in the 3T (Disadvantaged, Frontier, and Outermost) regions still do not enjoy reliable electricity, hampering socio-economic development and reinforcing the cycle of poverty. Although Indonesia has great potential for renewable energy—such as solar and wind—its use is still minimal due to infrastructure constraints, investment, and non-contextual development approaches. In this context, a hybrid solar-wind energy system integrated with Internet of Things (IoT) technology offers an efficient and sustainable decentralized solution. IoT enables real-time monitoring, predictive maintenance, and data-driven energy management, which are critical in remote areas with limited technicians and physical access. This study uses a qualitative approach through a literature review to examine the challenges, potential, and policy relevance in developing IoT-based renewable energy systems. The results of the analysis show that transforming energy systems in marginalized areas requires not only technological innovation, but also a paradigm shift towards inclusive energy justice. Therefore, strengthening local capacity and integrating context-based policies are key to realizing a fair, reliable and sustainable energy system in Indonesia.
Copyright (c) 2025 Usman Tahir, Erwan Darmawan, Farisan Robbbani (Author) https://creativecommons.org/licenses/by-sa/4.0
Smart City System Review: Challenges and Opportunities for Implementation in Urban Areas
Rapid urbanization has pushed cities in Indonesia to face complex challenges related to infrastructure capacity, public services, and urban governance. Smart cities are seen as a strategic solution to build efficient, adaptive, and sustainable cities through the use of digital technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data. However, the implementation of smart cities in Indonesia still faces various obstacles, including digital infrastructure inequality, low human resource capacity, and weak institutional coordination. This study uses a qualitative descriptive approach and a SWOT analysis framework to identify the strengths, weaknesses, opportunities, and threats in the implementation of smart cities in urban areas in Indonesia. Data were obtained from policy literature studies, national and international agency reports, and smart city project documentation. The results of the study show that the success of smart cities is highly dependent on the synergy between infrastructure readiness, utilization of technological opportunities, and mitigation of socio-technological risks. Policies are needed that encourage cross-sector collaboration, citizen data protection, and strengthening digital literacy and local capacity. With a participatory approach and inclusive governance, smart cities can be an instrument for transforming cities that are not only technologically modern, but also socially just and sustainable in the long term.
Copyright (c) 2025 Julinaldi Julinaldi, Nursahar Buang , Dody Dody, Muhammad Ade Kurnia Harahap (Author) https://creativecommons.org/licenses/by-sa/4.0
Literature Review on the Role of Mechanical Engineering in Supporting the Industrial Revolution 5.0
The Industrial Revolution 5.0 marks a paradigm shift from full automation to symbiotic collaboration between humans and machines, emphasizing a human-centric approach, sustainability, and the integration of intelligent technologies. In this context, the role of mechanical engineering has undergone a significant transformation, from merely designing mechanical systems to becoming a multidisciplinary bridge between digital technology and human needs. This study aims to review the literature related to the contribution of mechanical engineering in supporting intelligent manufacturing systems, human-machine collaboration, and the application of sustainability principles such as circular economy and eco-design. Using a qualitative literature study method, data were obtained from indexed academic sources in the last decade and analyzed using a thematic approach. The results of the study indicate that mechanical engineering must integrate artificial intelligence, the Internet of Things (IoT), and cyber-physical systems to support adaptive and efficient production. In addition, the development of cobots requires expertise in safety-based and ergonomic design. In terms of the environment, mechanical engineers are required to apply the principles of product life cycle engineering and low-emission technologies. This transformation creates cross-field challenges that require new competencies and a systemic approach. Therefore, a comprehensive literature review is a strategic basis for formulating the direction of adaptive and sustainable mechanical engineering development in the Industry 5.0 era
Copyright (c) 2025 Eric Krisna (Author) https://creativecommons.org/licenses/by-sa/4.0
Establishing Effective Processes in Information Systems
In the era of increasingly developing digital transformation, information systems (IS) no longer function only as administrative tools, but have become strategic components in supporting the sustainability and competitive advantage of organizations. This study aims to evaluate strategic planning of information systems using the Ward and Peppard methodology approach that emphasizes the alignment between business strategy and IS strategy. A descriptive qualitative approach with case studies is used in this study, with data collection through documentation studies and literature reviews. The analysis was carried out using various techniques, including SWOT, Value Chain, Critical Success Factors (CSF), Balanced Scorecard, McFarlan's Strategic Grid, and PEST. The results of the study indicate that the success of IS implementation is greatly influenced by a deep understanding of the organization's strategic needs and the use of appropriate methodologies to identify relevant IS applications. Ward and Peppard's methodology is able to provide a systematic framework for integrating information technology into business processes as a whole. Thus, IS strategic planning not only improves operational efficiency but also plays an important role in supporting the right decision making and the development of the organization's adaptive capabilities in facing the dynamics of the external environment. These findings provide an important basis for organizations in determining IT strategies that are aligned with long-term goals
Copyright (c) 2024 Abdullah Haikal Fikri (Author) https://creativecommons.org/licenses/by-sa/4.0
Amidst increasingly tight business competition and increasingly critical customers in choosing products or services, companies are required to build more personal and sustainable relationships through Customer Relationship Management (CRM) strategies. The IDIC (Identify, Differentiate, Interact, Customize) model developed by Peppers and Rogers is one of the effective approaches in implementing CRM in a structured and strategic manner. This study aims to analyze the application of the IDIC Model in improving the effectiveness of customer relationship management. The approach used is qualitative with descriptive-analytical methods, through literature studies and literature analysis from various relevant sources. The results of the discussion show that the IDIC Model facilitates companies to recognize customers comprehensively, differentiate them based on value and needs, build meaningful interactions, and customize offers individually. Identify and Interact are included in the operational CRM realm, while Differentiate and Customize are part of analytical CRM that relies on customer data analysis. This model enables large-scale personalization, which is strengthened by big data technology and artificial intelligence (AI), so that companies can increase customer engagement, loyalty, and business profits sustainably. The application of the IDIC Model reflects a shift from mass marketing to a more relevant one-to-one marketing approach in the digital era
Copyright (c) 2024 Miftahur Rizky (Author) https://creativecommons.org/licenses/by-sa/4.0
Assessing And Understanding The Current Situation In Information Systems
This study aims to examine the information system strategy in supporting the alignment between business needs and technology utilization through the Business Process Reengineering (BPR) approach. In a dynamic business environment, understanding external opportunities and threats, as well as the organization's internal capabilities, is an important foundation in designing information systems that can drive efficiency, effectiveness, and competitive advantage. Information systems not only play a role as operational support, but also as a driver of strategic transformation through innovation in processes, structures, and organizational culture. This study uses a qualitative descriptive method with a case study approach, involving in-depth interviews, observations, and documentation studies. The analysis techniques used include Critical Success Factors (CSF), Balanced Scorecard (BSC), and gap analysis to map actual conditions and determine future strategies. The results of the study are expected to produce an application portfolio that is in accordance with the needs of the organization, as well as a BPR strategy that is oriented towards improving service quality, reducing costs, and customer satisfaction. The strategic value of information systems is largely determined by the extent to which business understanding is integrated into the design of an adaptive system. Active participation at all levels of the organization, including through workshops based on actual data, is key to formulating effective and sustainable strategies.
Copyright (c) 2024 Anisatul Maghfiroh (Author) https://creativecommons.org/licenses/by-sa/4.0
Literature Study: Potential of 3D Printing Technology in the World of Mechanical Engineering and Manufacturing
This study discusses the paradigm shift in mechanical engineering due to the adoption of 3D printing technology as part of the industrial revolution 4.0. This additive manufacturing technology offers advantages in terms of design complexity, production efficiency, and cost flexibility, but also raises technical challenges such as material anisotropy, surface roughness, and process parameter control. Through a descriptive qualitative approach based on literature studies, this study explores the impact of 3D printing on the structure of the manufacturing industry, performance-based design, and the need for reform in engineering education. Data sources are taken from scientific journals, academic books, and technical reports from the last decade (2014–2024), with a thematic analysis of technology applications, implementation challenges, and implications for mechanical engineering curricula. The results show that although 3D printing has fundamentally changed the design and production process, its integration into the industry is still limited by conventional supply chain structures and lack of human resource readiness. This study emphasizes the importance of transforming the engineering education system towards a digital-based interdisciplinary approach, as well as the need for critical and contextual technology adoption. Thus, 3D printing does not only act as a production tool, but also as a catalyst for systemic change in mechanical engineering and manufacturing.
Copyright (c) 2025 Ari Beni Santoso, Rahmad Surya Hadi Saputra (Author) https://creativecommons.org/licenses/by-sa/4.0
Optimization of On-Grid Solar Power Plant Design for Urban Residential Areas: Case Study in Indonesia
The increasing demand for electricity in urban areas of Indonesia demands diversification of sustainable energy sources. On-grid Solar Power Plants (PLTS) are a strategic alternative to reduce dependence on fossil fuels and increase household energy resilience. However, optimizing PLTS design still faces technical and structural challenges, such as the mismatch between panel production capacity and electricity consumption patterns, limited space, and weak regulatory support and fiscal incentives. This study uses a qualitative approach with a case study in an urban housing complex to examine the design process, implementation, and obstacles of on-grid PLTS. Data were obtained through in-depth interviews, field observations, and studies of policy and technical documents. The results of the study indicate that the success of PLTS implementation is highly dependent on a design that is contextual to the technical and social characteristics of housing, the support of fiscal policies such as initial subsidies, and institutional integration between communities, local governments, and the private sector. In addition, community-based approaches such as energy cooperatives can increase inclusive system adoption. This study concludes that on-grid PLTS is not only a technical solution for the clean energy transition, but also an instrument of socio-economic transformation that requires multidimensional synergy in its implementation in the urban environment of Indonesia
Copyright (c) 2025 Doni Suseno, I Putu Hikariantara, Usman Tahir, Miko Mei Irwanto (Author) https://creativecommons.org/licenses/by-sa/4.0
Hybrid Renewable Energy System: Sustainable Energy Engineering Solutions For The Future
This study aims to examine the potential contribution of the Hybrid Renewable Energy System in supporting sustainable energy transitions in the future, especially in the context of reducing carbon emissions and dependence on fossil fuels. This study uses a descriptive-quantitative research type with an engineering simulation approach. The study focuses on modeling and analyzing the contribution of a hybrid renewable energy system (HRES) in reducing carbon emissions and reducing dependence on fossil fuels. . Based on the results of observations and analysis of technical data on solar radiation and daily wind speed, photovoltaic (PV)-based renewable energy systems show significant technical potential in generating electricity consistently throughout the year, especially in tropical areas. Meanwhile, although the potential for wind energy is relatively smaller, especially in areas with low average wind speeds, wind turbines can still provide additional contributions — especially when solar conditions are limited such as at night or in the rainy season. By combining these two energy sources into a hybrid system (HRES), the efficiency of renewable energy utilization can be maximized. The combination of PV and wind turbines allows : 1 ) Direct carbon emission reduction, which is ~22.7 tons of CO₂ per year from the PV system alone. 2) Diversification of energy sources, which reduces vulnerability to single dependence on fossil fuels. 3) Increasing the reliability of the electricity system, especially for remote areas and areas not yet covered by the PLN network. Overall, HRES provides a practical, efficient, and sustainable solution to meet the energy needs of small to medium-scale communities. It also opens up opportunities for energy decentralization, promotes a green economy, and strengthens Indonesia's commitment to net zero emissions targets in the future.
Copyright (c) 2025 Loso Judijanto (Author) https://creativecommons.org/licenses/by-sa/4.0
The Industrial Revolution 5.0 marks a paradigm shift from full automation to symbiotic collaboration between humans and machines, emphasizing a human-centric approach, sustainability, and the integration of intelligent technologies. In this context, the role of mechanical engineering has undergone a significant transformation, from merely designing mechanical systems to becoming a multidisciplinary bridge between digital technology and human needs. This study aims to review the literature related to the contribution of mechanical engineering in supporting intelligent manufacturing systems, human-machine collaboration, and the application of sustainability principles such as circular economy and eco-design. Using a qualitative literature study method, data were obtained from indexed academic sources in the last decade and analyzed using a thematic approach. The results of the study indicate that mechanical engineering must integrate artificial intelligence, the Internet of Things (IoT), and cyber-physical systems to support adaptive and efficient production. In addition, the development of cobots requires expertise in safety-based and ergonomic design. In terms of the environment, mechanical engineers are required to apply the principles of product life cycle engineering and low-emission technologies. This transformation creates cross-field challenges that require new competencies and a systemic approach. Therefore, a comprehensive literature review is a strategic basis for formulating the direction of adaptive and sustainable mechanical engineering development in the Industry 5.0 era.
Copyright (c) 2025 Idzani Muttaqin (Author) https://creativecommons.org/licenses/by-sa/4.0
Preventive Maintenance Strategies to Increase Industrial Machine Life
In modern industries that increasingly rely on machines and automation systems, efficient maintenance is key to maintaining production continuity and avoiding losses due to unscheduled downtime. Preventive maintenance has emerged as a more effective solution compared to the corrective maintenance approach, which is reactive. This study discusses the urgency of implementing preventive maintenance in improving machine reliability, extending equipment life, and reducing long-term costs. The use of advanced technologies such as the Internet of Things (IoT), Computerized Maintenance Management Systems (CMMS), and predictive analytics can optimize preventive maintenance by detecting potential failures early, thereby minimizing downtime by up to 50%. However, the effectiveness of this strategy is highly dependent on the readiness of the digital infrastructure and the competence of the human resources (HR) who manage the technology. Without the integration of historical data, real-time monitoring systems, and adequate training, the implementation of preventive maintenance is at risk of being less than optimal. Therefore, the development of a technology-based preventive maintenance strategy must be accompanied by increased technical and managerial capacity, as well as organizational readiness to adapt to digital change. This research shows that a structured, data-driven preventive approach can support operational efficiency, strengthen competitiveness, and support industry sustainability.
Copyright (c) 2025 Amalia Tasya, Muhammad Suprapto (Author) https://creativecommons.org/licenses/by-sa/4.0
Smart City Priority Innovation Assessment In West Bandung Regency
This study aims to assess the implementation of smart city innovations in West Bandung Regency in 2024, focusing on evaluating user satisfaction with the priority applications that have been launched. The research method uses the Unified Theory of Acceptance and Use of Technology (UTAUT) model to measure Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions variables, as well as their impact on customer satisfaction. Data were collected through questionnaires from public servants associated with 37 smart city innovations. The results showed that Smart Branding: Visit KBB had the highest Performance Expectancy and Facilitating Conditions scores, while BA QRIS and Smart Branding: Visit KBB applications had the highest Effort Expectancy scores. The implications of this research are to provide recommendations for improving the effectiveness and acceptance of smart city applications in West Bandung Regency, as well as providing insights for the development of future smart city programs.
Copyright (c) 2025 Rizky Fajar Ramdhani, Hady Sofyan (Author) https://creativecommons.org/licenses/by-sa/4.0