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Journal of Renewable Engineering
Published by PT Anagata Sembagi Education
ISSN : -     EISSN : 30467624     DOI : https://doi.org/10.62872/zm22xb92
Core Subject : Engineering,
Automotive Engineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering
The journal publishes original articles on current issues and trends occurring internationally in mechanical engineering, electrical engineering, civil engineering, physical engineering, chemical engineering, industrial engineering, informatics engineering, telecommunications engineering, computer engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 4 (2025): JORE - August" : 5 Documents clear
Literature Review: Integration of Hybrid Renewable Energy Systems in Remote Areas Sulaiman A; Minarti Minarti; Rahmad Surya Hadi Saputra
Journal of Renewable Engineering Vol. 2 No. 4 (2025): JORE - August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/ex26fj18

Abstract

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.
Industrial Revolution 4.0 In Mechanical Engineering: A Literature Review On The Application Of Iot And Automation In Production Systems Arie Wahyu Prananta; Dwiyanto Dwiyanto
Journal of Renewable Engineering Vol. 2 No. 4 (2025): JORE - August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/f9kz7a81

Abstract

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.
The Application of Artificial Intelligence in Industrial Supply Chain Optimization and Its Implications for Business Performance Arie Wahyu Prananta; Amelia Hayati
Journal of Renewable Engineering Vol. 2 No. 4 (2025): JORE - August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/02xg5t30

Abstract

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.
Exploration of Stakeholder Perceptions on the Application of Biomining for Mining Waste Management Rafiuddin
Journal of Renewable Engineering Vol. 2 No. 4 (2025): JORE - August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/2vpjgt65

Abstract

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.       
SWOT Analysis of the Application of Battery-Free Sensor Systems for Smart Infrastructure: A Literature Review on Micro Energy Technology Dwiyanto Dwiyanto
Journal of Renewable Engineering Vol. 2 No. 4 (2025): JORE - August
Publisher : Pt. Anagata Sembagi Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62872/n1kyg656

Abstract

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

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