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Green Engineering: Journal of Engineering and Applied Science

GreenEngineering
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Published by International Forum of Researchers and Lecturers

ISSN : 30636841 EISSN : 30636833 DOI : 10.70062

Core Subject : Agriculture, Engineering,

Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering

(Green Engineering: Journal of Engineering and Applied Science) [e-ISSN : 3063-6833, p-ISSN : 3063-6841] is an open access Journal published by the IFREL ( Forum of Researchers and Lecturers). Green Engineering accepts manuscripts based on empirical research results, new scientific literature review, and comments/ criticism of scientific papers published by Green Engineering. This journal is a means of publication and a place to share research and development work in the field of Engineering and Applied Science. Articles published in Green Engineering are processed fully online. Submitted articles will go through peer review by a qualified international Reviewers. Complete information for article submission and other instructions are available in each issue. Green Engineering publishes 4 (four) issues a year in January, April, July and October, however articles that have been declared accepted will be queued in the In-Press issue before published in the determined time.

Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)

Articles 42 Documents

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Integrated Maritime Workforce Resilience and Health Management Frameworks: Post-Pandemic Seafarer Wellbeing and Organizational Safety Culture Transformation Ramadhan Hasri Harahap
Green Engineering: International Journal of Engineering and Applied Science Vol. 3 No. 1 (2026): January: Green Engineering: International Journal of Engineering and Applied Sc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v3i1.264

This research investigates integrated maritime workforce resilience and mental health management frameworks addressing post-pandemic seafarer wellbeing challenges and organizational safety culture transformation. Through qualitative analysis involving 39 stakeholders including seafarers, ship operators, mental health professionals, maritime unions, training institutions, and maritime authorities, this study examines how COVID-19 pandemic intensified mental health crises through extended contracts, shore leave restrictions, and isolation while exposing systemic inadequacies in psychological support systems. Results demonstrate that comprehensive mental health frameworks can reduce psychological distress by 55-70%, improve safety performance by 40-55%, enhance crew retention by 45-60%, and decrease incident rates by 35-50% when integrating organizational culture change, leadership competency development, predictive analytics, and culturally-adapted interventions. Key challenges include mental health stigma (affecting 65-80% of seafarers), limited organizational investment (only 18-25% adequate), service accessibility gaps, and workforce demographic diversity requiring culturally-sensitive approaches. Findings reveal that effective mental health management requires systemic organizational transformation integrating psychological wellbeing into safety management systems, work design optimization, family support programs, and career sustainability rather than treating mental health as peripheral welfare concern, supporting maritime industry's workforce retention and operational safety imperatives.

Evaluating the Impact of Distributed Solar-Battery Systems on Urban Electricity Resilience and Community Carbon Emissions Reduction Idi Jang Acik; Soleman; Syeda Azwa Asif
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 1 (2025): January: Green Engineering: International Journal of Engineering and Applied Sc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i1.272

This study evaluates the impact of distributed solar-battery systems on urban electricity resilience and community carbon emissions reduction. As urban areas continue to grow, the demand for electricity has placed considerable strain on traditional centralized grids, resulting in increased vulnerabilities. The integration of decentralized energy resources (DERs), particularly solar photovoltaic (PV) systems paired with battery energy storage systems (BESS), has emerged as a promising solution to enhance grid resilience, reduce carbon emissions, and support the transition to more sustainable energy systems. This research uses a simulation-based approach to model the integration of solar-battery systems into residential blocks, assessing their impact on grid reliability, downtime reduction, and the frequency of power outages. Additionally, the study estimates the reduction in carbon dioxide (CO₂) emissions achieved by shifting from fossil-fuel-based energy generation to renewable sources such as solar PV. The results demonstrate that solar-battery systems significantly improve electricity reliability by providing backup power during outages, while also reducing CO₂ emissions by decreasing reliance on conventional grids. The study also discusses the technical and financial challenges associated with the integration of these systems, such as energy storage capacity, system efficiency, and upfront installation costs. Policy recommendations emphasize the importance of government incentives, grid modernization, and long-term financial benefits to encourage the adoption of decentralized energy solutions. Finally, the study highlights areas for future research, including advanced storage technologies and the integration of electric vehicles with solar-battery systems to further enhance energy resilience and sustainability.

Optimization of Electric Vehicle Battery Recycling through Green Chemical Processes and Circular Economy Principles Yuniansyah Yuniansyah; Suprayuandi Suprayuandi; Evan Apriadi Delatama; Tri Akhayari Romadhon
Green Engineering: International Journal of Engineering and Applied Science Vol. 1 No. 2 (2024): April: Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v1i2.257

This study focuses on optimizing electric vehicle (EV) battery recycling through the use of green chemical processes and circular economy principles. The research aims to enhance the recovery of valuable metals lithium, cobalt, and nickel from used lithium-ion batteries (LIBs) in an environmentally sustainable manner. Green solvents were employed as a safer alternative to conventional, toxic chemicals, minimizing hazardous waste emissions and improving the efficiency of the recycling process. Experimental results showed that the green solvent-based process achieved high recovery rates of 90% for cobalt, 87% for nickel, and 85% for lithium, with metal purity levels exceeding 95% for all three metals. The study also examined the scalability of the green solvent method, revealing its potential to offer more sustainable and cost-effective solutions compared to traditional methods, which typically involve high temperatures and toxic chemicals. Despite the promising results, challenges such as solvent recovery and the adaptation of the process for large-scale industrial applications remain. Nonetheless, the study demonstrates that integrating green solvent-based recycling into the global EV supply chain can significantly reduce environmental impacts, conserve resources, and support the transition to a circular economy. The findings highlight the potential of this recycling method to provide a more sustainable and efficient solution for EV battery recycling, ultimately contributing to the development of a more sustainable EV industry.

Integration of Advanced Biodegradable Polymer Coatings with Solar-Powered Textile Waste Treatment for Reducing Microplastic Pollution in Urban Runoff Systems Rizqi Elmuna Hidayah; Yohandika Tri Apriliyanto; Beta Arya Ash Shidik
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 1 (2025): January: Green Engineering: International Journal of Engineering and Applied Sc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i1.280

Microplastic pollution, particularly from textile waste, has become a significant environmental concern, especially in urban runoff systems. These pollutants pose a considerable threat to water quality, aquatic life, and human health. Traditional wastewater treatment methods often fall short in addressing the complexities of microplastic contamination. This research explores the integration of advanced biodegradable polymer coatings with solar-powered textile waste treatment to reduce microplastic pollution in urban runoff systems. Biodegradable polymers, such as polylactic acid (PLA) and polyhydroxyalkanoates (PHA), are highlighted for their potential to efficiently filter microplastics while providing an eco-friendly alternative to conventional filtration technologies. By combining these materials with a small solar-powered unit, the prototype enables an off-grid, low-energy solution to treat textile wastewater in urban environments. The study includes testing the prototype in simulated urban runoff conditions with varying concentrations of microplastics, evaluating key performance indicators such as microplastic removal efficiency, energy consumption, and operational sustainability. Results demonstrate a significant reduction in microplastic concentration, indicating the effectiveness of biodegradable polymer coatings and solar-powered systems in treating urban runoff. The discussion addresses the feasibility of using local biodegradable materials, performance in real-world urban environments, and operational challenges such as maintenance and scalability. This innovative approach is compared with existing microplastic filtration methods, such as membrane filtration and adsorption, highlighting its advantages in terms of sustainability and cost-effectiveness. The findings suggest that this integrated system could offer a viable, low-cost solution for addressing microplastic pollution in urban drainage systems, with potential for widespread urban implementation.

Performance Governance Analysis of the Career Center Information System at Universitas Muhammadiyah Jambi Using COBIT 2019 Fadila Fitrianisa; Noneng Marthiawati; Kevin Kurniawansyah; Arniwita Arniwita
Green Engineering: International Journal of Engineering and Applied Science Vol. 3 No. 2 (2026): April : Green Engineering: International Journal of Engineering and Applied Sci
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v3i2.282

This study analyzes the governance performance of information systems at the Career Center of Universitas Muhammadiyah Jambi using the COBIT 2019 framework. The primary objective is to evaluate the maturity level of IT governance and provide recommendations to enhance the efficiency and effectiveness of information systems in supporting the institution’s strategic objectives. Data were collected through interviews, observations, and questionnaires involving system users and decision-makers within the Career Center. The findings indicate that several areas require greater attention, particularly Managed IT Changes, Managed Risk, and Managed Operations. These domains are considered critical in improving the management and reliability of the existing information systems. The study also identifies several challenges affecting system performance, including limited system integration, insufficient human resources, and the use of outdated technology. Based on these findings, the research recommends strengthening the organizational structure, improving the competence of human resources, and optimizing IT processes in accordance with COBIT 2019 standards. Implementing these improvements is expected to increase IT governance maturity, enhance service quality for students and alumni, and better support the university’s strategic development goals.

Developing a Visual Module-Based Internship Learning Model for Students with Deafness in Vocational High School Ewit Dihasma Yulianingrum; Kokom Komariah
Green Engineering: International Journal of Engineering and Applied Science Vol. 3 No. 2 (2026): April : Green Engineering: International Journal of Engineering and Applied Sci
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v3i2.283

This study aims to identify the learning needs of deaf students in internship programs, examine the challenges they face, develop appropriate solutions, and design as well as evaluate a visual module-based learning model to improve their work skills. The study used a Research and Development (R&D) approach with a 4D model: Define, Design, Develop, and Disseminate. The participants included deaf students from special needs high schools (SMALB) involved in vocational internships, mentor teachers, and industry supervisors. Data were collected through observation, interviews, questionnaires, documentation, and focus group discussions, and analyzed using qualitative techniques supported by descriptive analysis. The findings indicate that deaf students require visual, structured, and easily understandable work instructions supported by symbols, color codes, and guidance materials. Major challenges include limited verbal communication, difficulty understanding instructions, and risks of procedural errors. To address these issues, a systematic and communicative visual module-based learning model was developed, incorporating collaborative support from schools and industry. The resulting model integrates planning, implementation, mentoring, and evaluation stages, and has proven feasible and effective in enhancing students’ independence, technical competence, and overall work readiness.

Framework for Circular-Economy Based Remanufacturing in Electrical and Electronic Equipment: A Case Study Approach Abdul Azis; Edwar Ali
Green Engineering: International Journal of Engineering and Applied Science Vol. 1 No. 1 (2024): January: Green Engineering: International Journal of Engineering and Applied Sc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v1i1.284

E-waste has become a critical global issue due to the rapid growth of electronic product consumption and the environmental risks associated with improper disposal. Traditional disposal methods, such as landfilling and incineration, are no longer sustainable as they lead to environmental degradation, health hazards, and loss of valuable resources. In contrast, remanufacturing, a key component of the circular economy, offers a more sustainable solution. This study explores the effectiveness of remanufacturing as a strategy for e-waste management, focusing on its ability to reduce waste generation and improve material efficiency in the electronics industry. The research utilizes a case study approach, examining industrial-scale remanufacturing processes, including material input-output analysis to track resource flows and waste streams. The findings reveal a significant reduction in e-waste generation, with up to a 50% decrease in waste volume, and substantial improvements in material recovery, particularly in metals like gold and copper. Additionally, the study highlights the economic and environmental benefits of remanufacturing, such as cost savings and resource conservation. However, the study also identifies barriers to the widespread adoption of remanufacturing, including technological, financial, and regulatory challenges. The results underscore the potential of a circular-economy-based remanufacturing model as a sustainable solution for the electronics industry. The study calls for further research into improving remanufacturing technologies, enhancing policy frameworks, and expanding circular economy practices across various industries.

Carbon Neutral Industrial Process Optimization through Hybrid Machine Learning and Real Time Energy Efficiency Monitoring Framework Suyahman Suyahman; Ardy Wicaksono; Dwi Utari Iswavigra; Yogiek Indra Kurniawan; Very Dwi Setiawan; Dedi Setiadi
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 2 (2025): April : Green Engineering: International Journal of Engineering and Applied Sci
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i2.285

Introduction: Achieving carbon neutrality in industrial systems is essential for mitigating climate change and promoting sustainability. The increasing demand for energy optimization and carbon emission reduction has driven the development of advanced technologies, particularly hybrid machine learning (ML) models. These models, combining ensemble learning and reinforcement learning (RL), offer significant promise in optimizing industrial processes, reducing energy consumption, and improving environmental performance. This study explores the application of hybrid ML models in achieving carbon neutral goals through dynamic process optimization and energy control in industrial settings. Literature Review: Hybrid ML models integrate different machine learning techniques to handle complex and dynamic environments effectively. Ensemble learning methods, such as boosting, bagging, and stacking, combine multiple algorithms to improve predictive performance and robustness. Reinforcement learning (RL), on the other hand, enables real time decision making and adaptation based on trial and error interactions with the environment. In energy optimization, these models are used to reduce energy intensity and carbon emissions, enhancing overall operational efficiency. Previous studies have demonstrated the effectiveness of ML models in energy management, but challenges such as data quality, model integration, and computational complexity remain. Materials and Method: The study applies hybrid ML models combining ensemble learning and RL to optimize energy consumption and minimize carbon emissions in industrial processes. Data from real time sensors and operational parameters are used to train the models. The ensemble learning component improves the accuracy of energy predictions, while RL ensures dynamic process adjustments in response to fluctuating energy demand. The models were tested in various industrial settings, including manufacturing processes, smart grids, and microgrid systems. Performance metrics such as energy efficiency, carbon emissions reduction, and operational costs were evaluated to assess the effectiveness of the models. Results and Discussion: The hybrid ML models achieved significant reductions in energy intensity (15-20%) and carbon emissions (18-25%). The real time adaptability of the RL component allowed the models to adjust energy consumption patterns dynamically, improving energy efficiency and reducing waste. The models demonstrated their ability to adapt to varying operational conditions, ensuring optimal energy use. A cost-benefit analysis showed that the hybrid models provided substantial energy savings and reduced operational costs, with a return on investment (ROI) of 30-35% within the first year of deployment. However, challenges such as computational complexity and data quality issues were identified, highlighting the need for further refinement in model development.

Design of an Autonomous Solar Powered Smart Aquaculture Monitoring System for Energy Efficiency and Environmental Impact Reduction Lukman Medriavin Silalahi; Safrizal Safrizal; Erick Fernando; Hayadi Hamuda; Ribut Julianto; Yuanita Sinatrya
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 2 (2025): April : Green Engineering: International Journal of Engineering and Applied Sci
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i2.286

Aquaculture is a vital sector in global food production, providing essential protein sources. However, the industry faces significant challenges, including high energy consumption and environmental impact. The integration of renewable energy, particularly solar power, with automation and IoT systems offers a promising solution to enhance energy efficiency, sustainability, and productivity in aquaculture operations. This study aims to evaluate the effectiveness of solar powered autonomous systems in reducing energy usage, improving operational efficiency, and promoting environmental sustainability in aquaculture. Literature Review: Recent research has explored various technologies, such as Digital Twins (DTs) and Precision Fish Farming (PFF), which integrate IoT sensors for real time monitoring and optimization of fish farming operations. The combination of Artificial Intelligence (AI) and the Internet of Things (IoT), known as AIoT, has further advanced the industry by enabling automated decision making and predictive analytics. Solar power integration with IoT systems has been shown to significantly reduce operational costs, minimize carbon emissions, and enhance the sustainability of aquaculture practices. These advancements have the potential to address the challenges of energy consumption and environmental degradation in the industry. Materials and Method: This research utilizes a hybrid solar powered IoT system for aquaculture, integrating solar panels, IoT sensors, and automated control systems. The system monitors key water quality parameters, such as pH, dissolved oxygen, turbidity, and temperature, to maintain optimal conditions for aquatic life. Data is collected through IoT sensors and analyzed through a cloud-based platform. A pilot study is conducted on a small scale aquaculture farm to evaluate the system's performance, including energy consumption, water quality management, and fish health. Energy savings, operational efficiency, and environmental impact are assessed. Results and Discussion: The integration of solar powered IoT systems significantly reduced energy consumption compared to traditional systems, with a notable decrease in grid electricity reliance. The system successfully maintained optimal water quality conditions, enhancing fish health and growth. Solar powered systems proved reliable, even in regions with variable sunlight, and demonstrated improvements in operational efficiency through automation. The environmental benefits were evident, with a reduction in carbon emissions and lower operational costs. The study highlights the feasibility of solar powered IoT systems as a sustainable solution for modern aquaculture operations.

Development of a Digital Twin Based Smart Green Building Energy Management Model Integrating IoT Sensors and Predictive Sustainability Analytics Asro Asro; Solihin Solihin; John Chaidir; Febri Adi Prasetya; Tuti Susilawati; Muhamad Furqon; Bentar Priyopradono
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 2 (2025): April : Green Engineering: International Journal of Engineering and Applied Sci
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i2.287

Introduction: The integration of Digital Twin (DT) technology and the Internet of Things (IoT) into Building Energy Management Systems (BEMS) offers a transformative approach to optimizing energy consumption in buildings. This study explores the development of a Digital Twin based BEMS prototype, which leverages real time data collection, predictive analytics, and machine learning to enhance energy efficiency, reduce costs, and support sustainability goals in modern buildings. The research also addresses key gaps in current energy management systems, including real time adaptive control and integration with smart grid platforms. Literature Review: Previous research highlights the limitations of traditional BEMS, which often rely on static control strategies and lack real time adaptability. Recent advancements, including predictive maintenance and machine learning integration, have improved energy optimization. However, challenges such as data interoperability, scalability, and cybersecurity remain. This review consolidates current approaches and identifies opportunities for enhancing BEMS through the integration of DT technology, IoT, and machine learning. Materials and Method: The methodology employed involves the design of a Digital Twin based BEMS prototype, incorporating IoT sensors for real time data collection on variables such as HVAC load, occupancy, and environmental factors. The system uses time series forecasting and adaptive control strategies to optimize energy consumption. A case study building is used for validation, with performance metrics such as energy savings, CO₂ footprint reduction, and peak load reduction assessed to evaluate the system's effectiveness. Results and Discussion: The results demonstrate a significant reduction in energy consumption (up to 50%) compared to traditional BEMS, along with improved forecasting accuracy and sustainability performance. The prototype achieved a high R² score in predicting energy usage, validated through real world application in the case study building. The economic feasibility analysis showed substantial cost savings and a strong return on investment, making the system a financially viable solution for energy efficient building management.

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Contact Name Abdul Karim

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Editorial Address Jalan Watunganten 1 No 1-6, Batursari, Mranggen, Kab. Demak, Provinsi Jawa Tengah, 59567

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Contact Name
Abdul Karim

Contact Email
indexsasi@apji.org

Phone
+6282135809779

Journal Mail Official
info@ifrel.org

Editorial Address
Jalan Watunganten 1 No 1-6, Batursari, Mranggen, Kab. Demak, Provinsi Jawa Tengah, 59567

Location
Kab. demak,

Jawa tengah

INDONESIA