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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Mechatronics, Electrical Power, and Vehicular Technology Jurnal Ketahanan Nasional Sinergi JOURNAL OF MECHANICAL ENGINEERING, MANUFACTURES, MATERIALS AND ENERGY VOX EDUKASI: Jurnal Ilmiah Ilmu Pendidikan Journal of Renewable Energy, Electrical, and Computer Engineering Jurnal Informatika Teknologi dan Sains (Jinteks) Heca Journal of Applied Sciences Leuser Journal of Environmental Studies Journal of Educational Management and Learning Grimsa Journal of Science Engineering and Technology Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada
Erkata Yandri
Universitas Darma Persada
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Medicine & Pharmacology Physics Other

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Leading Light: The Impact of Advanced Lighting Technologies on Indonesia's Office Industry Murdiyansyah, Novan; Yandri, Erkata; Lodewijk, Dewi Putriani Yogosara; Ariati, Ratna
Leuser Journal of Environmental Studies Vol. 2 No. 1 (2024): April 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v2i1.140

Abstract

Addressing concerns over resource scarcity and environmental sustainability necessitates a global shift towards sustainable energy, notably facilitated by adopting Light-Emitting Diode (LED) lamps. This transition is pivotal for ensuring global energy security and aligning with sustainability goals. This study endeavors to comprehensively analyze potential energy savings achievable through the transition from Fluorescent (FL) lamps to LED lamps within industrial offices. Emphasis is placed on highlighting the central role of energy efficiency. Utilizing false color rendering as a visual guide, the study systematically identifies areas where FL lamps inadequately illuminate. The findings prompt recalculations for determining optimal room illumination achievable through implementing LED lamps. Lux calculations are then employed to showcase the superior illumination offered by LED lamps, revealing consistent monthly cost savings of 35%, particularly when harmonized with Building Management System (BMS) control in industrial office buildings. The study's results indicate that LED lamps provide superior illumination, yielding a noteworthy 35% monthly cost savings, especially when integrated with BMS control. Lamps contribute modestly (21-30%) to overall energy consumption, while air conditioning commands a substantial 60%, underscoring the critical need for advanced lighting technology. This need is emphasized, particularly with Solar PV as a sustainable energy source. Understanding technological developments, especially in BMS, is crucial to optimize energy efficiency in industrial offices. The imperative implementation of LED lighting technology is a critical solution to address resource scarcity and environmental concerns in industrial offices. The efficacy of LED lamps in achieving significant energy savings, especially when coupled with advanced systems like BMS and complemented by renewable energy sources such as Solar PV. The conclusion stresses the significance of staying abreast of technological advancements to foster sustained progress towards energy-efficient and environmentally conscious practices within industrial environments.
Optimizing University Admissions: A Machine Learning Perspective Maulana, Aga; Noviandy, Teuku Rizky; Sasmita, Novi Reandy; Paristiowati, Maria; Suhendra, Rivansyah; Yandri, Erkata; Satrio, Justinus; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 1 No. 1 (2023): August 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v1i1.46

Abstract

The university admission process plays a pivotal role in shaping the future of aspiring students. However, traditional methods of admission decisions often fall short in capturing the holistic capabilities of individuals and may introduce bias. This study aims to improve the admission process by developing and evaluating machine learning approach to predict the likelihood of university admission. Using a dataset of previous applicants' information, advanced algorithms such as K-Nearest Neighbors, Random Forest, Support Vector Regression, and XGBoost are employed. These algorithms are applied, and their performance is compared to determine the best model to predict university admission. Among the models evaluated, the Random Forest algorithm emerged as the most reliable and effective in predicting admission outcomes. Through comprehensive analysis and evaluation, the Random Forest model demonstrated its superior performance, consistency, and dependability. The results show the importance of variables such as academic performance and provide insights into the accuracy and reliability of the model. This research has the potential to empower aspiring applicants and bring positive changes to the university admission process.
Machine Learning for Early Detection of Dropout Risks and Academic Excellence: A Stacked Classifier Approach Noviandy, Teuku Rizky; Zahriah, Zahriah; Yandri, Erkata; Jalil, Zulkarnain; Yusuf, Muhammad; Mohamed Yusof, Nur Intan Saidaah; Lala, Andi; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 2 No. 1 (2024): May 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v2i1.191

Abstract

Education is important for societal advancement and individual empowerment, providing opportunities, developing essential skills, and breaking cycles of poverty. Nonetheless, the path to educational success is marred by challenges such as achieving academic excellence and preventing student dropouts. Early identification of students at risk of dropping out or those likely to excel academically can significantly enhance educational outcomes through tailored interventions. Traditional methods often fall short in precision and foresight for effective early detection. While previous studies have utilized machine learning to predict student performance, the potential for more sophisticated ensemble methods, such as stacked classifiers, remains largely untapped in educational contexts. This study develops a stacked classifier integrating the predictive strengths of LightGBM, Random Forest, and logistic regression. The model achieved an accuracy of 80.23%, with precision, recall, and F1-score of 79.09%, 80.23%, and 79.20%, respectively, surpassing the performance of the individual models tested. These results underscore the stacked classifier's enhanced predictive capability and transformative potential in educational settings. By accurately identifying students at risk and those likely to achieve academic excellence early, educational institutions can better allocate resources and design targeted interventions. This approach optimizes educational outcomes and supports informed policymaking, fostering environments conducive to student success.
RANCANG BANGUN LOW HEAD TURBIN PIKO HIDRO Aep Saepul Uyun; Bangun Novianto; Erkata Yandri; Syukri M Nur
Jurnal Sains & Teknologi Fakultas Teknik Universitas Darma Persada Vol. 10 No. 1 (2020): Jurnal Sains & Teknologi
Publisher : Fakultas Teknik Universitas Darma Persada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70746/jstunsada.v10i1.79

Abstract

Sumber energi listrik sangat dibutuhkan untuk memenuhi target elektrifikasi yang merata di pedesaan. Pemenuhah energi listrik di pedesaan tersebut dapat menggunakan energi setempat yang tersedia misalkan energi air. Potensi energi air yang dapat dimanfaatkan dapat berasal dari sungai-sungai kecil dengan pembangkit mini dan mikro-hidro. Tantangan terbesar dalam pemanfaatan energi air pada sungai-sungai tersebut adalah bagaimana mendesain turbin air yang sesuai dengan tipe sungai low head tersebut. Karena setiap lokasi air memiliki kondisi lokasi yang berbeda, maka desain, pemilihan jenis dan ukuran turbin yang tepat menjadi lebih penting. Penelitian ini merupakan desain secara teoritis dalam optimasi perancangan profile sudu turbin serta analisis efek pusaran air pada prestasi turbin. Metode yang digunakan dalam penelitian ini adalah dengan mengembangakan model turbin menggunakan teori sayap. Selanjutnya dengan analisis numerik dihitung analisis daya hilang pada sistem akibat pusaran air. Hasil simulasi menunjutkan bahwa sudut serang optimum menghasilkan daya prediksi sebesar 976 W, serta daya hilang pada pusaran sebesar 8 W, sementara daya hilang total sebesar 59.5W atau efisiensi sistem berkurang 6% dengan efisiensi keseluruhan sebesar 74.5%.
Optimizing Compressed Air Operations for Electrical Energy Savings: A Case Study in Pharmaceutical Packaging Manufacturing Candra, Arief; Yandri, Erkata; Saiful, Rifki; Uhanto, Uhanto; Hilmi, Erik; Hamja, Nasrullah; Ariati, Ratna
Grimsa Journal of Science Engineering and Technology Vol. 2 No. 2 (2024): October 2024
Publisher : Graha Primera Saintifika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61975/gjset.v2i2.58

Abstract

This study in pharmaceutical packaging manufacturing focuses on improving compressed air efficiency through targeted strategies at both the source and user levels by establishing a baseline to analyze energy consumption patterns. Key measures, including minimizing air leaks, adjusting pressure, and optimizing compressor performance, aim to achieve a 20-50% increase in efficiency, thereby supporting environmental sustainability. The User Point and Source Point approaches are expected to lower Specific Power Consumption (SPC), with data collected from December 2020 to May 2022 providing insights into potential energy savings. Establishing this baseline, based on machine runtime and productivity, offers a solid foundation for evaluation. Results show a 23% reduction in compressor electricity usage and a 7-8% decrease in compressed air consumption. A structured improvement process and strong collaboration between engineering and management are essential for enhancing productivity and achieving sustainable energy efficiency in the industrial sector.
Hybrid Energy Solutions for Sustainable Offshore Oil and Gas Operations: Leveraging Thermoelectric, Solar, and Wind Potential Hilmi, Erik; Yandri, Erkata; Uhanto, Uhanto; Saiful, Rifki; Hamja, Nasrullah
Leuser Journal of Environmental Studies Vol. 2 No. 2 (2024): October 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v2i2.218

Abstract

The transition towards sustainable offshore oil and gas operations is increasingly important given the declining conventional energy reserves and growing environmental concerns. This research developed a concept design to enhance sustainability in offshore operations by integrating local solar and wind energy sources. The proposed hybrid system combines solar energy systems and wind turbines with traditional Thermoelectric Generators (TEGs), which have traditionally relied on natural gas. The study found that incorporating these renewable energy sources into the system significantly reduces carbon emissions, lowers dependency on fossil fuels, and improves overall operational efficiency. The main conclusion of this research is that integrating local renewable energy sources into offshore operations mitigates environmental impact, offers long-term cost savings, and enhances energy security. This framework provides practical solutions for the energy sector's transition towards greener, more resilient offshore operations.
Optimizing Motorcycle Manufacturing Sustainability through the Integration of Waste Heat Recovery and Metal Scrap Recycling: A Process Engineering Approach Saiful, Rifki; Yandri, Erkata; Hilmi, Erik; Hamja, Nasrullah; Uhanto, Uhanto; Fitriani, Fitriani; Ibrahim, Riki Firmandha
Leuser Journal of Environmental Studies Vol. 2 No. 2 (2024): October 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v2i2.225

Abstract

The automotive industry manufacturing has experienced rapid growth 2–3 times by 2050, with motorcycles constituting around 30% of vehicles worldwide, but this increase in production has significantly heightened the demand for raw materials and energy. A major challenge arises in managing material waste and waste heat generated during the manufacturing process. This research aims to develop a framework that optimizes the synergy between material waste recycling and waste heat recovery to enhance the sustainability of the motorcycle industry, reduce waste, and lower energy consumption. The design leverages waste heat from the melting process to preheat raw materials, raising temperatures from around 50 °C to 350 °C before melting, thereby reducing additional energy needs, lowering emissions, and decreasing operational costs. Utilizing waste heat for preheating not only mitigates environmental impact and thermal load but also significantly improves energy efficiency, ultimately resulting in cost savings and optimized resource use. Utilizing waste heat directly for preheating raw materials has effectively lowered energy consumption by as much as 30%. This approach not only improves operational efficiency but also decreases production costs and minimizes environmental impact, offering a more sustainable solution for the manufacturing sector.
Developing a Smart Implementation Framework for Blockchain-Based P2P Renewable Energy Trading in Indonesia: A Qualitative Analysis Approach Ludji, Omrie; Yandri, Erkata; Sidharta, Rendy; Timba, Ayub; Amaral, Clizardo; Aryati, Ratna
Heca Journal of Applied Sciences Vol. 3 No. 1 (2025): March 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/hjas.v3i1.273

Abstract

The shift towards decentralized and sustainable energy frameworks is progressively propelled by innovations in technology and the imperative for energy democratization. Blockchain technology is a viable approach for facilitating peer-to-peer (P2P) energy trading, thereby diminishing dependence on intermediaries while augmenting transparency, security, and efficiency within energy transactions. Nevertheless, the application of blockchain-enabled energy trading continues to be constrained in Indonesia due to regulatory, technical, and economic challenges. This study aims to develop a smart implementation framework for integrating blockchain into P2P renewable energy trading in Indonesia. A qualitative research approach is employed, incorporating content analysis and thematic analysis of policy documents, technical reports, and stakeholder interviews. A blockchain simulation model is also designed to evaluate feasibility, efficiency, and scalability. The findings highlight that blockchain can significantly enhance renewable energy adoption by facilitating direct energy exchanges among prosumers, improving grid resilience, and reducing transaction costs. The proposed framework outlines essential components such as smart contracts, digital tokens, decentralized ledgers, and regulatory compliance mechanisms. Case studies from global implementations, including Power Ledger in Australia and LO3 Energy in the U.S., demonstrate the viability of blockchain-based energy trading. The study concludes that while blockchain has strong potential to transform Indonesia’s energy landscape, successful implementation requires supportive policies, infrastructure investment, and public awareness. Future research should focus on optimizing smart contracts and developing consensus mechanisms tailored to Indonesia’s regulatory and market conditions.
Sustainable Energy Integration in Geothermal Exploration: Conceptual Design and Innovation Sidharta, Rendy; Yandri, Erkata; Ludji, Omrie; Timba, Ayub; Amaral, Clizardo; Ariati, Ratna
Leuser Journal of Environmental Studies Vol. 3 No. 1 (2025): April 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v3i1.282

Abstract

Geothermal drilling operations in remote areas are commonly powered by diesel generators, leading to high fuel consumption and substantial carbon emissions. This study explores the integration of a hybrid solar PV–diesel generator system to enhance energy sustainability at a geothermal drilling base camp in Indonesia. The system design considers local renewable energy potential and incorporates integration with existing equipment. The integration strategy is evaluated through a feasibility analysis considering system efficiency, energy yield, and environmental impact. Using Helioscope software for solar simulation and load analysis based on equipment specifications, the results show that the PV system can supply up to 35% of the daytime energy demand, reducing daily carbon emissions by 8% and enhancing generator performance through optimized load sharing. Despite the absence of battery storage, the system demonstrates significant environmental and operational benefits, while also highlighting the potential for further improvements through energy storage integration, smart control systems, and targeted energy management.
A Energy Efficiency Strategy in Manufacturing Industry Through Implementation of Automation Technology Gede Arya Rachman; Rifki Saiful; Ratna Ariati; Syukri M. Nur; Erkata Yandri
JOURNAL OF MECHANICAL ENGINEERING MANUFACTURES MATERIALS AND ENERGY Vol. 9 No. 1 (2025): June 2025 Edition
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jmemme.v9i1.13998

Abstract

The implementation of automation technology in the manufacturing industry has become a critical solution in facing global energy efficiency challenges. Amid increasing demands for reduced energy consumption and carbon emissions, the manufacturing sector is required to adopt innovative solutions in their operations. This study aims to analyze and evaluate energy efficiency strategies through the application of automation technology in the manufacturing sector, with a focus on optimizing energy consumption and increasing productivity. The research methodology uses both quantitative and qualitative approaches, including analysis of historical energy consumption data from 50 manufacturing facilities that have implemented automation systems, in-depth interviews with industry experts, and comparative evaluation of various automation technologies available in the market. The results show that the implementation of automation technology can reduce energy consumption by an average of 27.5% in the first 12 months, with an increase in production efficiency by 35%. Further analysis reveals that automation systems based on the Internet of Things (IoT) and artificial intelligence provide optimal results in energy management, with an average return on investment of 2.3 years. The integration of smart sensors and automated control systems has proven to be effective in optimizing energy use in production processes, predictive maintenance, and peak load management. The study also identified key challenges in implementation, including high initial investment costs, personnel training needs, and the complexity of system integration. The study found that key factors for successful implementation include strategic planning, top management support, and a comprehensive training program. In conclusion, the application of automation technology in the manufacturing industry is an effective strategy to achieve long-term energy efficiency, with the potential for significant savings and increased industrial competitiveness.
Co-Authors Aep Saepul Uyun Aep Saepul Uyun Amaral, Clizardo Andy Tirta Ariati, Ratna Aryati, Ratna Bahri, Ridzky Aulia Bangun Novianto Candra, Arief Fitriani Fitriani Gede Arya Rachman Ghazi Mauer Idroes Hafit Isandono Hamja, Nasrullah Hilmi, Erik Ibrahim, Riki Firmandha Irvanizam, Irvanizam Kukuh Priyo Pramono Lala, Andi Lodewijk, Dewi Putriani Yogosara Ludji, Omrie Maria Paristiowati Maulana, Aga Mohamed Yusof, Nur Intan Saidaah Muhammad Syukri Nur Muhammad Yanis Muhammad Yusuf Murdiyansah, Novan Murdiyansyah, Novan Naoto Hagino Nizamuddin Nizamuddin Pramono, Kukuh Priyo Ratna Ariati Ratna Ariati Rifki Saiful Riki Firmandha Ibrahim Rinaldi Idroes Rizal F. Hariadi Saiful, Rifki Sasmita, Novi Reandy Satrio, Justinus Sidharta, Rendy Sihombing, Very Sparisoma Viridi Suhendra, Rivansyah Syukri Muhammad Nur Teuku Rizky Noviandy Timba, Ayub Uhanto, Uhanto Viendyasari, Mila Zahriah, Zahriah Zulkarnain Jalil