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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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Journal : Heca Journal of Applied Sciences

 1 
Cultivating Energy Conscious Communities: The Path to Increased Efficiency Lodewijk, Dewi Putriani Yogosara; Yandri, Erkata; Murdiyansah, Novan; Ariati, Ratna
Heca Journal of Applied Sciences Vol. 2 No. 1 (2024): March 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/hjas.v2i1.157

Abstract

This research addresses the critical need for increased energy efficiency in communities, emphasizing the pivotal role of community involvement and awareness. With the growing concern for sustainable energy practices, empowering communities to contribute to energy efficiency initiatives is imperative. Thus, the research aims to investigate and understand the role of community empowerment in increasing energy efficiency through community role and awareness. The theory applied to the research is the theory of planned behavior. A descriptive quantitative approach is employed, utilizing a structured questionnaire based on the Likert scale. Then, after the questionnaires were collected, statistical data processing was carried out using the T-test, F-test, and validity and reliability tests. The questionnaire gauges participants' perceptions and behaviors about energy efficiency, enabling a comprehensive analysis of the community's role and awareness in promoting sustainable energy practices. Preliminary findings indicate a positive correlation between community empowerment, heightened awareness, and increased energy efficiency. The Likert scale responses provide valuable insights into the areas where communities excel and areas that require targeted interventions. The data also reveal notable patterns in community behaviors and perceptions of energy consumption and conservation. In conclusion, the research underscores the significance of community empowerment as a catalyst for enhancing energy efficiency. The findings suggest that fostering community awareness and active involvement can lead to tangible improvements in sustainable energy practices. This study contributes valuable insights for policymakers, community leaders, and energy advocates seeking effective strategies to address the global energy challenge through localized, community-driven initiatives.
Predictive Maintenance with Machine Learning: A Comparative Analysis of Wind Turbines and PV Power Plants Uhanto, Uhanto; Yandri, Erkata; Hilmi, Erik; Saiful, Rifki; Hamja, Nasrullah
Heca Journal of Applied Sciences Vol. 2 No. 2 (2024): September 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/hjas.v2i2.219

Abstract

The transition to renewable energy requires innovations in new renewable energy sources, such as wind turbines and photovoltaic (PV) systems. Challenges arise in ensuring efficient and reliable performance in their operation and maintenance. Predictive maintenance using machine learning (PdM-ML) is relevant for addressing these challenges by enhancing failure predictions and reducing downtime. This study examines the effectiveness of PdM-ML in wind turbine and PV systems by analyzing operational data, performing data preprocessing, and developing machine learning models for each system. The results indicate that the model for wind turbines can predict failures in critical components such as gearboxes and blades with high accuracy. In contrast, the model for PV systems is effective in predicting efficiency declines in inverters and solar panels. Regarding operational complexity, each model has advantages and disadvantages of its own, but when compared to conventional maintenance techniques, both provide lower costs with greater operational efficiency. In conclusion, machine learning-based predictive maintenance is a promising solution for enhancing the reliability and efficiency of renewable energy systems.
Potential for Electrical Energy Savings in AC Systems by Utilizing Exhaust Heat from Outdoor Unit Hamja, Nasrullah; Yandri, Erkata; Hilmi, Erik; Uhanto, Uhanto; Saiful, Rifki
Heca Journal of Applied Sciences Vol. 2 No. 2 (2024): September 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/hjas.v2i2.223

Abstract

This study explores the potential of utilizing waste heat from air conditioning systems, one of the largest consumers of electrical energy. Currently, most of the waste heat generated by outdoor units is typically released into the environment without being utilized, leading to missed energy-saving opportunities. This study analyzes the potential for improving electrical energy efficiency in air conditioning (AC) systems by harnessing this waste heat. Two primary approaches are evaluated: the first is the use of waste heat for domestic water heating, and the second is the conversion of heat into electrical energy using thermoelectric generators (TEG). The results of this research indicate that both methods have the potential to improve overall energy efficiency significantly. However, challenges related to conversion efficiency and integration of these technologies with AC systems require further, more specific studies. These findings are expected to contribute to more efficient and environmentally friendly cooling systems by optimizing technology and overcoming barriers to wider implementation.
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.
Utilization Strategy of Discharged Seawater from Power Plant Cooling System to Reduce Energy Consumption: A Process Engineering Approach Amaral, Clizardo; Yandri, Erkata; Ludji, Omrie; Sidharta, Rendy; Timba, Ayub; Ariati, Ratna
Heca Journal of Applied Sciences Vol. 3 No. 2 (2025): September 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/hjas.v3i2.309

Abstract

Steam power plants are among the primary sources of electricity generation; however, they face significant challenges in terms of energy efficiency and environmental impact due to their high consumption of coal. Innovative strategies are required to reduce emissions and improve system efficiency. One potential approach is the reutilization of condenser cooling water to drive a hydropower turbine before being discharged into the sea. By harnessing the head and flow rate of this water, the kinetic energy from the waste stream can be converted into additional electricity. This study examines a process engineering approach to integrating a hydropower generation system with a steam power plant, encompassing technical analysis, energy efficiency, as well as economic and environmental impacts. Simulation results indicate that the system is capable of generating between 14.2 and 49.5 kW of power, depending on operating conditions and water availability. The electricity produced can be utilized for internal Steam power plant needs, such as cooling pumps and lighting, thereby reducing dependence on coal combustion. This strategy not only improves energy efficiency and reduces operational costs but also supports environmental conservation and the long-term sustainability of power plant operations.
Co-Authors Aep Saepul Uyun Amaral, Clizardo Ariati, Ratna Aryati, Ratna Bahri, Ridzky Aulia Bangun Novianto Candra, Arief Faizin, Muhammad Ihsan Nur Fitriani Fitriani Gede Arya Rachman Ghazi Mauer Idroes Hamja, Nasrullah Heriyanto, Hernawan Hilmi, Erik Ibrahim, Riki Firmandha Irvanizam, Irvanizam Isandono, Hafit 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 Riyanto, Andry Rizal F. Hariadi Saiful, Rifki Sasmita, Novi Reandy Satrio, Justinus Sidharta, Rendy Sihombing, Very Sparisoma Viridi Suhendra, Rivansyah Teuku Rizky Noviandy Timba, Ayub Tirta, Andy Uhanto, Uhanto Utami, Mei Budi Viendyasari, Mila Zahriah, Zahriah Zulkarnain Jalil