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ELKHA : Jurnal Teknik Elektro
Published by Universitas Tanjungpura
ISSN : 18581463     EISSN : 25806807     DOI : http://dx.doi.org/10.26418
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering
The ELKHA publishes high-quality scientific journals related to Electrical and Computer Engineering and is associated with FORTEI (Forum Pendidikan Tinggi Teknik Elektro Indonesia / Indonesian Electrical Engineering Higher Education Forum). The scope of this journal covers the theory development, design and applications on Automatic Control, Electronics, Power and Energy Systems, Telecommunication, Informatics, and Industrial Engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 285 Documents
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Analysis of Potential Fire Due to Short Current in Semi-permanent Buildings at Tinumbu Street in Aisle 148-149 Makassar City Rahmania, Rahmania; Adriani, Adriani; Rohana, Rohana
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.84748

Abstract

Fires can occur if several other factors are met  heat sources, flammable materials and oxygen. The biggest potential cause of fires in buildings is electricity. This research aims to prove whether electrical short circuits trigger fires in residential homes or semi-permanent buildings, especially in electrical installation equipment. This type of research is quantitative using experimental methods, which are descriptive analysis to determine the effect of a particular treatment on other treatments under controlled conditions, to find out for sure the main cause of the fire. This research show that the mothers' knowledge is quite limited regarding the use of household electricity and the tools used are old enough to cause short circuits. This is also triggered by the use of electrical installations that do not meet PUIL 2000 and SNI standards. Researchers need to provide education to residents, especially housewives, about the effectiveness of using electricity at different times of the day. An explanation of the load distribution system for electrical devices is a top priority in this education. In this education, various forms of explanation and direction are provided regarding the importance of saving energy during peak hours and the importance of knowing the use of energy-saving products (LED lights). With the program to use environmentally friendly and energy efficient household electricity, mothers' understanding of the concept of environmentally friendly PLN will be more developed and more efficient in terms of welfare and family comfort from various environmental threats due to electricity disturbances.
State of Charge Estimation on Lithium-Ion Batteries Using Particle Swarm Optimization Method Dewanto, Muhammad Ridho; Saputra, Riza Hadi; Sugiarto, Kharis; Saputra, Agung Adi
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.90020

Abstract

Lithium-ion battery management is crucial as their use grows in devices and electric vehicles. A key aspect is State of Charge (SoC) estimation, which indicates the battery's charge level at any given time. This research aims to develop a method that can provide accurate SoC estimates for Li-ion batteries using the Particle Swarm Optimization (PSO) method. In this research, a 12V 8.4 Ah Lithium-Ion battery was used as a test subject, utilizing a voltage sensor, ACS712 sensor, and LM35 temperature sensor to measure key parameters such as voltage, current, and temperature. The PSO approach was chosen because of its ability to find optimal solutions in complex search spaces, such as SoC estimation in batteries. Through a combination of the PSO algorithm and data generated from sensors, it is hoped that the SoC estimates produced can improve battery usage efficiency, extend service life, and increase the performance of systems that depend on batteries. PSO can provide more accurate predictions with smaller errors, both in terms of the RMSE value of 0.0391 and the MAPE value of 12.028%. The high accuracy of 87.972% of PSO also shows that this method is reliable for applications that require precise SoC predictions. It is hoped that the results of this research can become a basis for further research in the field of battery management and metaheuristic algorithm optimization. After all, this research aims to enhance battery management systems and deepen understanding of PSO-based SoC estimation.
Analysis of 3 kW Solar Power Plant Production Optimization by Improving Energy Production Efficiency Using 3d Pvsyst Simulation Method Fiqri, Teguh Mohammad; Yacoub, Redi Ratiandi; Kurnianto, Rudi; Rusman, Rusman; Hasan, Hasan
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.89864

Abstract

This study aims to analyze the effect of optimizing the position of solar panels on improving energy production efficiency in a 3 kW solar power plant (PLTS) system. The 3D PVsyst simulation method was used to model the system and predict performance before and after optimization. Simulation results indicate that repositioning the solar panels can increase energy production by 2% (from 0.99 kWh to 1.01 kWh). A comparison between simulation results and actual data shows reasonably good agreement, although some differences require further investigation. Discrepancies between simulation and actual data may be attributed to several factors, such as weather conditions, component efficiency, and other environmental factors. This study concludes that optimizing the position of solar panels is an effective step to enhance the performance of PLTS systems. However, further research is needed to consider additional factors affecting system performance and to develop more accurate simulation models
Analysis of Photovoltaic Panel Performance Integrated with the Grid in a Load-Sharing Scheme Aditya, Agellio Farras; Ulinuha, Agus
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.91191

Abstract

This paper examines the performance of photovoltaic panels integrated into the electrical grid in a load-sharing scheme at Darool Ehsan Muhammadiyah Senior High School, Sragen. The study is part of Universitas Muhammadiyah Surakarta's community service program focused on renewable energy development in educational environments. Unlike previous studies relying on simulated data, this research uses real-time primary data from direct measurements of photovoltaic power production and grid electricity consumption over a specific period. The study’s innovation lies in analyzing the photovoltaic system within a tropical climate-based load-sharing scheme and comparing energy usage when connected to photovoltaic panels versus when disconnected. It also evaluates the impact of reducing solar energy consumption from the grid. The collected data reveal an estimated daily load of 49.89 kWh, with PLN-supplied energy consistently exceeding inverter-supplied energy. Integration of photovoltaic panels into the grid reduces PLN electricity consumption by up to 30% during optimal sunlight periods, achieving an average system efficiency of 15%. This research offers valuable insights into the potential and challenges of implementing photovoltaic panels in educational settings, emphasizing the importance of climate considerations in system design and optimization. Future studies will focus on techno-economic evaluations of solar power installations and harmonic distortion (THD) analysis for larger-scale implementations.
Wireless Sensor Sub-Network Based IoT System for Probiotic Dosing and Water Quality Management Using Artificial Neural Network Junfithrana, Anggy Pradiftha; Suryana, Anang; Saputri, Utamy Sukmayu
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.96914

Abstract

Water quality management in aquaculture plays a crucial role in maintaining fish health and optimizing growth, particularly in intensive tilapia farming. This study develops a Wireless Sensor Sub-Network (WSSN) based Internet of Things (IoT) system designed to automate probiotic dosing and monitor water quality conditions using real-time sensor feedback and Artificial Neural Network (ANN) analysis. Utilizing TCS3200 color sensors, flow sensors, and an ANN within a WSSN, the system autonomously manages probiotic delivery based on real-time water color analysis, marking a shift towards intelligent water-quality management in aquaculture. The system architecture consists of three primary sensing and control components: a flow sensor connected to an ESP32 microcontroller to measure the precise volume (in milliliters) of probiotic solution dispensed; a TCS3200 color sensor, also integrated with an ESP32 module, to detect variations in water color as an indicator of pond health; and a solenoid valve controlled through a relay-actuated ESP32 node to regulate probiotic release into the pond. The sensor network operates wirelessly to provide continuous monitoring and intelligent decision-making. The ANN employs the backpropagation algorithm to perform color-based classification, where light green indicates a healthy condition, dark green represents normal stability, light brown signals the need for probiotic dosing, and dark brown denotes a critical condition requiring water replacement. This integration of optical and flow sensing with neural network computation provides an intelligent, non-invasive, and adaptive mechanism for probiotic management in tilapia aquaculture, supporting sustainable aquaculture practices and improving operational efficiency through automation and predictive learning.

Page 29 of 29 | Total Record : 285

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