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Nurhayati
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Departement of Electrical Engineering Faculty of Engineering Universitas Negeri Surabaya
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INDONESIA
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering)
Published by Universitas Negeri Surabaya
ISSN : -     EISSN : 26142589     DOI : 10.26740/inajeee
Core Subject : Science, Engineering,
Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering
INAJEEE or Indonesian Journal of Electrical and Eletronics Engineering (E-ISSN 2614-2589) is a scientific peer-reviewed journal issued by The Department of Electronics, Faculty of Engineering, Universitas Negeri Surabaya (UNESA). Accepted articles will be published online and the article can be downloaded for free (free of charge). INAJEEE is published periodically (2 issues per volume/year) with 5 articles each time published (10 articles per year). INAJEEE is free (open source) all to access and download. The journal includes developments and research in the field of Electronic Engineering, both theoretical studies, experiments, and applications, including: 1. Electronics Engineering 2. Power system Engineering 3. Telematics 4. Control System Engineering
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 165 Documents
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Remaining Useful Life Estimation of Fouled HVAC Condensers via a Physics-Constrained Temporal Convolutional Network with SHAP Interpretation Dandy Risfanto Huri; Lusia Rakhmawati; Rifqi Firmansyah
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol. 9 No. 1 (2026): Februari
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajeee.v9n1.p36-40

Abstract

The condenser is one of the most fouling-prone parts of an HVAC system, and as deposits build up the compressor draws more power while efficiency falls. Predictive maintenance tries to catch this decline early, but it needs a dependable estimate of how much useful life the component has left. As a preliminary, simulation-based feasibility study, this work examines whether an explainable and physically consistent model can supply that estimate for an air-cooled condenser. Using the asymptotic Kern-Seaton model, a degradation dataset covering one complete fouling cycle (180 days sampled every minute) was generated, and from it six thermal and electrical features were derived and checked against the underlying physics. A Temporal Convolutional Network (TCN) was then trained with a physics-informed penalty that prevents the predicted life from rising over time, and SHapley Additive exPlanations (SHAP) were used to expose the reasoning behind each prediction. On a quartile-stratified test set the unconstrained TCN obtained a mean absolute error of 2.63 days and an R2 of 0.994, against 3.43 days for an LSTM baseline. Adding the physics penalty raised the error only slightly, to 2.88 days, while cutting non-monotonic predictions, a deliberate trade-off of a small amount of pointwise accuracy for physically consistent RUL trajectories. SHAP ranked the approach temperature as the most influential feature, which matches the way fouling degrades heat transfer. The predicted RUL and a derived Health Index were finally translated into a four-level maintenance decision scheme. The results indicate that the framework is promising; validation on real sensor data is the necessary next step.
Solving the Reactive Power Dispatch Optimization for Large Scale System Nungky Ibrahim; Tri Wrahatnolo; Rifqi Firmansyah
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol. 9 No. 2 (2026): August
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajeee.v9n2.p56-70

Abstract

Reactive power dispatch (RPD) is a crucial optimization task in power system operation because it seeks the optimal settings of control variables, such as generator voltages, transformer tap positions, and shunt VAR compensators, to reduce active power loss while satisfying operating constraints [file:1]. This study investigates the application of the fmincon solver and particle swarm optimization (PSO) to the RPD problem on three benchmark IEEE test systems, namely the 30-bus, 57-bus, and 118-bus networks [file:1]. For the IEEE 30-bus system, the minimum active power loss obtained by fmincon and PSO was 4.5480 MW and 4.4858 MW, respectively, corresponding to loss reductions of 21.88% and 22.95% from the initial value of 5.8223 MW [file:1]. For the IEEE 57-bus system, the power loss was reduced from 0.2846 p.u. to 0.2473 p.u. by fmincon and to 0.2362 p.u. by PSO, equivalent to reductions of 13.11% and 17.01%, respectively [file:1]. These results show that both methods are effective for large-scale RPD optimization, while PSO generally provides the best performance among the compared techniques in terms of active power loss minimization. The contribution of this study lies in providing a focused comparison between a deterministic nonlinear programming solver and a population-based metaheuristic approach across different system sizes, thereby demonstrating their practical suitability for large-scale reactive power optimization
Monitoring and Analysis of Induction Motor Behavior Using Haiwell Cloud SCADA with Tension Control Method Hanif Rifai Adha; Daeng Rahmatullah; Danang Arengga W
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol. 9 No. 2 (2026): August
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajeee.v9n2.p79-83

Abstract

In the modern industrial sector, monitoring the condition of induction motors is the main key to maintaining efficiency and reliability. Internet of Things (IoT) technology in the monitoring system can be done in real-time, to provide convenience in monitoring induction performance. Haiwell Cloud SCADA-based monitoring system to analyze the behavior of induction motors in real-time voltage, current, speed, frequency, and temperature. This system integrates a tension control method using a magnetic powder brake to simulate changes in the load dynamically. The results show that at a low torque of 0 – 6 Nm, the induction motor operates stably at a speed close to synchronous with a low stator current. However, at torques above 8 Nm, there is a significant voltage drop, and the stator current increases four times compared to the nominal current, and there is a temperature increase of up to 35oC, which represents an increase in power losses. This research offers a combination of IoT-based monitoring and tension control methods. IoT-based monitoring systems help users easily monitor the performance of induction motors in real-time and anticipate potential problems before failures occur.
A MAINTENANCE SCHEDULING OF SPIRAL PIPE MILL MACHINES BASED ON CORRECTIVE MAINTENANCE DATA USING THE RANDOM FOREST MODEL Nashyh Ulvan Alghany; Unit Three Kartini
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol. 9 No. 2 (2026): August
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajeee.v9n2.p71-78

Abstract

The Spiral pipe mill machine is a vital asset in the steel pipe manufacturing industry that often experiences downtime due to maintenance strategies that are still reactive or corrective maintenance. This approach leads to operational uncertainty and high repair costs. This study aims to create a maintenance schedule for the spiral pipe mill machine using a random forest machine learning algorithm model. This research analyzes 168 historical machine failure data points from January to December 2024 to calculate machine failure intervals. The model was trained using 500 decision trees with an 80% training data and 20% testing data split. Evaluation results show precise model performance with an R-Squared (R²) value of 0.9916, Mean Absolute Percentage Error (MAPE) of 1.84%, and Mean Absolute Error (MAE) of 0.3993 days. Based on these calculations, an annual maintenance schedule can be compiled to provide accurate maintenance time recommendations to minimize sudden machine failures and increase production efficiency.
Soil Moisture and pH Monitoring System with a Flexible Monopole Antenna Based on IoT for Agricultural Applications Akbar Izulhaq Izulhaq; Nurhayati; Hesti Khuzaimah Nurul Yusufiyah; Sayyidul Aulia Alamsyah
INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Vol. 9 No. 2 (2026): August
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/inajeee.v9n2.p84-90

Abstract

This study aims to address the limitations of manual monitoring in the agricultural sector by designing an Internet of Things (IoT)- based soil moisture and pH monitoring system. The primary focus of this study is the integration of a flexible monopole antenna made of Polydimethylsiloxane (PDMS) to extend the range of data transmission on the ESP32 Wroom-U microcontroller. Using the Research and Development (R&D) method, the antenna was designed for a 2.4 GHz frequency, with simulation results showing a return loss of -14.69 dB and a VSWR of 1.45. Field test results prove that the use of a flexible external antenna can increase transmission range up to 521.59 meters, or 17 times farther than a standard antenna. The IoT system successfully transmitted sensor data to the ThingSpeak platform in real-time every 15 to 30 seconds with stable connectivity. Implementation in rice fields demonstrated the system’s accuracy in reading soil conditions and its effectiveness in operating automatic irrigation pumps. This research provides an efficient and adaptive communication infrastructure solution for the development of smart farming.

Page 17 of 17 | Total Record : 165

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