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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) Teknika INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Syntax Literate: Jurnal Ilmiah Indonesia Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control KACANEGARA Jurnal Pengabdian pada Masyarakat Buletin Ilmiah Sarjana Teknik Elektro JE-Unisla Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Engineering and Technology (INAJET) INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) IJORER : International Journal of Recent Educational Research Jurnal Teknik Elektro (JTE) PROFICIO: Jurnal Pengabdian Masyarakat Indonesian Journal of Multidiciplinary Research (IJoMR) Abimanyu: Journal of Community Engagement Tarbiyah Wa Ta'lim: Jurnal Penelitian Pendidikan dan Pembelajaran Jurnal Sains dan Teknologi Jurnal Elektronika dan Teknik Informatika Terapan IT-Edu: Jurnal Information Technology and Education
Unit Three Kartini
Universitas Negeri Surabaya
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

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Design of an IoT-Based Automatic Switching and Monitoring System for Hybrid Power Plants Aguska, Anggi; Haryudo, Subuh Isnur; Kartini, Unit Three; Rohman, Miftahur
invotek Vol 24 No 1 (2024): INVOTEK: Jurnal Inovasi Vokasional dan Teknologi
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/invotek.v24i1.1179

Abstract

Hybrid power generation, a power plant that combines two or more plants, continues to grow along with technological advances. The performance of these power plants relies heavily on effective switching and monitoring systems. Monitoring data is critical in maintenance scheduling, preventive intervention, and the timely identification and assessment of environmental changes. One of the switching and monitoring technologies integrated with the Internet is the Internet of Things (IoT) technology. This study introduces a system design capable of wirelessly performing switching operations and transmitting real-time data to a hybrid power plant monitoring system through an application. Test results demonstrate that the system successfully executes automatic switching between the hybrid power plant and the PLN electricity grid based on accumulator voltage thresholds. The monitoring data analysis reveals MAPE values of 2.959% and 3.577% for the voltage and current of the hybrid power plant, and a MAPE of 1% for the accumulator voltage. The voltage and load current readings also exhibit MAPEs of 0.604% and 8.625%. Based on the test results, it can be concluded that this device shows the ability of the system to automate the switching of resources to the load and monitor the hybrid power plant very well, with the smallest MAPE value achieved of 0.604%.
PEMANFAATAN PUBLISH OR PERISH DAN CHAT GPT UNTUK GURU SMK KETINTANG DALAM PENINGKATAN PENULISAN REFERENSI JURNAL Baskoro, Farid; I Gusti Putu Asto; Ismet Basuki; Unit Three Kartini; Ibrohim; Rifqi Firmansyah
Jurnal Pengabdian Masyarakat FKIP UTP Vol 7 No 1 (2026): PROFICIO : Jurnal Abdimas FKIP UTP
Publisher : FKIP UNIVERSITAS TUNAS PEMBANGUNAN SURAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36728/jpf.v7i1.5586

Abstract

Penelitian ini bertujuan untuk meningkatkan keterampilan penulisan referensi jurnal bagi guru SMK Ketintang Surabaya dengan memanfaatkan teknologi Publish or Perish dan Chat GPT. Kegiatan Pengabdian Kepada Masyarakat (PKM) yang dilakukan meliputi survei awal untuk mengidentifikasi kebutuhan peserta, pelatihan penggunaan teknologi untuk pencarian dan penyusunan referensi, serta sesi tanya jawab dan diskusi untuk memperdalam pemahaman. Hasil pelatihan menunjukkan peningkatan yang signifikan dalam berbagai aspek keterampilan. Sebelum pelatihan, pemahaman peserta tentang cara mencari referensi jurnal hanya mencapai 40%, namun setelah pelatihan meningkat menjadi 85%. Kemampuan menggunakan Publish or Perish dan menyusun referensi sesuai format sitasi juga meningkat dari 25% menjadi 80% dan dari 35% menjadi 90%, berturut-turut. Kepercayaan diri peserta dalam menulis referensi jurnal meningkat dari 30% menjadi 85%, serta keterampilan menggunakan Chat GPT untuk mengedit referensi meningkat dari 20% menjadi 75%. Hasil ini menunjukkan bahwa pelatihan berhasil mencapai tujuannya dan memberikan dampak positif dalam meningkatkan kualitas penulisan referensi jurnal bagi guru. Penggunaan teknologi dalam pendidikan terbukti efektif untuk mendukung pengembangan profesional guru dan meningkatkan kualitas pengajaran serta penelitian di lingkungan pendidikan.
PORTABLE SOLAR CELL SEBAGAI SUMBER ENERGI PERALATAN ELEKTRIK DAN PENERANGAN DI KECAMATAN KOKOP MADURA Nurhayati, Nurhayati; Mohammad As'ad Rosyadi; Unit Three Kartini; Akbar Izulhaq
Jurnal Pengabdian Masyarakat FKIP UTP Vol 7 No 1 (2026): PROFICIO : Jurnal Abdimas FKIP UTP
Publisher : FKIP UNIVERSITAS TUNAS PEMBANGUNAN SURAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36728/jpf.v7i1.5646

Abstract

Pembangkit Listrik Tenaga Surya (PLTS) merupakan energi terbarukan yang ramah lingkungan dengan memanfaatkan energi alam yaitu sinar matahari sebagai sumber utama, sumber energi matahari juga dapat digunakan untuk mengatasi krisis energi yang ramah lingkungan, mengurangi pemanasan global (global warming) dan pencemaran udara. PLTS bekerja berdasarkan energi matahari akan diubah menjadi energi listrik dengan memanfaat panel surya atau solar cell. Tujuan dari kegiatan PKM ini dengan melakukan perancangan dan membuat suatu perangkat portable PLTS untuk masyarakat (dalam lingkup umum) yang berkativitas dan bekerja diluar rumah yang tidak terjangkau energi listrik. Solar cell yang digunakan berjenis polycristaline, dilengkapi SCC, baterai, satu unit box panel. Perlu juga adanya pemantauan tegangan dan arus guna memudahkan pada saat proses perawatan, perancangan alat monitoring arus dan tegangan menggunakan microcontroller arduino uno dengan pembacaan sensor. Hasil penelitian ini diharapkan dapat meningkatkan produktivitas pertanian melalui pembuatan portable solar cell yang dapat digunakan untuk sumber energi pompa untuk mengairi sawah, penerangan maupun penggerak peralatan elektrik lainnya. Dengan demikian, teknologi yang dikembangkan dapat berkontribusi dalam menciptakan sistem yang lebih ramah lingkungan, berkelanjutan, dan efisien yang dapat membantu masyarakat Kokop.
Electrical System Design for High Rise Building Based on Reliability Index Juhan Andi Praseto Aji; Bambang Suprianto; Unit Three Kartini
INSOLOGI: Jurnal Sains dan Teknologi Vol. 5 No. 1 (2026): Februari 2026
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55123/insologi.v5i1.7506

Abstract

The research discusses the evaluation of electrical systems in multi-storey buildings, including analysis of compliance with PUIL 2011 standards and integration of Faraday Cage-based lightning protection systems. This study focuses on the Pasar Baru Bandung Building, with the aim of assessing the efficiency and safety of the electrical system used. The research method is carried out through the stages of field observation, data collection, and data processing. Observations were made to identify electrical equipment and assess the feasibility of its use. Data collection includes load capacity and single line diagrams, which are then processed to determine the value of Strong Current Conductivity (KHA) and Drop Voltage. The results of data processing were compared with existing data and analysed based on applicable standards. The results show that the power distribution system in Pasar Baru Bandung Building has been designed with high efficiency, with organised power distribution through main panels and sub-panels. The electrical protection evaluation shows that the grounding and earthing system has met the safety standards to prevent electrical faults. In addition, lightning protection analysis with the Rolling Sphere method ensures that the building's protection against lightning strikes is at an optimal level. The benefit of this study is the comprehensive examination of the electrical system, considering power distribution, protection, and energy efficiency. Despite challenges like inaccuracies in voltage drop measurement due to factors like environmental conditions and equipment age, the research still has a significant impact on improving the safety and efficiency of electrical systems in tall buildings.
Prediksi Jangka Sangat Pendek Daya Keluaran PLTS Menggunakan LSTM Berbasis Sky Clearness Index Muhammad Miftahul Rizqi; Unit Three Kartini; Lusia Rakhmawati; Joko
JURNAL TEKNIK ELEKTRO Vol. 15 No. 1 (2026): JANUARI 2026
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jte.v15n1.p38-45

Abstract

Pembangkit Listrik Tenaga Surya (PLTS) merupakan salah satu sumber energi terbarukan yang potensial di Indonesia, namun daya keluarannya sangat dipengaruhi oleh kondisi atmosfer yang bersifat fluktuatif. Penelitian ini bertujuan mengembangkan model prediksi jangka sangat pendek daya keluaran PLTS menggunakan metode Long Short-Term Memory (LSTM) berbasis Sky Clearness Index (SCI). Data penelitian berupa tegangan, arus, dan SCI dikumpulkan dari sistem PLTS Universitas Negeri Surabaya dengan interval 5 menit selama periode Mei–Juni 2025. Model LSTM dirancang dengan dua lapisan tersembunyi, Adam Optimizer, dan fungsi loss Mean Squared Error (MSE). Dataset dibagi menjadi 80% data latih dan 20% data uji. Evaluasi kinerja model dilakukan menggunakan Root Mean Square Error (RMSE), Mean Absolute Error (MAE), dan Mean Absolute Percentage Error (MAPE). Hasil penelitian menunjukkan bahwa model LSTM berbasis SCI mampu memprediksi daya keluaran PLTS dengan akurasi tinggi, dengan nilai RMSE sebesar 0,644, MAE sebesar 0,536, dan MAPE sebesar 3,66%. Nilai MAPE di bawah 10% menunjukkan performa prediksi yang sangat baik untuk peramalan jangka sangat pendek. Dengan demikian, integrasi SCI sebagai variabel input terbukti efektif dalam meningkatkan keandalan prediksi daya keluaran PLTS secara real-time.
Predictive Modeling of Electricity Load Demand Forecasting Using the CNN-BiLSTM method based on Peak Load in Household Sector Consumers Arrahmad Budiarto; 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.p41-47

Abstract

Accurate short-term electricity load forecasting is essential for ensuring reliable energymanagement and maintaining power system stability, particularly in the household sector whereelectricity consumption exhibits highly dynamic and nonlinear patterns. Conventional forecastingmethods often have limited capability in capturing these complex temporal characteristics.Therefore, this study proposes a hybrid Convolutional Neural Network–Bidirectional Long ShortTerm Memory (CNN-BiLSTM) model to forecast 24-hour ahead household electricity demand basedon peak load data collected from Mojowarno District, Jombang Regency, Indonesia. The datasetconsists of hourly electricity consumption records from January 2024 to January 2025 and waspreprocessed through smoothing, outlier handling, and normalization before model training. Theproposed model combines CNN for automatic spatial feature extraction and BiLSTM for learningbidirectional temporal dependencies. Experimental results demonstrate excellent forecastingperformance with a Test Loss of 0.0024, Test MAE of 0.0562, Test RMSE of 0.0699, MAE of 3.4146kW, RMSE of 4.2470 kW, and an R² value of 0.9889. These findings indicate that the proposed CNNBiLSTM model effectively captures household electricity consumption patterns and providesaccurate short-term peak load forecasting, making it a promising approach for supporting energymanagement and electricity distribution planning
Optimization of Seal Steam Turbine Pressure Control on CCPP Boiler System Using Fuzzy-PID Auto-Tuning Method Muhammad Barkah; Bambang Suprianto; 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.p48-55

Abstract

This study optimizes the High-Pressure to Turbine Seal Steam Pressure Control Valve system in a Combined Cycle Power Plant to address nonlinear characteristics and fluctuating load dynamics. Conventional fixed-gain controllers structurally fail to manage these conditions effectively. We propose a hybrid Relay Feedback with Fuzzy-PID strategy, employing a quantitative simulation design validated with industrial data from the Muara Tawar CCPP. Using a First Order Plus Dead Time model, the method integrates Relay Feedback for initial parameter identification and Fuzzy Logic for real-time PID adjustment. Evaluated via MATLAB/Simulink across various scenarios, the hybrid approach yielded superior transient performance, outperforming metaheuristic benchmarks (Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO)) in stabilizing the system. Crucially, validation against real operational data demonstrated that the proposed method eliminated oscillatory valve behavior, yielding a massive improvement in actuator energy efficiency and significantly reducing the Root Mean Square Error (RMSE). The novelty lies in integrating Relay Feedback autotuning with Fuzzy self-tuning PID, explicitly validated using real operational data. This practical approach provides robust control and extends actuator lifespan by mitigating mechanical wear.
Maximization Very Short-Term Forecasting of Power Photovoltaic System Using Machine Learning Based on Clearness Index Model Unit Three Kartini; L. Endah Cahya Ningrum; M. Nur Adiwana
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 3 (2026): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i3.16181

Abstract

The hybrid model for very short-term photovoltaic (PV) power forecasting, covering one hour ahead with 20-minute intervals, combines the k-nearest neighbour (k-NN) and multilayer backpropagation neural network (BP-NN) methods. The uniqueness of this model lies in integrating meteorological and the clarity index. the data preprocessing stage, the k-NN method is applied, while the multilayer BP-NN is used for forecasting. The k-NN Multilayer BP-NN algorithm calculates the nearest data points using Euclidean distance, and then processes the training and testing data through the multilayer BP-NN to generate PV power predictions. The simulation dataset was divided into 70% training data and 30% testing data, with a maximum PV power output of 611 W. The error statistical indicators of machine learning using k-NN-BP-NN model RMSE 27.44 W and MSE 1.5 W. These superior results are attributed to more stable weather patterns and consistent solar radiation. The simulation validity test demonstrated that the k-NN Multilayer BP-NN algorithm achieved better accuracy compared to the k-NN decomposition method. In addition, the model offers high computational efficiency and short inference time, making it highly suitable for real-time PV power forecasting systems.
Dingo optimization algorithm for designing power system stabilizer Widi Aribowo; Bambang Suprianto; Unit Three Kartini; Aditya Prapanca
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp1-7

Abstract

The dingo optimization algorithm (DOA) adopts the social life of dingo dogs. The dingo is a breed of ancient dog originating from Australia. Dingo hunting strategies such as assault with persecution, flocking, and scavenging behavior became the inspiration for DOA. In this paper, DOA is applied to a power system stabilizer (PSS) to dampen low-frequency oscillations (LFO) in a single-machine infinite bus (SMIB). DOA is used to obtain optimal parameters for PSS. The damping controller is designed for optimal lead-lag control. To obtain the performance of the DOA method, the results were compared with the uncontrolled method, conventional PSS, Whale optimization algorithm (WOA), and grasshopper optimization algorithm (GOA). Simulation using MATLAB with three different operating conditions, namely light load (20%), medium load (50%) and high load (100%). From the simulation using MATLAB with SMIB modeling, it was found that the application of the DOA method on PSS has the ability to reduce the average undershoot value by 28.16% and reduce the average undershoot value to 65.57% compared to the conventional PSS method.
Integrating Meteorological and PV Data for Short-Term Solar Irradiance Forecasting Using BPNN Ahmad Rizal Agustian; Unit Three Kartini; Muhammad Miftahul Rizqi; Sa'adatud Daroini
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2449

Abstract

Solar power plants are highly dependent on solar radiation intensity, which fluctuates due to changes in atmospheric conditions. To maintain system stability and efficiency, an accurate short-term solar radiation prediction model is essential. This study developed a model for forecasting global solar radiation one hour ahead using the Backpropagation Neural Network (BPNN) method. The dataset was obtained from a photovoltaic (PV) system at Building A8 of Surabaya State University, recorded over four days (June 14-17, 2025) at two-minute intervals. Five input variables were used: clearness index, solar radiation, air temperature, air humidity, and PV output power, resulting in a total of 3,020 data samples. The model was trained through a trial-and-error process by varying the number of neurons, hidden layers, and epochs to determine the optimal configuration. The forecast capability of the model was assessed through four statistical indicators: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The best performance was achieved with a network architecture of 15 input neurons representing input variables resulting from data transformation using the sliding window method, one hidden with 25 neurons, and a single unit in the output layer trained for 2000 epochs, resulting in R2 = 0.98, MAPE = 5.89%, and MSE = 0.00027. The novelty of this research lies in the integration of meteorological data with actual PV power output as model input, enabling the network to capture more realistic nonlinear temporal relationships. The proposed short-term forecasting model provides a practical approach to predicting solar radiation based on historical data and can support efficient energy management and photovoltaic system performance analysis.
Co-Authors Achmad Imam Agung Achmad Imam Agung Adam Maulana Adi Reski Ariangga Aditama, Maulana Rizki Aditya Prapanca Aguska, Anggi Ahmad Rizal Agustian Akbar Izulhaq Akbar Tahir Kalbii Amarulloh, Ilham Anjar Novian Arrahmad Budiarto Asto, I Gusti Putu At - Thariq Ramadhan Ayusta Lukita Wardani Bambang Suprianto . Budiarta, Mohammad Erwin Chatarina Umbul Wahyuni DEDDY PUTRA ARDYANSYAH DWI ARDIANTO Dwikky Sucahyo Putra DZIKRI MUHAJIR EL FAHMI Edy Sulistiyo EKA PRASETYO HIDAYAT Endryansyah Endryansyah Farid Baskoro Fendi Achmad Feri Rohman Syah Ghifari Fikri Yuviyanto Habbib Rakhasiwi Aminulloh Hapsari Peni Hernanda Setiawan I Gusti Putu Asto I Gusti Putu Asto Buditjahjanto Ibrohim Ibrohim Ichwan Dwi Wahyu Hermanto Ilham Amarulloh Ilham Cahyo Wibowo Aji Ilham Farisi Almadani Indra Iskandar Ismet Basuki Joko . Joko Joko Juhan Andi Praseto Aji Kevin Pranata Putra Khoirul Fadli Krisna Taufik Brilliansyah Kristanto, Andika Wisnu Adam Kukuh Eko Purwantoro L. Endah Cahya Ningrum Lailil Ika Wardani Lilik Anifah Lusia Rakhmawati M. Nanda Tri Maulana Ridwan M. Nur Adiwana M. Yusuf Isbakhtiar Yusuf Mahendra Widyartono Mardika Wahyu Kristanto MASVIKI AGAM Mirza Wahyu Purnama MOCH. NUR ADIWANA Mochammad Iqbal Firmansyah Mohammad As'ad Rosyadi Muhammad Barkah Muhammad Fathoni Muhammad Helmy Anjab Muhammad Miftahul Rizqi Muhammad Mujiburrahman Muhammad Rizka Ardiansyah Muhammad, Yasyfin Nur Mulya Adi Prasetiya Nining Widyah Kusnanik Nofianto Sugiarto Novian Zainun Qorif Putera Nur Kholis Nurhayati Nurhayati Nurwijayanti Pamungkas, Ivan Fahrezi Puguh Ady Mahendra Puput Wanarti Rusimamto Putra Adi Wicaksono Putri, Tiris Mega Raden Mohamad Herdian Bhakti Rani Fajriyah Islamiyati Asfah Rifqi Firmansyah Rizqi Rizal Dharmawan Roesita Dekakovi Tauba Setyawan Rois Alfikri RR. Ella Evrita Hestiandari S. Suparji Sa'adatud Daroini Saifudin Saifudin Saputra, Ramadhan Dwi Sari Cahyaningtias Septian, Bahrul Anas Subuh Isnur Haryudo Syamsul Muarif Tedy Muhammadhy Tjahyaningtijas, Raden Roro Hapsari Peni Agustin Tri Rijanto Tri Wrahatnolo Tulende, James ULIN NIKMATUL CHOIROH W. Wasis Wahyu Tri Handoko WELBI RENALDI SUKRISNA widi . aribowo widi aribowo Widi Aribowo Widi Ariwibowo Wildan Arif Billahi WRAHATNOLO, TRI Yanuarius Kristian Wibisono Yuli Sutoto Nugroho Yusuf Rony Rony