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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Simetris TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Teknosains EMITTER International Journal of Engineering Technology SUSTINERE: Journal of Environment and Sustainability JPP IPTEK (Jurnal Pengabdian dan Penerapan IPTEK) Celebes Education Review Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Engineering and Technology (INAJET) INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Elektro (JTE) Jurnal Pendidikan Teknik Elektro ELPOSYS: Jurnal Sistem Kelistrikan Journal of Electrical Engineering Vokasi UNESA Bulletin of Engineering, Technology and Applied Science JURNAL LINTAS KARSA Jurnal Elektronika dan Telekomunikasi
Widi Aribowo
Universitas Negeri Surabaya
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Transportation Other

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Dingo optimization algorithm for designing power system stabilizer Aribowo, Widi; Suprianto, Bambang; Three Kartini, Unit; Prapanca, Aditya
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.
K-Nearest Neighbors for Smart Solution Transportation: Prediction Distance Travel and Optimization of Fuel Usage and Charging Recommendations for ICE Vehicles Based in Surabaya Baskoro, Farid; Aribowo, Widi; Shehadeh, Hisham; Zangana, Hewa Majeed; Putro, Wahyu Sasongko; Dwiyanti, Sri; Nurdiansyah, Aristyawan Putra
Buletin Ilmiah Sarjana Teknik Elektro Vol. 8 No. 2 (2026): April
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v8i2.15068

Abstract

Surabaya ranks 9th in Southeast Asia and 44th globally in the TomTom Traffic Index, with an average travel time of ±22 minutes for a 10 km distance, longer than Jakarta’s ±20 minutes. Given these traffic conditions, this study examines the application of the K-Nearest Neighbors (KNN) algorithm to predict vehicle travel distance based on remaining fuel consumption and provides recommendations for the nearest Gas Station (SPBU) based on the predicted distance. The study seeks to provide accurate distance predictions and recommend the nearest Gas Station (SPBU) for users based on fuel consumption and the predicted route, helping to navigate Surabaya’s congested traffic efficiently. The data used includes various levels of fuel consumption: 0.02, 0.06, 0.10, 0.14, 0.16, 0.20, and 0.24 liters for engines of 110, 125, and 150 cc. The model evaluation results, using three metrics: MAE, MAPE, and RMSE show that KNN performs excellently at low fuel consumption levels. At a consumption rate of 0.02 liters, the model produces a low MAE of 0.347, MAPE of 31.21%, and RMSE of 0.40, indicating minimal prediction error. The model's performance remains consistent at a consumption of 0.06 liters with MAE of 0.330, MAPE of 9.90%, and RMSE of 0.41, demonstrating a high level of accuracy. Technically, the implementation of this model can help reduce traffic congestion by directing vehicles to the nearest gas stations, thereby minimizing sudden stops on the road, improving traffic flow, and reduce wasted time spent searching for distant gas stations.
Motorcycle Parking Availability Monitoring Using YOLOv5 and Mobile-Based Systems Wibisono, R. Endro; Susanti, Anita; Haratama, Kusuma Refa; Aribowo, Widi; Ariyanti, Karin Nur Fitria; Oliva, Diego; Shehadeh, Hisham A.; Umar, Abubakar
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.v8i3.16087

Abstract

The increasing number of motorcycles in developing countries has intensified parking management challenges, particularly in high-density environments with irregular vehicle arrangements. This study proposes a motorcycle parking availability detection system using the YOLOv5 object detection algorithm to address limitations of conventional parking methods. The research contribution is the development of a context-aware detection framework using a locally collected dataset and the evaluation of its performance under real-world parking conditions.The dataset consists of 1,200 images collected from campus parking areas and is divided into training, validation, and testing sets. The images were annotated into occupied and vacant classes and trained using YOLOv5 with 100 epochs. Model performance was evaluated using precision, recall, F1-score, and mean Average Precision (mAP@0.5) on a held-out test set.The results show that the model achieves an F1-score of 0.57 and mAP@0.5 of 0.566, indicating moderate detection performance in dense and occluded environments. Although a precision of 1.00 is obtained at a confidence threshold of 0.978, this condition significantly reduces recall, highlighting a trade-off between detection accuracy and coverage. The confusion matrix and recall–confidence analysis reveal that errors are primarily caused by occlusion, shadow effects, and background interference. Compared to previous studies focusing on car parking detection, this system demonstrates comparable performance while addressing the unique complexity of motorcycle parking. However, the relatively small dataset size and environmental variability limit generalization.In conclusion, the proposed system provides a feasible initial approach for motorcycle parking detection, but further improvements in dataset diversity, annotation quality, and model robustness are required to achieve reliable large-scale deployment.
Improving Neural Network Based on Seagull Optimization Algorithm for Controlling DC Motor Widi Aribowo; Supari Muslim; Fendi Achmad; Aditya Chandra Hermawan
Jurnal Elektronika dan Telekomunikasi Vol. 21 No. 1 (2021)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/jet.v21.48-54

Abstract

This article presents a direct current (DC) motor control approach using a hybrid Seagull Optimization Algorithm (SOA) and Neural Network (NN) method. SOA method is a nature-inspired algorithm. DC motor speed control is very important to maintain the stability of motor operation. The SOA method is an algorithm that duplicates the life of the seagull in nature. Neural network algorithms will be improved using the SOA method. The neural network used in this study is a feed-forward neural network (FFNN). This research will focus on controlling DC motor speed. The efficacy of the proposed method is compared with the Proportional Integral Derivative (PID) method, the Feed Forward Neural Network (FFNN), and the Cascade Forward Backpropagation Neural Network (CFBNN). From the results of the study, the proposed control method has good capabilities compared to standard neural methods, namely FFNN and CFBNN. Integral Time Absolute Error and Square Error (ITAE and ITSE) values from the proposed method are on average of 0.96% and 0.2% better than the FFNN and CFBNN methods.
PELATIHAN PENGGUNAAN DAN PEMELIHARAAN PEMBANGKIT TENAGA SURYA PADA DESA BEGAN, KECAMATAN GLAGAH, KABUPATEN LAMONGAN JAWA TIMUR Ayusta Lukita Wardani; Mahendra Widiyartono; widi aribowo; Reza Rahmadian; Aditya Chandra Hermawan; Nur Vidia Laksmi B; Daeng Rakhmatullah; As'ad Shidqy Aziz; Fithrotul Irda Amaliah; Alfarid Hendro Yuwono
Jurnal Lintas Karsa Vol. 2 No. 1 (2025): Jurnal Lintas Karsa (November 2025)
Publisher : S1 Teknik Mesin Fakultas Teknik. Universitas Negeri Surabaya Gedung A6 Kampus UNESA Ketintang Surabaya 60231

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/lintaskarsa.v2i01.74039

Abstract

Pemanfaatan energi surya merupakan salah satu solusi strategis dalam meningkatkan kemandirian energi dan kualitas fasilitas umum di wilayah pedesaan. Desa Began, Kecamatan Glagah, Kabupaten Lamongan, Jawa Timur, memiliki potensi energi surya yang cukup besar, namun pemanfaatan dan pemeliharaan sistem pembangkit listrik tenaga surya (PLTS) masih menghadapi keterbatasan pengetahuan dan keterampilan masyarakat. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kapasitas masyarakat dalam penggunaan dan pemeliharaan PLTS, khususnya PLTS Penerangan Jalan Umum (PJU), melalui pelatihan dan pendampingan teknis. Metode pelaksanaan meliputi survei awal pada fasilitas desa, yaitu masjid, jalan desa, dan area pemakaman, untuk menentukan lokasi penempatan yang tepat, dilanjutkan dengan pelatihan penggunaan dan pemeliharaan PLTS yang dilengkapi dengan pretest dan posttest sebagai instrumen evaluasi. Selain itu, masyarakat dibekali dengan buku saku sebagai panduan praktis penggunaan, pemeliharaan, dan penanganan gangguan (troubleshooting). Hasil kegiatan menunjukkan adanya peningkatan pemahaman dan antusiasme masyarakat terhadap pemanfaatan energi surya, yang tercermin dari peningkatan hasil posttest serta partisipasi aktif peserta selama pelatihan. Kegiatan ini diakhiri dengan serah terima PLTS PJU dan buku saku kepada masyarakat Desa Began sebagai luaran nyata kegiatan pengabdian. Secara keseluruhan, kegiatan ini berkontribusi terhadap pencapaian SDG 7 (Energi Bersih dan Terjangkau),dan SDG 11 (Kota dan Permukiman Berkelanjutan) melalui peningkatan kemandirian energi dan kapasitas masyarakat desa.
Co-Authors A. Shehadeh, Hisham A.A. Ketut Agung Cahyawan W Abdullayev, Vugar Hacimahmud Abualigah, Laith Achmad Imam Agung ACHMAD RIZAL MAWALI Achmad, Fendi Ade Ananda Kurniawan Adhim Triano Nasrullah Aditya Chandra Hermawan Aditya Chandra Hermawan Aditya Prapanca Agus Budi Santosa Agus Budi Santosa Agustin, Intan Permata Ainul, Safira Tri Handini Akhmad Rizqi Kamal Alfarid Hendro Yuwono Aljohani, Abeer Amaliah, Fithrotul Irda Anita Susanti Arief, Muhammad Baharuddin Arief, Rozihan Ariyanti, Karin Nur Fitria Ariyanto, Sudirman Rizki Arrashid, Rakhmad Arrashid, Rakhmad Agus As'ad Shidqy Aziz As’ad Shidqy Aziz Ayusta Lukita Wardani B, Nur Vidia Laksmi B., I Gusti Putu Asto Bambang Suprianto . Daeng Rakhmatullah Danang Aji Basudewa DIDIK PURWANTO Diego Oliva Dwi, Mochamad Hanif Edy Kurniawan Effendi, Moh. Zaenal Elsayed Abd Elaziz, Mohamed Erina Rahmadyanti Euis Ismayati Farid Baskoro Faruqi, Muhammad Ismail Feby Agung Pamuji Fendi Achmad Firdaus, Muhammad Riqi Fithrotul Irda Amaliah Fransisca, Yulia Hafid Al azzah Haratama, Kusuma Refa Heri Suryoatmojo Hermawan , Aditya Chandra Hermawan,, Aditya Chandra Hisham A. Shehadeh Ibrohim Ibrohim Ibrohim Igo Nanda Deka Zaymapa Ilham Amarulloh Isaac, Jacob Raglend Ismet Basuki Joko Joko Kevin Pranata Putra Khoirul Anwar Khoriri, Doddy Nur Laith Abualigah Liu, Tian-Hua Lucia Tri Pangesthi Lukita Wardani, Ayusta Luthfiyah Nurlela Ma'arif, Muhammad Fikrul Mahendra Widiyartono Mahendra Widyartono Mochamad Hanif Dwi Wicaksono Mubarok, Muhammad Syahril MUHAMMAD PERMANA SETYA GUNAWAN Muhammad Syahril Mubarok Muhammad Taufiqurrohman, Muhammad Munoto Munoto Musthofa, Achmad Malikur Robbani Mzili, Toufik Nita Kusumawati Nugrahani Astuti Nugroho, Yuli Sutoto Nur Vidia Laksmi B Nurdiansyah, Aristyawan Putra Nurlita, Ita Nurul Jaizah Oliva, Diego Pradipta, Moh. Alfiansyah Putera Putra, Alfredo Arianto Permana Putra, Andreas Perkasa Putro, Wahyu Sasongko R. Endro Wibisono Raden Mohamad Herdian Bhakti Rahmadian, Reza Rahmatullah, Daeng Rakhmad Agus Arrashid Ridwan, M. Nanda Tri Maulana Rina Harimurti Rosalin, Berliana Dzakiyya Rufi'i Ruzairi Abdul rahim Sabo Aliyu Sabo, Aliyu Salam, Muhammad Abdus Shehadeh, Hisham Shehadeh, Hisham A. Shidqy Aziz, As'ad Siti Sulandjari Soleimanian Gharehchopogh, Farhad Sri . Handayani Sri Dwiyanti Subuh Isnur Haryudo Suhermanto, Dimas Ahmad Nur Kholis Supari Muslim Supari Supari Syamsul Muarif Taufiqur Rohman Toufik Mzili Udin, Muhammad Syafi Umar, Abubakar Umaroh, Susi Tri Unit Three Kartini Wicaksono, Mochamad Hanif Dwi Widiyartono, Mahendra Wiyli Yustanti WRAHATNOLO, TRI YUNI YAMASARI Zahrotul Maulia Zangana, Hewa Majeed Zaymapa, Igo Nanda Deka