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Design and Development of Solar Pump System for Automatic Watering of Shallots Muh. Ilham; Yuliana; Idris, Ahmad Rosyid; Usman; Achmad, Alamsyah
Jurnal Teknologi Elekterika Vol. 21 No. 2 (2024)
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v21i2.5117

Agriculture is a key sector of the Indonesian economy, with shallots being one of the most important commodities. However, limited access to electricity in rural areas is often a barrier to the implementation of efficient irrigation systems. This research focuses on developing an automatic shallot irrigation system using a solar pump. The system is designed by using solar panels to convert solar energy into electricity to power the water pump. They use an Arduino-based control system integrated with a real-time clock (RTC) to automatically set the watering schedule so that plants can be watered at the right time without human intervention. Tests were conducted on 96 m² of land to evaluate the performance of the automation system, energy efficiency, and system performance under actual operating conditions. The testing results show that the system can operate efficiently, with the solar panel generating enough energy to power the pump and maintain watering continuity. The system can reduce dependence on conventional electricity, providing a sustainable and environmentally friendly irrigation solution. As such, the system provides an effective solution for agricultural systems in areas with limited access to electricity, while supporting the use of renewable energy.

MEDIUM VOLTAGE INSULATOR CRACK DETECTION USING MOBILENetV2 AND TENSORFLOW Yani, Ahmad; Sofyan, Sofyan; Lukman, Musfirah Putri; Usman, Usman; Junaidi, Apri
Jurnal Teknologi Elekterika Vol. 22 No. 1 (2025)
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v22i1.5420

This study discusses the detection of medium voltage insulator cracks using object detection technology. This study uses medium voltage ceramic insulator image data at the ULP Daya Waste Material Warehouse. Ceramic insulator image data is categorized into good and damaged conditions. Preprocessing involves labeling, dividing train data, validation, and testing, and exporting data to Pascal VOC format. MobileNetV2 is implemented on Google Collab to train the object detection model. The evaluation of the model accuracy is in the COCO matrix, while the performance graph shows that the model can read objects well because the reading curve is in line with the smooth curve. Furthermore, this model is applied in creating an Android application that uses the device's camera to detect objects in real-time. This application processes images, converts from YUV to RGB, and performs object detection using the trained model. The detection results are displayed with bounding boxes and labels on the camera reviewer, namely the good class with a reading value of 1.0, the damaged class with a reading value of 0.67 and the background 1.0. This application also tracks detected objects and updates the display according to the detection results.

Investigating the Effect of PV Panel Mounting Orientation under Partial Shading Conditions (A Simulation-Based Study) Usman, Usman; Achmad , Alamsyah; Sofyan , Sofyan; Sirad, Mochammad Apriyadi Hadi; Hidayatullah, Syarif; Isman, Muh
INTEK: Jurnal Penelitian Vol 12 No 1 (2025): April 2025
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/intek.v12i1.5174

This study aims to investigate the effect of shading on the mounting orientation of PV panel and the availability or unavailability of Bypass Diodes on the performance of PV panel under partially shading conditions. In this study, for each PV panel mounting orientation, the number of PV cells that received shading was grouped into three categories: 9 cells, 18 cells and 27 cells respectively with the shading fixed vertically. The study also considers the availability and unavailability of bypass diodes. The simulation results show that with vertical shading partially covering the PV cells, the landscape mounting orientation is the best orientation for PV panels with bypass diodes to avoid the partial shading effect

Grey Wolf Optimizer-Neural Network Model for Indonesia Electricity Demand Prediction: Multi-Scenario Analysis and Performance Evaluation 2026-2034 Sofyan, Sofyan; Usman, Usman; Achmad, Alamsyah; Hadi Sirad, Mochammad Apriyadi; Fudholi, Ahmad; Sapari, Norazliani MD
PROtek : Jurnal Ilmiah Teknik Elektro Vol 12, No 3 (2025): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v12i3.10398

Indonesia's rapid economic development and energy transition goals necessitate accurate long-term electricity demand forecasting to ensure supply security while optimizing infrastructure investments. This study addresses critical gaps in existing forecasting methodologies by developing a hybrid Grey Wolf Optimizer-Neural Network (GWO-NN) model specifically designed for emerging economy characteristics. While recent deep learning approaches (LSTM, CNN-LSTM) show promise for short-term forecasting, they often fail in long-term predictions due to limited adaptability to economic volatility and infrastructure constraints typical in developing nations. Our GWO-NN framework overcomes these limitations through intelligent hyperparameter optimization and multi-scenario modeling that captures Indonesia's unique socio-economic dynamics. The model incorporates 15 years of historical data (2010-2025) across seven key variables: GDP growth, population dynamics, temperature variations, industrial activity, urbanization rates, energy efficiency, and electrification progress. Rigorous validation against PLN's official projections reveals superior performance: Conservative scenario achieves exceptional 3.9% average absolute difference, Moderate scenario 19.0%, demonstrating significant improvement over traditional ARIMA models (35% error) and recent CNN-LSTM approaches (25% error). The 2034 demand projections range from 377.0 TWh (Conservative) to 546.1 TWh (Optimistic), providing policymakers with robust planning envelopes. This research contributes methodologically through hybrid metaheuristic optimization and practically through evidence-based planning support for Indonesia's renewable energy transition and carbon neutrality targets by 2060.

Grey Wolf Optimizer-Neural Network Model for Indonesia Electricity Demand Prediction: Multi-Scenario Analysis and Performance Evaluation 2026-2034 Sofyan, Sofyan; Usman, Usman; Achmad, Alamsyah; Hadi Sirad, Mochammad Apriyadi; Fudholi, Ahmad; Sapari, Norazliani MD
PROtek : Jurnal Ilmiah Teknik Elektro Vol 12, No 3 (2025): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v12i3.10398

Indonesia's rapid economic development and energy transition goals necessitate accurate long-term electricity demand forecasting to ensure supply security while optimizing infrastructure investments. This study addresses critical gaps in existing forecasting methodologies by developing a hybrid Grey Wolf Optimizer-Neural Network (GWO-NN) model specifically designed for emerging economy characteristics. While recent deep learning approaches (LSTM, CNN-LSTM) show promise for short-term forecasting, they often fail in long-term predictions due to limited adaptability to economic volatility and infrastructure constraints typical in developing nations. Our GWO-NN framework overcomes these limitations through intelligent hyperparameter optimization and multi-scenario modeling that captures Indonesia's unique socio-economic dynamics. The model incorporates 15 years of historical data (2010-2025) across seven key variables: GDP growth, population dynamics, temperature variations, industrial activity, urbanization rates, energy efficiency, and electrification progress. Rigorous validation against PLN's official projections reveals superior performance: Conservative scenario achieves exceptional 3.9% average absolute difference, Moderate scenario 19.0%, demonstrating significant improvement over traditional ARIMA models (35% error) and recent CNN-LSTM approaches (25% error). The 2034 demand projections range from 377.0 TWh (Conservative) to 546.1 TWh (Optimistic), providing policymakers with robust planning envelopes. This research contributes methodologically through hybrid metaheuristic optimization and practically through evidence-based planning support for Indonesia's renewable energy transition and carbon neutrality targets by 2060.

ANALISIS PENGARUH PEMBANGKIT LISTRIK TENAGA SURYA TERHADAP KESTABILAN SISTEM KELISTRIKAN KEPULAUAN SANGIHE Syarwan Ariwibowo, Muhammad; Usman, Usman; Putri L, Musfirah; Rahmadani, Arief
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3S1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3S1.8048

PT PLN (Persero) merencanakan penambahan pembangkit EBT sebesar 40,6 GW hingga tahun 2030, rencana tersebut tersebar ke seluruh pelosok Indonesia termasuk sistem isolated 20 kV salah satunya yaitu pembangunan PLTS Sangihe 1,3 MWp yang berlokasi di Kabupaten Kepulauan Sangihe. Karena sifat surya yang intermiten berpotensi memicu deviasi frekuensi dan penurunan tegangan, penelitian ini mengevaluasi dampak integrasi PLTS terhadap kinerja dinamik sistem dengan acuan standard Grid Code 2020 dengan batas nilai frekuensi operasi sebesar 50,00 Hz ± 0,20 serta tegangan nominal +5% dan −10%. Pemodelan dilakukan pada ETAP 21.0.1 untuk subsistem PLTD Tahuna dan PLTS Sangihe yang terhubung melalui feeder express sekitar 4,4 km dan didukung Battery Energy Storage System (BESS). Hasil penelitian simulasi aliran daya menunjukkan bahwa, nilai profil tegangan di ujung penyulang meningkat rata rata 0,368% kV dengan tegangan paling besar 19,55kV dan tetap dalam standard yang ditentukan. Pada percobaan stabilitas peralihan saat penurunan daya keluaran PLTS sebesar 20%, 50%, 70%, dan 100% pada beban puncak siang, ayunan frekuensi selalu berada dalam batas yang diizinkan dan pulih menuju keadaan tunak dalam kisaran 7 sampai 13 detik, sedangkan tegangan rata rata lima busbar kembali sekitar 19,4 kV dalam 7 sampai 10 detik

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