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Pemodelan Interaksi Medan Listrik Dinamis dan Gelombang Elektromagnetik Monang Marpaung; Gideon Fercy Silitonga; Wandani Putri Siregar; Arwadi Sinuraya; Desman Jonto Sinaga
JURNAL ILMIAH NUSANTARA Vol. 3 No. 1 (2026): Jurnal Ilmiah Nusantara Januari 2026
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jinu.v3i1.7491

Abstract

This research stems from the need to understand the complex relationship between time-varying electric fields and electromagnetic waves, which often presents difficulties in simulating their propagation in various media. The primary focus is to develop a numerical model capable of predicting the dynamics of this interaction, thus enabling its use in antenna development and radiation evaluation. The applied method includes a Finite-Difference Time-Domain approach, which solves the fundamental equations stepwise in both the time and space domains. The results show that the model is capable of reproducing transverse propagation patterns with a high degree of accuracy and detecting strong mutual induction effects at high frequencies. These findings provide a foundation for improving the performance of electromagnetic devices, minimizing potential interference, and opening up new innovations in the telecommunications sector.
STUDI HUBUNG SINGKAT PADA TRANSFORMATOR TEGANGAN TINGGI MENGGUNAKAN ETAP 16.0.0 Julio Betran Simalango; Egy Wira indana; Muhammad Rizky Hidayah; Arwadi Sinuraya; Desman Jonto Sinaga
JURNAL ILMIAH NUSANTARA Vol. 3 No. 1 (2026): Jurnal Ilmiah Nusantara Januari 2026
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jinu.v3i1.7496

Abstract

Short-circuit fault is a dangerous condition in power systems because it produces very high currents. Transformers, as important equipment in high-voltage systems, must be analyzed to ensure safe operation during faults. This study aims to analyze short-circuit characteristics of a high-voltage transformer using ETAP 16.0.0.softwareShort-circuit fault is a dangerous condition in power systems because it produces very high currents. Transformers, as important equipment in high-voltage systems, must be analyzed to ensure safe operation during faults. This study aims to analyze short-circuit characteristics of a high-voltage transformer using ETAP 16.0.0 software.This research is expected to be used as a reference for designing protection systems for high-voltage equipment.
STUDI STARTING DAN RESISTANSI STATOR TERHADAP SLIP, ARUS AWAL, DAN KUALITAS DAYA MOTOR INDUKSI Irenius Aditya Lumbangaol; Andira; Muhammad Ikbal; Desman Jonto Sinaga; Arwadi Sinuraya
JURNAL ILMIAH NUSANTARA Vol. 3 No. 1 (2026): Jurnal Ilmiah Nusantara Januari 2026
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jinu.v3i1.7519

Abstract

This study presents a literature review on the influence of starting methods and stator resistance on slip characteristics, inrush current, and power quality performance of three-phase induction motors. Several starting strategies including direct-on-line (DOL), star–delta, autotransformer, soft-starter, and voltage–frequency (V/f) control using inverter-based drives are reviewed to evaluate their effect on initial current surge and electromagnetic torque development. Findings indicate that conventional starting methods such as DOL produce high inrush current and voltage sag, while soft-starter and inverter-based methods provide smoother torque transition and reduced starting current. Variation of stator resistance demonstrates a proportional effect on slip characteristics and torque, where higher resistance increases slip and reduces starting efficiency. In addition, starting methods may influence power quality parameters such as harmonic distortion, power factor, and voltage drop depending on the applied control strategy. The study concludes that integrating appropriate starting control with stator resistance adjustments can improve dynamic performance of induction motors and reduce power disturbances in industrial systems.
Simulasi Sistem Pendeteksi Getaran Menggunakan Sensor Tilt Di Tinkercad Caecilia Kristiwinita Sitanggang; Jerryo Daniel Saragih; Rizki Abdillah; Arwadi Sinuraya; Desman Jonto Sinaga
Menulis: Jurnal Penelitian Nusantara Vol. 1 No. 12 (2025): Menulis - Desember
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/menulis.v1i12.755

Abstract

Pendeteksian getaran sangat penting untuk memantau integritas struktur, kesehatan mesin, dan sistem peringatan dini gempa bumi. Penelitian ini bertujuan untuk merancang dan mensimulasikan sistem pendeteksi getaran menggunakan sensor tilt (SW-520D) pada platform Tinkercad. Sistem mengintegrasikan mikrokontroler Arduino Uno, sensor tilt untuk mendeteksi perubahan sudut akibat getaran, buzzer sebagai peringatan suara, dan LED sebagai indikator visual. Metodologi simulasi mencakup perakitan rangkaian virtual, pemrograman logika berbasis ambang batas, serta pengujian real-time pada berbagai kondisi kemiringan. Hasil menunjukkan sistem mampu mendeteksi sudut kemiringan di atas 15° dengan waktu respons kurang dari 200 ms, mengaktifkan buzzer dan LED secara bersamaan. Sistem tetap stabil pada kondisi normal dan otomatis reset saat kembali ke posisi seimbang. Tinkercad terbukti sebagai alat prototipe yang efektif dan gratis sebelum implementasi fisik. Penelitian ini menyimpulkan bahwa pendekatan berbasis sensor tilt menawarkan solusi sederhana, andal, dan skalabel untuk pemantauan getaran pada bangunan, peralatan industri, dan aplikasi pendidikan, serta mendukung pengembangan sistem peringatan dini berbiaya rendah.
Prediksi Akurat Output Daya Jangka Pendek PLTS Menggunakan Algoritma Long Short-Term Memory (LSTM) Jaringan Saraf Tiruan Berbasis Data Cuaca Real-Time Elvin Frans Aritonang; Afriza Arif; Okta Danil Tarigan; Desman Jonto Sinaga; Arwadi Sinuraya
JURNAL ILMIAH NUSANTARA Vol. 3 No. 1 (2026): Jurnal Ilmiah Nusantara Januari 2026
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jinu.v3i1.7593

Abstract

Accurate short-term power output forecasting for Photovoltaic (PV) systems is crucial for electricity grid management and energy trading. This study proposes and validates a Long Short-Term Memory (LSTM) model, a Deep Learning architecture, for forecasting PV power output 1-hour ahead using historical and real-time weather variables (irradiance, temperature, humidity, and wind speed). The model is compared against the conventional Autoregressive Integrated Moving Average (ARIMA) and Support Vector Machine (SVM) models. One year of 15-minute performance data from a 50 kWp rooftop PV system was utilized for model training and testing. Evaluation results demonstrated that the LSTM model significantly outperformed the ARIMA and SVM models in terms of accuracy metrics. The LSTM model achieved a Mean Absolute Error (MAE) of 5.5% and a Root Mean Square Error (RMSE) of 7.8% of the nominal capacity, substantially lower than the comparative models, especially under fluctuating weather conditions (partial cloudiness). The superiority of LSTM lies in its ability to capture the complex temporal dependencies between weather variables and power output, a major challenge for traditional statistical models. This research confirms that the integration of Deep Learning offers a more robust and accurate solution for PV power forecasting, supporting grid operators in achieving higher reliability and operational efficiency.