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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Robotics and Automation (IJRA) International Journal of Applied Power Engineering (IJAPE) International Journal of Renewable Energy Development Jurnal Teknologi Reaktor Nuklir Tri Dasa Mega Techno.Com: Jurnal Teknologi Informasi Jurnal Neutrino : jurnal fisika dan aplikasinya TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknosains JSI: Jurnal Sistem Informasi (E-Journal) JFA (Jurnal Fisika dan Aplikasinya) JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Jurnal Pendidikan Fisika Jurnal Teknologi Elektro Journal of Teaching and Learning Physics JPSE (Journal of Physical Science and Engineering) Jurnal Rekayasa Bahan Alam dan Energi Berkelanjutan Journal of Physics: Theories and Applications BERDIKARI : Jurnal Inovasi dan Penerapan Ipteks JRST (Jurnal Riset Sains dan Teknologi) Indonesian Journal of Chemistry Natural: Jurnal Ilmiah Pendidikan IPA Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Pendidikan Fisika dan Teknologi Jambura Journal of Electrical and Electronics Engineering Indonesian Journal of Electrical Engineering and Computer Science G-Tech : Jurnal Teknologi Terapan International Journal of Educational Review Indonesian Community Journal Jurnal Pijar MIPA Jurnal Algoritma PREVENIRE: Journal of Multidisciplinary Science Cakrawala Journal of Artificial Intelligence and Digital Business JESCEE- Journal of Emerging Supply Chain, Clean Energy, and Process Engineering Jurnal Pendidikan Sains Indonesia (Indonesian Journal of Science Education) International Journal of Renewable Energy Development Jurnal Teknik AMATA Jurnal Pendidikan MIPA Jurnal Pemanfaatan Teknologi untuk Masyarakat
Prayogi, Soni
Department Of Electrical Engineering, Faculty Of Industrial Engineering, Pertamina University, Jakarta 12220 Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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Pengaruh Model Kadir Dengan Echomind Untuk Meningkatkan Hasil Belajar Siswa Pada Materi Gelombang Bunyi fitria silviana; Hilda Mazlina; Putri Zuhra; Soni Prayogi
Jurnal Pendidikan Fisika Vol. 15 No. 1 (2026)
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Rendahnya hasil belajar fisika peserta didik masih menjadi tantangan dalam pembelajaran, khususnya pada materi gelombang bunyi yang bersifat abstrak. Penelitian ini bertujuan untuk menganalisis pengaruh model pembelajaran KADIR (Koneksi, Aplikasi, Diskursus, Improvisasi, dan Refleksi) berbantuan aplikasi EchoMind terhadap hasil belajar fisika peserta didik kelas XI SMAN 13 Jakarta. Penelitian menggunakan pendekatan kuantitatif dengan metode quasi-experimental dan desain Nonequivalent Control Group Design. Sampel dalam penelitian ini terdiri dari  kelas XI.2 yang berjumlah 30 orang sebagai kelas kontrol serta kelas XI.4 dengan  jumlah 30 orang sebagai kelas eksperimen. Sampel ini dipilih melalui teknik purposive sampling. Instrumen penelitian berupa tes hasil belajar yang diberikan sebelum (pretest) dan sesudah (posttest) pembelajaran. Data dianalisis menggunakan uji normalitas Shapiro–Wilk, uji homogenitas Levene, dan uji hipotesis menggunakan Mann–Whitney U test. Hasil penelitian setelah perlakuan, diperoleh perbedaan yang signifikan pada hasil posttest (p = 0,018 < 0,05), yang menunjukkan bahwa model pembelajaran KADIR berbantuan aplikasi EchoMind memberikan pengaruh positif terhadap hasil belajar fisika peserta didik. Integrasi model pembelajaran aktif dengan media pembelajaran digital mampu menciptakan proses pembelajaran yang lebih interaktif, kontekstual, dan bermakna.
Peningkatan Produktivitas Kebun Hidroponik Pagifarm Bogor melalui Implementasi Pembangkit Listrik Tenaga Surya Berbasis IoT Soni Prayogi; Raden RDR; Ismah Aulia Larasati; Muhammad Abdillah; Arif Murti Rozamuri
I-Com: Indonesian Community Journal Vol 5 No 4 (2025): I-Com: Indonesian Community Journal (Desember 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/i-com.v5i4.8070

Abstract

Permasalahan tingginya ketergantungan pada listrik konvensional dalam usaha hidroponik berdampak pada tingginya biaya operasional dan risiko penurunan produktivitas akibat pemadaman listrik. Kegiatan pengabdian masyarakat ini dilaksanakan di Pagifarm Bogor dengan tujuan meningkatkan efisiensi energi dan produktivitas pertanian hidroponik melalui penerapan Pembangkit Listrik Tenaga Surya (PLTS) berbasis Internet of Things (IoT). Metode pelaksanaan meliputi survei kebutuhan energi, perancangan dan instalasi sistem PLTS, serta pelatihan teknis kepada mitra mengenai penggunaan dan pemeliharaan sistem. Hasil kegiatan menunjukkan pengurangan konsumsi listrik dari PLN hingga 70%, penurunan biaya operasional listrik, serta peningkatan produktivitas tanaman sebesar 10–15% dengan siklus panen yang lebih singkat. Selain itu, mitra mampu mengelola sistem PLTS secara mandiri melalui aplikasi monitoring berbasis IoT. Kesimpulannya, penerapan energi terbarukan berbasis PLTS mampu meningkatkan keberlanjutan usaha hidroponik sekaligus memberikan dampak positif pada aspek ekonomi, sosial, dan lingkungan.
Simple Pendulum Experiment with Sound Assistance Using Arduino UNO for Students with Special Needs Soni Prayogi; Fitria Silviana
International Journal of Educational Review Vol. 8 No. 1 (2026): International Journal of Educational Review, Volume 8, Number 1 (2026)
Publisher : Unib Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/ijer.v8i1.26454

Abstract

In this paper, we propose a way to demonstrate the dependence of distance and time in a pendulum experiment to blind students. The periodic oscillations of the pendulum are translated, by the Arduino and the ultrasonic sensor, into periodic frequency variations across the speaker. The main advantage of this proposal is the possibility of blind students understanding gestures without having to touch them. Our results show that by converting the position range into the frequency range emitted by computer speakers and blind students can realize how the periodic pendulum movement occurs. we believe that the idea presented here can be used in other experimental demonstrations involving movement observations. Visually impaired students can use their hands in front of the sensor and move them to correlate the frequency with the distance and use it as a sound rule.
Visible light communication for rapid monitoring of environmental changes using thin film solar cells Soni Prayogi; Wahyu Kunto Wibowo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 1: February 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i1.26375

Abstract

This study investigates the use of visible light communication (VLC) for rapid environmental monitoring by leveraging thin film solar cells as signal receivers. VLC, which employs visible light for data transmission, presents an energy-efficient and eco-friendly approach for real-time monitoring. Thin-film solar cells, recognized for their efficiency and low-light performance, function both as environmental sensors and VLC signal receivers. We conducted experiments to evaluate the system's performance across various environmental conditions, such as light intensity and temperature changes. Our findings indicate that thin-film solar cells can swiftly and accurately detect environmental changes while maintaining a low bit error rate for VLC data. The system also shows high responsiveness to rapid light variations, making it well-suited for dynamic monitoring tasks like air quality, humidity, and forest fire detection. This research highlights VLC technology's significant potential for environmental monitoring applications requiring quick, real-time data transmission, and energy efficiency with thin-film solar cells. The integration of this technology promises to enhance environmental monitoring systems, contributing to climate change mitigation and improved environmental management, and sets the stage for developing advanced, sustainable solutions in wireless communication and ecological monitoring.
Numerical simulation of layer thickness optimization in perovskite solar cells for enhanced power conversion efficiency Soni Prayogi
Jurnal Teknosains Vol 15, No 1 (2025): December
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/teknosains.109079

Abstract

Perovskite solar cells (PSCs) have gained significant attention due to their remarkable power conversion efficiency (PCE) and potential for low-cost, scalable production. Despite this progress, further efficiency enhancement requires systematic optimization of device architecture, particularly the thickness of functional layers. This study presents a numerical simulation using the OGMANANO simulation platform to investigate the influence of layer thickness variation, specifically in the perovskite absorber layer, electron transport layer (ETL), and hole transport layer (HTL), on the performance of planar PSCs. The simulation models a typical n-i-p structured device under standard AM1.5G illumination, evaluating key photovoltaic parameters such as short-circuit current density (Jsc), open-circuit voltage (Voc), fill factor (FF), and overall PCE. Results indicate that the optimal absorber thickness lies in the 500–600 nm range, with a peak efficiency of 22.7% achieved at 550 nm. Furthermore, ETL and HTL show optimal performance at 50 and 60 nm, respectively, minimizing recombination losses and enhancing charge transport. The study concludes that precise layer thickness control is critical for maximizing PSC efficiency. The use of OGMANANO proved effective in simulating multilayer perovskite structures, providing a reliable tool for pre-fabrication optimization in advanced solar cell design. 
Intelligent Energy Prediction in Smart Manufacturing Using Deep Learning Techniques Soni Prayogi; Wahyu kunto Wibowo
G-Tech: Jurnal Teknologi Terapan Vol 10 No 3 (2026): G-Tech, Vol. 10 No. 3 July 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i3.10725

Abstract

The transition toward smart manufacturing requires advanced energy management strategies that leverage artificial intelligence to improve operational efficiency and sustainability. This study proposes a novel deep learning framework based on a Long Short-Term Memory (LSTM) network for analyzing and predicting energy consumption in smart manufacturing environments using real-time data acquired from Internet of Things (IoT)-enabled industrial sensors. Unlike previous studies that primarily focus on offline energy forecasting or static datasets, the proposed approach integrates temporal energy consumption patterns from heterogeneous sensor streams to support predictive energy management and dynamic load optimization. The collected data were preprocessed through normalization and feature engineering before being trained and evaluated using the LSTM model. Experimental results demonstrate that the proposed model achieves a Mean Absolute Error (MAE) of 0.84 kWh, a Root Mean Square Error (RMSE) of 2.13 kWh, and a coefficient of determination (R²) of 0.987, indicating high prediction accuracy. Furthermore, the predictive framework enables an estimated energy consumption reduction of 14.8% through proactive load scheduling. These findings demonstrate that integrating LSTM-based deep learning with IoT sensor networks provides an effective solution for intelligent energy forecasting, improves manufacturing efficiency, and contributes to sustainable industrial development.
Co-Authors . Saminan A, Muhammad AA Sudharmawan, AA Alfredo, Andromeda J Amsal Aritonang Anandra, Muhammad F Apta Prana Mas Erlangga Arif Murti Rozamuri Aufa, Nurul Ayunis Ayunis Aziiz, Ahmad Mushawwir Beny Ragadita Cahyono, Yoyok Chandra, Annisya E Dadan Hamdani Darminto . Darminto Darminto Darminto Darminto Darminto Darminto Darminto Darminto Elmi Mahzum Fauzi Ahmad Muda Fitria Silviana Fitria Silviana fitria silviana Fitria Silviana Frisca Elfrisa Nainggolan Gatut Yudoyono Gatut Yudoyono Giganta Rose Kakke Hartanxia Hartanxia Herminarto Nugroho Herminarto Nugroho Hidayat, Robi T Hilda Mazlina I Nur Fajar Imammah, Sofyah Irgi Faturrahman Ismah Aulia Larasati Ketut Saha Kesta Dinatha Mahzum, Elmi Marza Ihsan Marzuki Marza Ikhsan Marzuki Marza Ikhsan Marzuki Marza Ikhsan Marzuki Marzuki, Marza I Marzuki, Marza Ikhsan Maulana, Rifqi Muhamad FE Nugroho Muhammad Muhammad Abdillah Muhammad Abdillah Muhammad Muhammad Muhammad Muhammad Muhammad Syukri Nanda Adiva Yusman Nita I Pertiwi Nita Indriani Pertiwi Nita Indriani Pertiwi Nugroho, Irvan A Nugroho, Teguh A Nur Fajar, Iqbal Nurul Aufa Pratama, Aldi Putra, Yehezkiel P. Putri Zuhra Raden RDR Rizky Agung Ramadhan Roong, Inggrid IO Safira Luthfia Saminan Saminan Saminan, Saminan Saputra , Duta M W Silviana, Fitria Sirait, Juanto Syahrul Ghufron Tan, Dennis Tarmizi Hamid, Tarmizi Teguh Aryo Nugroho Teguh Aryo Nugroho Teuku Muhammad Roffi Teuku Muhammad Roffi Wahyu Agung Pramudito Wahyu Agung Pramudito Wahyu Kunto Wibowo Wahyu Kunto Wibowo Wahyu Kunto Wibowo Wibowo, Wahyu K. Wibowo, Wahyu Kunto Yoyok Cahyono Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin* Zainuddin, Zainuddin Zapata, Malvin