Article Per Year (5 Year)
p-Index From 2021 - 2026
8.417
P-Index
This Author published in this journals
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 JSI: Jurnal Sistem Informasi (E-Journal) JFA (Jurnal Fisika dan Aplikasinya) JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI 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 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
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

Published : 59 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 59 Documents
Search

 2   3   4   5   6 
Analisis Tingkat Keasaman Ampas Kopi Sebagai Katalis Alternatif Sumber Energi Bio Baterai Mahzum, Elmi; Aufa, Nurul; Prayogi, Soni
N A T U R A L: Jurnal Ilmiah Pendidikan IPA Vol 9 No 2 (2022)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/natural.v9i2.13861

Abstract

In the study, we analyzed the acidity level of coffee grounds as an alternative catalyst for bio-battery energy sources, investigated how coffee grounds work as an alternative catalyst, and investigated how power is generated from variations in coffee grounds. This study used four variations of coffee grounds. Data collection was carried out by taking pH data or acidity level, voltage data, and also the length of time the LED was on from each variation of coffee grounds. The results showed that the civet arabica, original arabica, mongoose robusta, and original robusta coffee grounds respectively had pH values of 5, 5.15, 5.36, 5.6. Then the voltage is 1.35 volts, 1.27 volts, 1.11 volts, 0.994 volts. And the LED time is 417 hours, 414 hours, 409 hours, 404 hours. So that from the results obtained there is a significant relationship between the pH value and the voltage and power, that is, the smaller the pH value, the greater the voltage and power generated.
Implementation of CNN-Based Computer Vision for Personal Protective Equipment Detection in the Oil and Gas Industry prayogi, soni
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 4 (2025): NOVEMBER
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i4.2459

Abstract

Due to the inherently hazardous nature of operations in the oil and gas industry, strict compliance with safety protocols, including the obligatory use of Personal Protective Equipment (PPE), is essential for all workers. Nonetheless, monitoring PPE compliance through manual observation remains inefficient and prone to error, especially in expansive, intricate work settings. To address this challenge, there is a growing demand for an intelligent system capable of accurately and instantaneously detecting PPE use. This research introduces a Computer Vision approach employing Convolutional Neural Networks (CNNs) to identify PPE usage among workers within oil and gas environments. The system leverages a comprehensive dataset of images of workers wearing various types of PPE, including helmets, safety vests, and face masks. These images are used to train a CNN model designed to distinguish and classify the safety equipment. Experimental results demonstrate that the proposed CNN model achieves an impressive 94.2% detection accuracy on the validation data and maintains reliable performance across varying lighting conditions and camera angles. Moreover, the system can identify PPE violations in under 1 second per frame, making it suitable for real-time surveillance applications. As a result, this solution offers a promising enhancement to workplace safety oversight, with the potential to markedly reduce accident rates in the industry. The findings also pave the way for future integration with IoT-based monitoring platforms and further refinement of model adaptability across diverse industrial scenarios. The primary innovation of this study lies in the optimized deployment of CNNs tailored to the challenging conditions of oil and gas sites, delivering high detection precision and rapid response times. This area has seen limited exploration in existing literature.
Analysis of the process of coloring objects based on the optical properties of objects Prayogi, Soni; Silviana, Fitria; Hamid, Tarmizi
Cakrawala Vol 1, No 2 (2022): Desember
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/cakrawala.v1i2.1405

Abstract

Color is a certain spectrum contained in a perfect light (white). The purpose of this study is 1). Can determine the cause of the color of the object (what causes a different object than the other color) 2). Can observe the color that occurs when two or more colors are mixed. The benefit in order to inform readers about what actually causes the color of the object and what if two or more colors are mixed. Mixing colors for color RGB, the colors Red to Green produce colors orange, blue color to produce a color Sian Green, Red color with blue produce magenta, and Red, Green with Blue produces white color. For CMY color mixing, the colors Cyan with yellow produce green color, magenta with yellow produces red color, the color Cyan by Magenta produces blue, and the colors Cyan, Magenta produces yellow Gray (Brown). Color objects can be invisible to the eye because of the reflection of the color of the object illuminated by light.
Development of an Inexpensive Spectrometer Tool with a Tracker to Investigate Light Spectrum Prayogi, Soni; Silviana, Fitria; Saminan, Saminan
Jurnal Pendidikan MIPA Vol 24, No 1 (2023): Jurnal Pendidikan MIPA
Publisher : FKIP Universitas Lampung

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

Abstract

One of the most fascinating areas of physics is likely optics. However, it also includes some of the phenomena that students find to be less clear-the light spectra produced by light diffraction. The experimental analysis of light spectra to evaluate radiation bodies typically requires specialized and expensive equipment that is typically out of the price range for schools. Few teachers are proficient in measuring the wavelengths of light in a spectrum. In this study, we describe a low-cost, straightforward setup that can measure light spectra accurately enough to be utilized in physics and chemistry lectures. We demonstrate how the shareware program Tracker, which is frequently used to teach mechanics, may be used to measure wavelengths with a resolution of roughly 2 nm. Several methods are also available for calibrating various setups, depending on the level of accuracy required.Keywords: optics, spectrum, experimental, wavelength.DOI: http://dx.doi.org/10.23960/jpmipa/v24i1.pp28-38
Pengembangan Keterampilan Siswa Melalui Pelatihan Robotik Untuk Mendukung Agenda Sustainable Development Goals (SDGs) Soni Prayogi; Teguh Aryo Nugroho; Nita Indriani Pertiwi; Wahyu Agung Pramudito; Marza Ikhsan Marzuki; Muhammad Abdillah; Wahyu Kunto Wibowo; Herminarto Nugroho; Teuku Muhammad Roffi; Muhammad Muhammad
I-Com: Indonesian Community Journal Vol 5 No 1 (2025): I-Com: Indonesian Community Journal (Maret 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/icom.v5i1.6486

Abstract

ABSTRACT This Community Service Activity aims to improve students' technical skills in robotics while supporting SDGs, especially quality education and technological innovation. Training includes robotics assembly, programming, and applications, with an interactive approach tailored to the curriculum. The program begins with the identification of partner schools with limited resources, followed by coordination and preparation of training modules. Students learn basic robotics theory including the principles of electronics, mechanics, and programming, as well as the practice of assembling and programming robots in small groups. Internal competitions are held to test students' abilities and motivate them to solve problems creatively. The main challenges include limited facilities and time, overcome by adjusting materials and schedules. Evaluations show significant improvements in student skills, with creative innovations in technology-based solutions to support SDGs. The program has succeeded in generating students' interest in technology, providing a strong foundation for similar programs in the future, and encouraging collaboration between education and industry.
Sinergi Energi Terbarukan dan Pertanian Modern: Penerapan PLTS untuk Meningkatkan Kinerja Usaha Hidroponik di Pagifarm Bogor Soni Prayogi; Teguh Aryo Nugroho; Nita Indriani Pertiwi; Wahyu Agung Pramudito; Marza Ikhsan Marzuki; Muhammad Abdillah; Wahyu Kunto Wibowo; Herminarto Nugroho; Teuku Muhammad Roffi; Muhammad Muhammad
I-Com: Indonesian Community Journal Vol 5 No 2 (2025): I-Com: Indonesian Community Journal (Juni 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.v5i2.7395

Abstract

Permasalahan ketergantungan energi konvensional dalam usaha hidroponik menghambat produktivitas dan efisiensi operasional, terutama pada wilayah dengan akses listrik terbatas atau tidak stabil. Kegiatan pengabdian masyarakat ini dilaksanakan di Pagifarm Bogor dengan tujuan meningkatkan kinerja usaha hidroponik melalui penerapan Pembangkit Listrik Tenaga Surya (PLTS) berbasis IoT. Metode pelaksanaan meliputi survei kebutuhan energi, perancangan dan instalasi sistem PLTS, serta pelatihan penggunaan dan pemeliharaan kepada mitra. Hasil kegiatan menunjukkan adanya peningkatan efisiensi penggunaan energi, penurunan biaya operasional listrik, serta peningkatan produktivitas tanaman hidroponik. Selain itu, mitra mampu secara mandiri mengelola sistem PLTS yang terpasang. Kesimpulannya, sinergi antara energi terbarukan dan teknologi pertanian modern mampu mendukung ketahanan pangan dan keberlanjutan usaha tani, serta memberikan dampak positif terhadap ekonomi lokal dan lingkungan.
Firefly-Based MPPT System Design for Wind Energy Efficiency Enhancement in Remote Areas Soni Prayogi
G-Tech: Jurnal Teknologi Terapan Vol 9 No 3 (2025): G-Tech, Vol. 9 No. 3 July 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v9i3.7345

Abstract

The increasing demand for renewable energy in remote and off-grid areas has highlighted the importance of efficient wind energy utilization. However, wind energy systems are often challenged by unpredictable wind speeds, leading to suboptimal energy harvesting. This study proposes the design of a Firefly Algorithm (FA)-based Maximum Power Point Tracking (MPPT) system to enhance wind energy conversion efficiency. The objective is to develop an intelligent control strategy that optimizes the output power of a wind turbine under fluctuating wind conditions. The proposed system is implemented using a permanent magnet synchronous generator (PMSG) and a DC-DC boost converter. The Firefly Algorithm is employed to dynamically adjust the duty cycle of the converter, thereby maintaining operation at the maximum power point. Simulation results using MATLAB/Simulink demonstrate that the FA-based MPPT outperforms conventional Perturb and Observe (P&O) methods in terms of tracking speed, power stability, and efficiency. The proposed approach achieves faster convergence, reduced oscillations, and higher power output, making it highly suitable for deployment in remote areas with limited access to the power grid. These findings indicate that the integration of intelligent algorithms such as FA in MPPT systems can significantly enhance the performance of wind energy systems in challenging environments
Integration of Artificial Intelligence in Data Analysis for Modern Physics Experiments Silviana, Fitria; Prayogi, Soni
Jurnal Pendidikan Fisika dan Teknologi (JPFT) Vol 11 No 2 (2025): July - December
Publisher : Department of Physics Education, Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jpft.v11i2.10580

Abstract

This study aims to explore the integration of Artificial Intelligence (AI) in data analysis for modern physics experiments, focusing on how AI-based analytical tools can improve the accuracy, efficiency, and interpretability of experimental results. The research was conducted through an experimental approach combining traditional physics data collection methods with AI-driven algorithms, including regression models, clustering techniques, and neural networks. The experiment utilized datasets from motion and optics laboratories, where sensor-based measurements were analyzed using supervised and unsupervised learning models. Data preprocessing, feature extraction, and model validation were implemented through Python-based frameworks such as TensorFlow and Scikit-learn. The results demonstrated that AI-assisted data analysis significantly enhanced the precision of measurement interpretation, reduced error margins by 15–20% compared to conventional methods and identified hidden patterns within complex datasets that were previously difficult to detect through manual analysis. Moreover, neural network models proved highly effective in predicting outcomes of nonlinear systems, particularly in optics and electromagnetism experiments. The study also revealed that the integration of AI not only accelerates data processing but also serves as an educational tool to promote computational thinking among physics students. It is recommended that modern physics laboratories adopt AI-based analytical frameworks as a standard complement to traditional methods, supported by training modules that familiarize students with data-driven experimentation. This integration is expected to strengthen the alignment between physics education and emerging technologies, ultimately fostering innovation and interdisciplinary competence among future physicists.
Peningkatan Produktivitas Kebun Hidroponik Pagifarm Bogor melalui Implementasi Pembangkit Listrik Tenaga Surya Berbasis IoT Prayogi, Soni; RDR, Raden; Larasati, Ismah Aulia; Abdillah, Muhammad; Rozamuri, Arif Murti
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.
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 Dadan Hamdani, Dadan Darminto . Darminto Darminto Darminto Darminto Darminto Darminto Darminto Darminto Elmi Mahzum Fauzi Ahmad Muda Fitria Silviana 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 I Nur Fajar Imammah, Sofyah Irgi Faturrahman Ketut Saha Kesta Dinatha Larasati, Ismah Aulia 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 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. RDR, Raden Rizky Agung Ramadhan Roong, Inggrid IO Rozamuri, Arif Murti Safira Luthfia Saminan Saminan 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 Wibowo, Wahyu K. Wibowo, Wahyu Kunto Yoyok Cahyono Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin* Zapata, Malvin