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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) Majalah Ilmiah Teknologi Elektro 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) 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 Majalah Ilmiah Teknologi Elektro Jurnal Teknik AMATA Jurnal Pendidikan MIPA
Prayogi, Soni
Department Of Electrical Engineering, Faculty Of Industrial Engineering, Pertamina University, Jakarta 12220 Indonesia
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The Effect of Addition of SnO2 Doping on The Electronic Structure of TiO2 Thin Film as Photo-Anode in DSSC Applications Prayogi, Soni; Marzuki, Marza Ikhsan
Journal of Emerging Supply Chain, Clean Energy, and Process Engineering Vol 1 No 1 (2022): Journal of Emerging Supply Chain, Clean Energy, and Process Engineering
Publisher : Universitas Pertamina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57102/jescee.v1i1.3

Abstract

Photoanode is a component of the dye-sensitized solar cell (DSSCc) which is synthesized from metal oxide semiconductor material with nanoparticle size deposited on transparent conductive glass. TiO2 powder was synthesized by mixing 20 mL of Titanium (III) chloride (TiCl3) with 100 mL of the equator and stirred for 1 hour. TiO2-SnO2 thin films have been successfully synthesized using the coprecipitation method and coated on ITO (Indium Tin Oxide) substrate by doctor-blade technique. The structure and morphology of the films were investigated by XRD and SEM respectively. The analysis of optical characteristics shows that the absorbance of TiO2 photoanode is in the wavelength range of 300-600 nm while SnO2 is in the wavelength range of 300-870 nm. The results showed that the synthesized film with SnO2 had a stronger anatase formation than the film with pure TiO2. Finally, incorporating SnO2 into the TiO2 matrix is an effective strategy to improve the overall properties of solar cells in future applications
Resistor and Capacitor Time Constant Measuring Instrument Using Arduino UNO Prayogi, Soni; Silviana, Fitria; Saminan, Saminan
Jurnal Ilmiah Pendidikan Fisika Al-Biruni Vol 12 No 1 (2023): Jurnal Ilmiah Pendidikan Fisika Al-Biruni
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/jipfalbiruni.v12i1.15323

Abstract

The most interesting problem to be discussed in electrical physics is one-way electric circuits. In this work, the researchers constructed an experimental setup for determining the time constant of DC resistors and capacitors using the open-source Arduino UNO hardware platform. Arduino UNO was a signal generator for data collection systems and a simple signal visualization instrument. Experiments were carried out using an analog oscilloscope combined with theoretical calculations. The results show that, on a spreadsheet, the data processing and fitting of the curves for the six Resistor and Capacitor test sets yielded values determined by the component tolerances. The researchers believe that the design of this equipment and software demonstrates the recommended suitability, making it flexible for use in teaching and learning in laboratory contexts.
Firefly-Based MPPT System Design for Wind Energy Efficiency Enhancement in Remote Areas Prayogi, Soni
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
Implementasi Sistem Terintegrasi Pada Penyimpanan Fotovoltaik Dalam Satu Perangkat Maulana, Rifqi; Anandra, Muhammad F; Alfredo, Andromeda J; prayogi, soni
Jurnal Teknologi Elektro Vol 16, No 1 (2025)
Publisher : Electrical Engineering, Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jte.2025.v16i1.005

Abstract

Penelitian ini bertujuan untuk mengembangkan dan menguji sistem terintegrasi penyimpanan energi fotovoltaik dalam satu perangkat, guna meningkatkan efisiensi dan efektivitas konversi serta penyimpanan energi surya. Dalam penelitian ini, kami merancang sebuah perangkat yang menggabungkan panel fotovoltaik dengan sistem penyimpanan energi berbasis baterai lithium-ion, dilengkapi dengan pengendali daya pintar. Sistem ini dirancang untuk mengoptimalkan penyerapan energi matahari dan penyimpanannya, serta mengurangi kehilangan energi selama proses konversi dan penyimpanan. Proses fabrikasi melibatkan pemilihan material fotovoltaik yang efisien dan komponen penyimpanan yang memiliki densitas energi tinggi serta umur pakai yang panjang. Pengendali daya pintar dikembangkan untuk mengelola distribusi energi secara real-time, memastikan ketersediaan daya sesuai kebutuhan, dan meminimalkan kerugian akibat overcharging atau deep discharging. Pengujian dilakukan dalam kondisi lingkungan yang bervariasi untuk menilai kinerja sistem dalam situasi nyata. Hasil eksperimen menunjukkan bahwa sistem terintegrasi ini mampu meningkatkan efisiensi penyimpanan hingga 20% dibandingkan dengan sistem konvensional yang terpisah. Selain itu, sistem ini juga menunjukkan peningkatan stabilitas operasi dan pengurangan biaya instalasi serta pemeliharaan. Penelitian ini memberikan kontribusi signifikan terhadap kemajuan teknologi penyimpanan energi terbarukan dan menawarkan solusi praktis untuk mengatasi tantangan penyimpanan energi yang berkelanjutan dan efisien
Optimasi MPPT pada Sistem Turbin Angin Nonlinear Menggunakan Firefly Algorithm Prayogi, Soni
Techno.Com Vol. 24 No. 3 (2025): Agustus 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i3.13068

Abstract

Penelitian ini membahas pendekatan optimasi Maximum Power Point Tracking (MPPT) pada sistem turbin angin nonlinier menggunakan Firefly Algorithm (FA). Karakteristik nonlinier turbin angin, yang disebabkan oleh fluktuasi kecepatan angin serta interaksi mekanik dan elektrik, menjadi tantangan utama dalam proses ekstraksi daya maksimum. Metode MPPT konvensional sering mengalami keterbatasan dalam hal kecepatan konvergensi dan akurasi pelacakan pada kondisi angin yang dinamis. Oleh karena itu, penelitian ini mengusulkan penggunaan algoritma FA, yaitu algoritma optimasi metaheuristik yang terinspirasi dari perilaku cahaya kunang-kunang, untuk meningkatkan performa MPPT. Sistem konversi energi angin dimodelkan secara matematis dengan mempertimbangkan sifat nonlinier, dan FA digunakan untuk menyesuaikan duty cycle konverter guna mencapai titik daya maksimum secara efisien. Hasil simulasi pada lingkungan MATLAB/Simulink menunjukkan bahwa metode MPPT berbasis FA mampu meningkatkan akurasi pelacakan dan waktu respon dibandingkan dengan metode tradisional seperti Perturb and Observe (P&O) dan Incremental Conductance (IncCond). Metode yang diusulkan juga menunjukkan ketahanan terhadap perubahan kondisi angin dan dinamika sistem. Hasil penelitian ini menunjukkan bahwa Firefly Algorithm merupakan solusi yang menjanjikan untuk optimalisasi sistem energi angin nonlinier dan mendukung efisiensi teknologi energi terbarukan.   Kata kunci: MPPT, Turbin Angin Nonlinear, Firefly Algorithm, Optimasi, Energi Terbarukan.
Perancangan Sistem Monitoring Android-IoT yang Efisien untuk Solar Charge Controller MPPT Epever berbasis Modbus RTU A, Muhammad; Prayogi, Soni
Techno.Com Vol. 24 No. 3 (2025): Agustus 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i3.13438

Abstract

Permintaan terhadap energi terbarukan terus meningkat, sehingga diperlukan sistem monitoring yang efisien dan dapat diakses secara real-time untuk memastikan kinerja yang optimal. Penelitian ini mengimplementasikan sistem monitoring berbasis Internet of Things (IoT) dengan antarmuka Android pada solar charge controller MPPT merek Epever. Alasan utama pemilihan topik ini adalah keterbatasan aksesibilitas dan minimnya tampilan antarmuka pengguna pada sistem monitoring konvensional. Sistem ini menggunakan NodeMCU ESP8266 sebagai penghubung komunikasi antara solar charge controller dan aplikasi Android melalui jaringan Wi-Fi. Parameter yang dimonitor meliputi tegangan baterai, tegangan panel surya, arus, dan status pengisian daya, yang ditampilkan secara real-time pada perangkat Android. Metode yang digunakan mencakup perancangan sistem, integrasi perangkat keras dan perangkat lunak, serta pengujian performa di berbagai kondisi intensitas cahaya matahari. Hasil pengujian menunjukkan bahwa sistem mampu menampilkan data secara akurat dengan jeda waktu yang rendah, serta meningkatkan kemudahan pengguna dalam memantau kinerja sistem. Kesimpulannya, sistem ini memberikan solusi monitoring yang murah, portabel, dan mudah dikembangkan untuk sistem energi surya, serta berkontribusi dalam pengelolaan energi yang cerdas dan berkelanjutan. Kontribusi utama penelitian ini adalah pengembangan sistem monitoring yang efisien dan portabel berbasis Android-IoT menggunakan komunikasi Modbus RTU, yang belum banyak digunakan pada sistem serupa. Dibandingkan dengan sistem monitoring konvensional, sistem ini menunjukkan peningkatan efisiensi dalam hal latensi, konsumsi daya, dan aksesibilitas pengguna.   Kata kunci: Internet of Things, Solar Charge Controller, MPPT Epever, Monitoring Real-Time.
Deteksi Otomatis Penggunaan APD pada Pekerja Migas Menggunakan Deep Learning dan Computer Vision Tan, Dennis; Prayogi, Soni
Techno.Com Vol. 24 No. 3 (2025): Agustus 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i3.13449

Abstract

Industri minyak dan gas (migas) merupakan sektor dengan risiko kerja tinggi yang memerlukan penerapan prosedur keselamatan secara ketat, termasuk penggunaan Alat Pelindung Diri (APD) oleh pekerja. Namun, pengawasan penggunaan APD secara manual masih memiliki keterbatasan dari sisi efisiensi dan keakuratan, terutama di area kerja luas dan kompleks. Permasalahan ini mendorong perlunya sistem otomatis yang mampu mendeteksi pemakaian APD secara real-time dan akurat. Penelitian ini mengusulkan implementasi teknologi Computer Vision berbasis Convolutional Neural Network (CNN) untuk mendeteksi penggunaan APD pada pekerja di lingkungan industri migas. Sistem yang dibangun memanfaatkan dataset citra pekerja dengan berbagai variasi APD seperti helm, rompi, dan masker, yang kemudian dilatih menggunakan arsitektur CNN untuk mengenali atribut keselamatan tersebut. Hasil pengujian menunjukkan bahwa model CNN yang digunakan mampu mencapai akurasi deteksi hingga 94,2% pada data uji, dengan performa yang konsisten dalam berbagai kondisi pencahayaan dan posisi kamera. Sistem ini juga mampu mendeteksi ketidaksesuaian penggunaan APD dalam waktu kurang dari satu detik per frame, sehingga dapat diterapkan untuk kebutuhan monitoring secara real-time. Dengan demikian, solusi ini berpotensi meningkatkan efektivitas pengawasan keselamatan kerja dan mengurangi risiko kecelakaan di industri migas secara signifikan. Penelitian ini membuka peluang pengembangan lebih lanjut pada aspek integrasi dengan sistem pengawasan industri berbasis IoT dan peningkatan generalisasi model pada berbagai jenis lingkungan kerja. Kata kunci: Computer Vision, Convolutional Neural Network (CNN), Alat Pelindung Diri (APD).
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 (In Press)
Publisher : ISB Atma Luhur

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

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 errors, especially in expansive and intricate work settings. To address this challenge, there is a growing demand for an intelligent system capable of detecting PPE usage accurately and instantaneously. 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 comprising images of workers equipped with different types of PPE, such as 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 detection accuracy of 94.2% on validation data and maintains reliable performance across varying lighting and camera angles. Moreover, the system is capable of identifying PPE violations in under one 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—an area that has seen limited exploration in existing literature.
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 Fitria Silviana Frisca Elfrisa Nainggolan Gatut Yudoyono Gatut Yudoyono Giganta Rose Kakke Hartanxia Hartanxia Herminarto Nugroho Hidayat, Robi T I Nur Fajar Imammah, Sofyah Irgi Faturrahman Ketut Saha Kesta Dinatha Mahzum, Elmi Marza Ihsan 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 Nugroho, Herminarto Nugroho, Irvan A Nugroho, Teguh A Nugroho, Teguh Aryo Nur Fajar, Iqbal Nurul Aufa Pertiwi, Nita Indriani Pramudito, Wahyu Agung Pratama, Aldi Putra, Yehezkiel P. Rizky Agung Ramadhan Roffi, Teuku Muhammad Roong, Inggrid IO Safira Luthfia Saminan Saminan Saminan Saminan Saminan Saminan Saminan, Saminan Saputra , Duta M W Silviana, Fitria Sirait, Juanto Syahrul Ghufron Tan, Dennis Tarmizi Hamid Teguh Aryo Nugroho Teuku Muhammad Roffi Wahyu Agung Pramudito Wahyu Agung Pramudito Wahyu Kunto Wibowo Wibowo, Wahyu K. Wibowo, Wahyu Kunto Yoyok Cahyono Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin Zainuddin* Zapata, Malvin