Article Per Year (5 Year)
p-Index From 2021 - 2026
4.741
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Jurnal Informatika dan Teknik Elektro Terapan JURNAL KAJIAN TEKNIK ELEKTRO KACANEGARA Jurnal Pengabdian pada Masyarakat PRoMEDIA IJID (International Journal on Informatics for Development) Jurnal Informatika dan Rekayasa Perangkat Lunak ILKOMNIKA: Journal of Computer Science and Applied Informatics Jurnal Riset Teknologi Pencegahan Pencemaran Industri JCOMENT (Journal of Community Empowerment) Berdikari : Jurnal Pengabdian kepada Masyarakat Jurnal Ilmiah Ilmu Terapan Universitas Jambi KAMI MENGABDI Prosiding Seminar Nasional Rekayasa dan Teknologi (TAU SNAR- TEK) Mengabdi: Jurnal Hasil Kegiatan Bersama Masyarakat PANDAWA : Jurnal Pengabdian kepada Masyarakat
Wijonarko, Panji
Universitas 17 Agustus 1945 Jakarta
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Social Sciences Transportation Other

Published : 34 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 34 Documents
Search

 1   2   3   4 
Water Meter Detection System Using YOLOv11 with Variations in Image Augmentation Techniques and Integrated into Telegram Rajes Khana; Muhammad Sobirin; Ahmad Rofii; Panji Wijonarko; Bobby Arvian James; Rheza Shangajie
Jurnal Riset Teknologi Pencegahan Pencemaran Industri Vol. 17 No. 1 (2026): May
Publisher : Balai Besar Standardisasi dan Pelayanan Jasa Pencegahan Pencemaran Industri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21771/jrtppi.2026.v17.no1.p84-93

Abstract

While accurate water management is crucial for public utilities, manual meter reading remains inefficient due to recording errors and high operational costs. This study proposes an automatic water meter reading detection system based on YOLOv11 with a variety of image augmentation techniques integrated into Telegram. The dataset was obtained through a combination of ESP32-CAM image captures and online sources totaling 1,207 images, followed by labeling on Roboflow and augmentation in the form of flipping, rotation, saturation, and noise. The YOLOv11 model was trained on Google Colab using an A100 GPU with 100 epochs. Performance evaluation was conducted using Precision, Recall, mAP50, and mAP50-95 metrics. The results showed that the application of augmentation significantly improved model performance, with Precision of 95.9%, Recall of 98.2%, and mAP50 of 97.4%. The combination of four augmentation techniques produced the highest mAP50-95 value of 0.575, indicating the model's robustness against variations in field conditions. The system is also capable of automatically sending detection result notifications via Telegram, enabling its implementation for real-time remote monitoring. Compared to previous studies with YOLOv4 and YOLOv5, this approach proved to be superior in terms of accuracy and efficiency. These findings indicate that the integration of YOLOv11 with image augmentation techniques and IoT support has the potential to be an optimal solution in the modernization of digital water meter reading.
The WASPAS Method in Determining BSM Recipients Objectively Tundo Tundo; Panji Wijonarko; Muhammad Raffiudin
IJID (International Journal on Informatics for Development) Vol. 12 No. 1 (2023): IJID June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri (UIN) Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2023.4089

Abstract

This research was conducted due to complaints from several parents regarding the determination of BSM at SDN Karanganyar 02 which still contains subjectivity in its selection so that some students are less fortunate. SDN Karanganyar 02, once a year always carries out activities related to determining the selection of BSM recipients. With this activity, it is hoped that students who are underprivileged but have fairly good achievements can receive this BSM so that the activities they carry out do not feel burdened with financial needs. The fact is that in institutions there are still many students who do not get BSM, even though according to the requirements these students should be eligible to get BSM. So in the selection that occurs there is a very irrational subjectivity. To solve this problem, the researcher tries to make a solution through an application that applies the Weight Aggregated Sum Product Assessment (WASPAS) method, which is a method of determining with predetermined criteria. The criteria in question are activities, achievements, report cards, parental income, home conditions, and parental dependents. After analyzing and implementing the WASPAS Decision Support System, it was found that the results were detrimental to students where the criteria scores and final determination were lower than some other students, but the SD carried out an assessment by obtaining BSM. To prevent this incident from recurring, WASPAS is very capable of answering objective determinations with the results obtained at 79.88% and the previous subjective determination at 20.12%.
PENGENALAN VIRTUALISASI DAN IMPLEMENTASI OWNCLOUD SEBAGAI STORAGE SERVER PADA SMA WIJAYA KUSUMA JAKARTA UTARA Panji Wijonarko; Muhammad Maulana Yusuf; Ath Thaariq; Muhammad Akbar Firdaus; Ilham Dwi Cahya; Raihan Putra Pratama; Rajes Khana
BERDIKARI Vol 8, No 2 (2025): Jurnal Berdikari
Publisher : Universitas 17 Agustus 1945 Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52447/berdikari.v8i2.9023

Abstract

Saat ini, lembaga pendidikan dituntut untuk mengadopsi teknologi terbaru agar bisa mengelola data dan informasi dengan lebih efisien dan efektif. Di Indonesia, banyak sekolah, salah satunya SMA Wijaya Kusuma Jakarta Utara, menghadapi masalah dalam manajemen data yang semakin kompleks. Proyek Pengabdian kepada Masyarakat berjudul Pengenalan Virtualisasi dan Implementasi OwnCloud sebagai Storage Server pada SMA Wijaya Kusuma. Proyek pengabdian masyarakat ini menerapkan virtualisasi server menggunakan virtual box dan menggunakan OwnCloud sebagai server penyimpanan. Hasil Pengabdian telah berhasil memenuhi target yang direncanakan. Virtualisasi telah berhasil dibuat di perangkat komputer sebagai server lokal menggunakan virtual box, di mana owncloud juga dapat berjalan pada server virtualisasi yang dibangun. Pengujian terhadap OwnCloud dalam menambah folder, mengupload file, dan juga akses melalui jaringan lokal juga berhasil di jalan. Hal ini membuktikan bahwa SMA Wijaya Kusuma Jakarta, dapat membangun sendiri server penyimpanan data berbasis OwnCloud. Hasil Pengukuran Kuesioner menunjukkan 70% peserta puas ,60% peserta paham terhadap materi yang diberikan, 75% peserta baik guru maupun siswa setuju bahwa peserta mendapatkan ilmu atau pengetahuan dari pengabdian yang dilakukan
AN EVENT DRIVEN FRAMEWORK INTEGRATING RANDOM MATRIX THEORY AND DEEP LEARNING FOR ACTIVE VOLTAGE CONDITIONER INSTALLATION DECISION IN ELECTRICAL DISTRIBUTION SYSTEMS Rofii, Ahmad; Wijonarko, Panji; Sobirin, Muhammad; Kristyawati, Desy
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 10 No. 4 (2026): Volume 10, Nomor 4, August 2026
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v10i4.55945

Abstract

Voltage sags are frequent disturbances in industrial power systems that can disrupt system operations and cause equipment malfunctions. The proposed framework integrates Random Matrix Theory (RMT) to identify disturbance patterns. It evaluates the severity, vulnerabilities, and operational impact of voltage sag events using the Information Technology Industry Council (ITIC) curve. This research uses event data, disturbance type, associated equipment, disturbance duration, and three-phase voltage measurements to predict the temporal evolution of ITIC conditions in pattern disturbance dynamics. Deep learning models, namely Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), are then employed to predict the temporal evolution of ITIC conditions. Based on power metering unit measurements, the observed voltage variations were non-linear, yet the RMT stability index (Ψ) remained within ITIC tolerance limits. The severity of stability disturbances was successfully evaluated, and the GRU model demonstrated superior predictive performance compared to the LSTM model. Consequently, the industry requires an AVC system—aligned with the combined stability-severity-risk paradigm and the prediction results—to effectively mitigate voltage compensation risks through precise AVC operation. These findings demonstrate that integrating RMT-based fault analysis, ITIC-based severity assessment, and deep learning-based prediction offers a more systematic and predictive approach to voltage sag assessment than relying solely on empirical evaluation. Consequently, this enables more accurate determination of AVC installation requirements, thereby effectively mitigating faults. The implication is a shift in how AVC requirements are assessed—moving from a reactive to a predictive approach—thereby reducing the risk of inadequate or unnecessary compensation.
Co-Authors Abdus Salam, Abdus Ahmad Rofii Ahmad Rofii Ahmad Rofii Akbar, Rasyan Almeida, Giovani Costa Amalia Zahra Arestio, Revansyah Arvian James, Bobby Ath Thaariq Berliana, Niken Bimbang Agus Purnomo Bobby Arvian James Burhanudin Burhanudin Cahya, Ilham Dwi Da Conceição, Giovani Costa Almeida Danang Trijayanto Devin, Jonatan Diana Laila Rahmatillah Gatra, Rahmadhan Hamdala, Marcia Rizky Herlina Muzanah Zain Ilham Dwi Cahya Ismawati, Oktavioni James, Bobby James, Bobby Arvian Jibril, Mohammad Khana, Rajes Khoirunnisa Khoirunnisa Kristyawati, Desy Lia Aprilia Lopes, Fatima Odelia Lutfi Ramadhan, Muhammad M Fajri Hidayat Maharani, Shinta Aulia Marchella, Shelly Mufit, Choirul Muhammad Akbar Firdaus Muhammad Maulana Yusuf Muhammad Raffiudin Muhammad Sobirin Muhammad Sobirin Mumtaz, Muhammad Reynaldi Nia Rahmawati, Nia Nova, Rhama Viandra Nurulah, Ilyas Yasin Pratama, Dean Purwati Purwati Putri, EE Lailatul Rabima Rabima Rachman, Muhammad Afif Raffiudin, Muhammad Raihan Putra Pratama Rajes Khana Rajes Khana Rajes Khana Ramadhan, Leo Berliandri Ramadhan, Muhamad Lutfi Ramadhan, Muhammad Lutfi Rangki Astiani Rasyan Akbar Rheza Shangajie Ridwan, Jauhan Nuari Rizky Hamdala, Marcia Rohmad Dwi Cahya Rumbiak, Almendo Renal Yustus Sari, Silvia Agustina Wulan Sarifudin, Maulana Setiawan, Aditia Pernando Sri Endah Susilowati Tampubolon, Parlindungan Tasti, Andi Thalita Thaariq, Ath Thoriq, Daffa Raihan Tundo, Tundo Ulfah Fatmala Rizky Wagiman, Wagiman Wawan Iswanto Widagdo, Kristian Widiono Kusumo Wulan Sari, Silvia Agustina yusuf, muhammad maulana Zailanti, Nabila Reva Zain, Zahra Nasywa Zalianti, Nabila Reva