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All Journal Prosiding Seminar Nasional Ilmu Pendidikan Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer
Novaldi Ramdani Reza
Unknown Affiliation
Arts Computer Science & IT Economics, Econometrics & Finance Education Public Health Social Sciences

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Pemanfaatan Medan Elektromagnetik dalam Teknologi Pengobatan Modern Novaldi Ramdani Reza; Rovino Alghafari; Errisa Zulqa Deswana; Muhammad Rifqi; Diyajeng Luluk Karlina
Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 2 No. 6 (2024): Desember: Mars: Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v2i6.496

Abstract

The utilization of electromagnetic fields (EMF) in modern medical technology has become a significant focus of research. This study aims to explore the therapeutic effects of EMF, especially at low frequencies (ELF) and Pulsed Electromagnetic Fields (PEMF), in enhancing the healing of various medical conditions. The method used is a literature study by analyzing various sources from Google Scholar, Science Direct, and PubMed. The results showed that EMF therapy is effective in relieving pain, accelerating tissue healing, and improving the quality of life of patients with musculoskeletal disorders and fractures. Despite the many benefits, it is important to consider the potential health risks of long-term exposure to EMF. This study recommends the development of strict regulations and training for medical personnel to ensure the safe and effective use of EMF.
Penerapan VPN Dalam Topologi Star Untuk Keamanan Pengiriman Data Tiara Pramesti Wulandari; Novaldi Ramdani Reza; Errisa Zulqa Deswana; Muhammad Rifqi Adillah; Didik Aribowo
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 2 No. 2 (2024): Mei: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v2i2.93

Abstract

Building a computer network needs significant care in selecting a configuration to ensure its efficacy and efficiency. It involves decisions about network topology, types, and device use. Security measures are essential for protecting networks with internet access from external attacks. A study conducted at an Islamic university in Indonesia indicated the use of a star network architecture and a client-server network model. The servers utilize Debian Linux. The university's security infrastructure includes a server authentication system and the setting up of a Virtual Private Network (VPN). If the server authentication difficulty is caused by a power outage, it is recommended that you use an UPS (uninterruptible power supply) to preserve power stability. Overall, security methods show up to be more effective when firewalls are installed.
Systematic Literature Review Penerapan Artificial Intelligence dalam Pemeliharaan Prediktif Sistem Tenaga Listrik sebagai Inovasi Pembelajaran Berbasis Teknologi Digital Rachmatul Hidayathika; Zada Aulia Munawarah; Umar Hamzah; Didik Aribowo; Novaldi Ramdani Reza
Prosiding Seminar Nasional Ilmu Pendidikan Vol. 3 No. 1 (2026): Juni: Prosiding Seminar Nasional Ilmu Pendidikan
Publisher : Asosiasi Riset Ilmu Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/prosemnasipi.v3i1.220

Abstract

Artificial Intelligence (AI) has become an important technology in predictive maintenance of power systems due to its ability to improve reliability, efficiency, and asset management. Conventional maintenance approaches, such as corrective and preventive maintenance, often fail to accurately predict equipment failures, resulting in higher operational costs and unplanned outages. This study aims to analyze the development, applications, benefits, challenges, and future directions of AI in predictive maintenance of power systems. The research employed a Systematic Literature Review (SLR) based on the PRISMA framework. Literature was collected from Google Scholar using keywords related to artificial intelligence, predictive maintenance, machine learning, fault diagnosis, condition monitoring, and power systems. A total of 22 publications published between 2020 and 2025 met the inclusion criteria and were analyzed. The findings indicate that AI plays a significant role in fault detection, fault diagnosis, condition monitoring, and remaining useful life prediction of power equipment. AI has been widely applied to transformers, generators, switchgear, Photovoltaic Systems, and variable frequency drives. Furthermore, the integration of AI with IoT, Big Data Analytics, Cloud Computing, and Digital Twin technologies enhances predictive accuracy and maintenance decision-making. Overall, AI contributes significantly to improving the reliability, efficiency, and sustainability of future power systems.
Co-Authors Didik Aribowo Diyajeng Luluk Karlina Errisa Zulqa Deswana Muhammad Rifqi Adillah Rachmatul Hidayathika Rifqi Muhammad Rovino Alghafari Tiara Pramesti Wulandari Umar Hamzah Zada Aulia Munawarah