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All Journal Jurnal Teknik Mesin, Industri, Elektro dan Informatika Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Prosiding Seminar Nasional Ilmu Pendidikan
Fiana Fiana
Universitas Sultan Ageng Tirtayasa
Aerospace Engineering Arts Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Public Health Social Sciences

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Pengujian Kinerja Jaringan Topologi STAR dengan Switching: Studi Simulasi Menggunakan Cisco Packet Tracer Ardian Nurarifin; Rachmatul Hidayathika; Fiana Fiana; Rafika Desfiana; Didik Aribowo
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 2 No. 3 (2024): Mei : Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupiter.v2i3.315

Abstract

In the present day, many have used communication tools to share data as text, video, images, or sound and the like. There is a speed of data transmission depending on the delivery method, if there is a system error then the data is likely not to be sent, therefore there are various types of data managers so that there are no obstacles or errors during the data transmission process. The star topology was chosen for its advantages in network management, trouble shooting and providing reliable and easy-to-organize connectivity. The main focus is to evaluate the efficacy and effeciency of the star topology in handling different amounts of data traffic using performance characteristics including packet loss, jitter, delay, and throughput. And the use of switching in the star topology can provide optimal and stable performance under high traffic load can provide reliability and efficiency in data traffic management.
Inovasi Transportasi Modern: Pemanfaatan Medan Elektromagnetik pada Kereta Maglev dan Kendaraan Listrik Fiana Fiana; Rafika Desfiana; Muhammad Rifki Arrosyid; Muhammad Rosyid Ridho; Diyajeng Luluk Karlina
Jurnal Teknik Mesin, Industri, Elektro dan Informatika Vol. 3 No. 4 (2024): Desember : JURNAL TEKNIK MESIN, INDUSTRI, ELEKTRO DAN INFORMATIKA
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jtmei.v3i4.4535

Abstract

The introduction of electromagnetic devices into modern transportation has revolutionized mobility and enabled more rapid, efficient, and reliable solutions. This study examines the use of electromagnetic devices in Maglev and listrik (EV) keretas. Utilizing magnetic levitasi, EV uses electromagnetic principles to propel its hemat energy, whereas Maglev achieves high-speed transportation with low force. This study identifies key technologies, their benefits, and challenges in implementing the system in question. It also examines the system's global impact on energy consumption and environmental degradation. All of this indicates that more extensive innovation and investment in electromagnetic transportation can speed up transitions to ramah lingkungan mobility.
Analisis Pemanfaatan Teknologi Digital dalam Pemeliharaan Sistem Tenaga Listrik: Literature Review terhadap Implementasi Predictive Maintenance Fiana Fiana; Ardian Nurarifin; Muhamad Taufiq Hidayatullah Syari; Muhamad Rifki Arrosyid; Didik Aribowo
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.v3i1.219

Abstract

The rapid advancement of digital technologies has transformed maintenance practices in electric power systems, encouraging a shift from conventional approaches toward predictive maintenance strategies. This study examines the role of digital technologies in supporting predictive maintenance through a comprehensive literature review. The research was conducted by analyzing scientific journals, conference papers, and scholarly articles discussing the application of Internet of Things (IoT), Artificial Intelligence (AI), machine learning, SCADA, and digital twin technologies in power system maintenance. The review indicates that predictive maintenance contributes to improved system reliability, reduced equipment downtime, lower maintenance expenditures, and enhanced operational efficiency through continuous monitoring and data-based decision making. Furthermore, digital technologies facilitate earlier fault identification and more effective maintenance scheduling. Despite these benefits, several challenges remain, including cybersecurity concerns, investment requirements for digital infrastructure, and the need for skilled personnel. The findings of this study provide insights that may support the development of more intelligent, efficient, and reliable power systems in the future.
Co-Authors Ardian Nurarifin Didik Aribowo Diyajeng Luluk Karlina Muhamad Rifki Arrosyid Muhamad Taufiq Hidayatullah Syari Muhammad Rifki Arrosyid Muhammad Rosyid Ridho Rachmatul Hidayathika Rafika Desfiana