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All Journal JOIV : International Journal on Informatics Visualization Journal of Robotics and Control (JRC) Humanism : Jurnal Pengabdian Masyarakat International Journal of Robotics and Control Systems Decode: Jurnal Pendidikan Teknologi Informasi Journal of Software Engineering and Information System (SEIS) Jurnal Riset Sistem dan Teknologi Informasi Jurnal Pengabdian kepada Masyarakat (PEMAS) Scientific Journal of Computer Science
Dianda Rifaldi
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Religion Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Other

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Machine Learning 5.0 In-depth Analysis Trends in Classification Dianda Rifaldi; Tri Stiyo Famuji; Setiawan Ardi Wijaya; Ahmed Jaber Abougarair; Phichitphon Chotikunnan; Alfian Ma'arif; Furizal
Scientific Journal of Computer Science Vol. 1 No. 1 (2025): June
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjcs.v1i1.2025.18

Abstract

In the era of Technology 5.0 Machine Learning continues to show significant advancements across various sectors. This study aims to examine the latest trends in Machine Learning classification, focusing on four key approaches Explainable Artificial Intelligence, Federated Learning, Transfer Learning, and Generative Adversarial Networks. The methodology involves a comprehensive literature review of research in Asia and experimentation with related datasets. The findings indicate that Explainable Artificial Intelligence enhances transparency and accuracy in data classification, Federated Learning enables decentralized learning while safeguarding data privacy, Transfer Learning improves accuracy with small datasets, and Generative Adversarial Networks aids in data augmentation for better model training. In conclusion, these techniques not only enhance the efficiency and accuracy of classification but also open up new opportunities for innovation in various fields, including healthcare, transportation, and cybersecurity.
Co-Authors Abdul Fadlil Abdul Fadlil Abdul Fadlil Ahmed Jaber Abougarair Alfian Ma’arif Asno Azzawagama Firdaus Bella Okta Sari Miranda Fanani, Galih Fanani, Galih Pramuja Inngam Fauzan Purma Ramadhan Furizal Furizal, Furizal Herman Herman, - Iriene Putri Mulyadi Mulyadi, Iriene Putri Murinto Phichitphon Chotikunnan Ramadhan, Fauzan purma Saputra, Vanji Tri Stiyo Famuji Tristanti, Novi Vanji Saputra Vanji Saputra6 Wijaya, Setiawan Ardi