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All Journal JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOIV : International Journal on Informatics Visualization JOURNAL OF ELECTRICAL AND SYSTEM CONTROL ENGINEERING Jurnal Ilmiah FIFO TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika IJAIT (International Journal of Applied Information Technology) JATI (Jurnal Mahasiswa Teknik Informatika) Journal of Computer, Electronic, and Telecommunication (COMPLETE) Jurnal Ilmiah Teknik Elektro eProceedings of Engineering Jurnal Ilmiah Agroust SWAGATI: Journal of Community Service
Suryo Adhi Wibowo
Universitas Telkom
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Journal : eProceedings of Engineering

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Performance Analysis Of Class Rebalancing Self-Training Framework For Imbalanced Semi-Supervised Learning Alvaro Septra Dominggo Nauw; Suryo Adhi Wibowo; Casi Setianingsih
eProceedings of Engineering Vol 10, No 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstract

This research aims to analyze the effectiveness ofthe Class-Rebalancing Self-Training (CReST) method in semisupervisedlearning (SSL) on class-imbalanced data. The studyuses the CIFAR 10 long-tailed dataset to test the performance ofSSL with CReST using Python programming language on theGoogle Colab platform. The results showed that CReSTeffectively reduces pseudo-labels in the majority class andincreases recall in the minority class, with the best performanceachieved at Generation 16. However, there was a decrease inAverage Accuracy Recall per Class after Generation 16. Thestudy suggests addressing the over-sampling issue and exploringthe application of the CReST framework in other areas ofmachine learning and AI.Kata kunci— CReST, Semi-Supervised Learning, imbalancedata, pseudo label, Semi-Supervised Learning Generation
Co-Authors Achmad Rizal Agniya Tazkiya Aulia Agus Pratondo Akhmad Yusuf Nasirudin Aldo Tripolyta Alvaro Septra Dominggo Nauw Angga Rusdinar Anky Aditya P Annisa Istiqomah Atina Nur Azizah Bambang Hidayat Bambang Hidayat Bambang Setia Nugroho Bambang Setia Nugroho Casi Setianingsih Choiron Rosadi Dany Eka Saputra Devita Rahma Apriliani Dien Rahmawati Dini Himmah Al Aliyyah Al Aliyyah Djoko Heru Pamungkas Dwiki Kurniawan Dyah Avita Sari Fahmi Oscandar Fahmi Oscandar Faiz Nashrullah Farah Hana Kusumaputri Felix Corputty Fiky Yosef Suratman Fityanul Akhyar Gelar Budiman Hanaluthfina Nurhadiati Hashfi Fadhillah Hesty Susanti Husneni Mukhtar Iwan Iwut Tritoasmoro Jangkung Raharjo Joseph Dedy Irawan Koredianto Usman Kusnahadi Susanto Kusuma Nindia Rizki Ledya Novamizanti Liyana Faiza Lulud Annisa Ainun Mahmuddah Lyra Vega Ugi Muhammad Alief Hidayah Baso Muthia Saada Nadya Sindi Safitri Oriza Intani Prasaja Wibawa Utama Putri Utami Hafgianti Raditiana Patmasari Ricky Hilmi Sudrajad Rissa Rahmania Rissa Rahmania Rissa Rahmania Rissa Rahmania Rita Purnamasari Tembang Florian Falah Teuku Zulkarnain Muttaqien Viky Premeita Mitayani Vivian Alfionita Sutama Wahmisari Priharti Willy Anugrah Cahyadi Wiwit Ratri Wulandari Yacobus Sunaryo Yurika Ambar Lita Yuti Malinda