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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi IPTEK The Journal for Technology and Science Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) CommIT (Communication & Information Technology) Jurnal Ilmiah Kursor Prosiding SNATIKA Vol 01 (2011) Jurnal Sistem dan Informatika EKOMBIS REVIEW: Jurnal Ilmiah Ekonomi dan Bisnis MIX : Jurnal Ilmiah Manajemen Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Indonesian Journal of Information System Jurnal Eksplora Informatika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer WIDYABHAKTI Jurnal Ilmiah Populer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) CSRID (Computer Science Research and Its Development Journal) CCIT (Creative Communication and Innovative Technology) Journal SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Buletin Ilmiah Sarjana Teknik Elektro Journal of Robotics and Control (JRC) Journal of Applied Data Sciences International Journal of Robotics and Control Systems ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Bulletin of Social Informatics Theory and Application Jurnal Pengabdian Masyarakat (JURDIMAS)
Evi Triandini
Institut Teknologi Dan Bisnis STIKOM Bali
Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Nursing Social Sciences Other

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Journal : Journal of Robotics and Control (JRC)

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Enhancing Diabetic Retinopathy Classification in Fundus Images using CNN Architectures and Oversampling Technique Pamungkas, Yuri; Triandini, Evi; Yunanto, Wawan; Thwe, Yamin
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.25331

Abstract

Diabetic Retinopathy (DR) is a severe complication of diabetes mellitus that affects the retinal blood vessels and is a leading cause of blindness in productive-age individuals. The global increase in diabetes prevalence requires an effective DR classification system for early detection. This study aims to develop a DR classification system using several CNN architectures, such as EfficientNet-B4, ResNet-50, DenseNet-201, Xception, and Inception-ResNet-v2, with the application of the SMOTE oversampling technique to address data class imbalance. The dataset used is APTOS 2019, which has an unbalanced class distribution. Two scenarios were tested, the first without data balancing and the second with SMOTE implementation. The test results show that in the first scenario, Xception achieved the highest accuracy at 80.61%, but model performance was still limited due to majority class dominance. The application of SMOTE in the second scenario significantly improved model accuracy, with EfficientNet-B4 achieving the highest accuracy of 97.78%. Additionally, precision and recall increased dramatically in the second scenario, demonstrating SMOTE's effectiveness in enhancing the model's ability to detect minority classes and reduce prediction errors. DenseNet-201 achieved the highest precision at 99.28%, while Inception-ResNet-v2 recorded the highest recall at 98.57%. Overall, this study proves that the SMOTE method effectively addresses class imbalance in the fundus dataset and significantly improves CNN model performance. Although data balancing can help improve model quality by dealing with data imbalances, it comes at a higher computational cost. Using data balancing techniques with SMOTE significantly increased the iteration time per round on all tested CNN architectures.
A Comprehensive Review of EEGLAB for EEG Signal Processing: Prospects and Limitations Pamungkas, Yuri; Rangkuti, Rahmah Yasinta; Triandini, Evi; Nakkliang, Kanittha; Yunanto, Wawan; Uda, Muhammad Nur Afnan; Hashim, Uda
Journal of Robotics and Control (JRC) Vol. 6 No. 4 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i4.27084

Abstract

EEGLAB is a MATLAB-based software that is widely used for EEG signal processing due to its complete features, analysis flexibility, and active open-source community. This review aims to evaluate the use of EEGLAB based on 55 research articles published between 2020 and 2024, and analyze its prospects and limitations in EEG processing. The articles were obtained from reputable databases, namely ScienceDirect, IEEE Xplore, SpringerLink, PubMed, Taylor & Francis, and Emerald Insight, and have gone through a strict study selection stage based on eligibility criteria, topic relevance, and methodological quality. The review results show that EEGLAB is widely used for EEG data preprocessing such as filtering, ICA, artifact removal, and advanced analysis such as ERP, ERSP, brain connectivity, and activity source estimation. EEGLAB has bright prospects in the development of neuroinformatics technology, machine learning integration, multimodal analysis, and large-scale EEG analysis which is increasingly needed. However, EEGLAB still has significant limitations, including a high reliance on manual inspection in preprocessing, low spatial resolution in source modeling, limited multimodal integration, low computational efficiency for large-scale EEG data, and a high learning curve for new users. To overcome these limitations, future research is recommended to focus on developing more accurate automation methods, increasing the spatial resolution of source analysis, more efficient multimodal integration, high computational support, and implementing open science with a standardized EEG data format. This review provides a novel contribution by systematically mapping EEGLAB’s usage trends and pinpointing critical technical and methodological gaps that must be addressed for broader neurotechnology adoption.
Co-Authors Abdul Karim Achmad Syaifudin Agus Gian Angga Permana Alifah Putri, Athirah Hersyadea Arie Indrawan Arif Djunaidy Artana, I Gede Edy Aryanto, I Komang Agus Ady Ayu Chrisniyanti Bayu Iswara Budaya, I Gede Bintang Arya Cahya Ayuu Pertami Candra Ahmadi Chusak, Thassaporn Dandy Pramana Hostiadi Daniel Oranova Siahaan Dian Puspita Hapsari DwAyu Agung Indra Swari EDWAR EDWAR Fajar Astuti Hermawati Forca, Adrian Jaleco Franky Rawung Ganda Werla Putra Gde Sastrawangsa Gusti Ngurah Aditya Krisnawan Hashim, Uda Hendra Wijaya Hisbiyah, Yuni I Gede Putu Krisna Juliharta I Gede Suardika I Gusti Ayu Widari Upadani I Gusti Bagus Wiksuana I Ketut Dedy Suryawan I Ketut Putu Suniantara I Ketut Suniantara I Komang Dharmendra I Komang Rinartha Yasa Negara I Made Dwi Darma Artanaya I Made Suniastha Amerta I Nyoman Suraja Antarajaya Indrawan, Arie Indrianto Indrianto Iswara, Bayu Jafari, Nadya Paramitha Jayanatha, Sadu Kabnani, Ezra Tifanie Gabriela Kadek Surya Adi Saputra Karolita, Devi Krisnawan, Gusti Ngurah Aditya Kuswanto , Djoko Kuswanto, Djoko Made Pradnyana Ambara, Made Pradnyana Maneetham, Dechrit Marco Ariano Kristyanto Muhammad Faizi, Muhammad Nakkliang, Kanittha Ni Ketut Dewi Ari Jayanti Ni Luh Putri Srinadi Ni Luh Putu Indiani Ni Wayan Deriani, Ni Wayan Ni Wayan Ni Wayan Novia Ari Sandra Nur Rochmah, Nur Nurfalah, Rizal Farhan Nabila Nuryananda, Praja Firdaus Pamungkas, Yuri Perwitasari, Rayi Kurnia Puji Purwatiningsih, Aris Putra, Chrystia Aji Putra, I Gd Windu Sara Adi Putu Adi Guna Permana Putu Ayu Sita Laksmi Putu Suarma Widiada Rangkuti, Rahmah Yasinta Ratna Kartika W Ratna Kartika Wiyati Ravi Vendra Rishika Reza Fauzan Reza Fauzan Rijal, Muhammad Syamsu Riko Setya Wijaya Rusli, M Rusli, M Sadu Jayanatha Sangsawang, Thosporn Saputra, Kadek Surya Setiawan , I Wayan Agus Hery Setini, Made Shofwan Hanief Siti Rochimah Suardana, Gede Sugiarto Sugiarto S Sugiarto Sugiarto Sugiarto Sugiarto Suniantara , I Ketut Putu Suradarma, IB Suradarma, IB Tedy Apriawan Thwe, Yamin Uda, Muhammad Nur Afnan Wawan Yunanto Werla Putra, Ganda Widari Upadani, I Gusti Ayu Wijaya, I Gusti Ngurah Satria Wulandari, Riza Yohanes Priyo Atmojo Zulaikha, Ellya