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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Teknik ITS Proceedings of KNASTIK JUTI: Jurnal Ilmiah Teknologi Informasi Teknik dan Ilmu Komputer Seminar Nasional Informatika (SEMNASIF) Journal of Information Systems Engineering and Business Intelligence SISFO CCIT (Creative Communication and Innovative Technology) Journal Journal of Information System,Graphics, Hospitality and Technology ILKOMNIKA: Journal of Computer Science and Applied Informatics JAREE (Journal on Advanced Research in Electrical Engineering) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Sewagati Masip: Jurnal Manajemen Administrasi Bisnis dan Publik Terapan Proceeding of International Conference on Social Science and Humanity
Wiwik Anggraeni
Departemen Sistem Informasi Institut Teknologi Sepuluh Nopember
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Journal : ILKOMNIKA: Journal of Computer Science and Applied Informatics

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Addressing Imbalance Data Label Distribution in Dengue Severity Classification with Hybrid Machine Learning Approach Arrizal Kusuma, Moch Farrel; Anggraeni, Wiwik
ILKOMNIKA Vol 6 No 3 (2024): Volume 6, Nomor 3, Desember 2024
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v6i3.649

Abstract

Early detection of disease is essential for ensuring proper diagnosis and treatment, which helps to reduce complications and limit the spread of cases. Dengue fever remains a major public health issue in Indonesia, with some regions reporting case fatality rates above 1%. This study aims to develop a robust classification model to predict the severity of dengue fever based on laboratory data, addressing the issue of imbalanced label distribution. To achieve this, we applied a combination of oversampling, machine learning, and optimization techniques. Specifically, we utilized the SMOTE-ENN method to enhance the representation of minority classes and applied XGBoost for multi-class classification. Additionally, Particle Swarm Optimization (PSO) was used to fine-tune the model’s hyperparameters. After testing 15 experimental scenarios, the hybrid SMOTE-ENN-XGBoost-PSO approach delivered the best performance, achieving an accuracy of 95% and an F1-score of 94%. These results demonstrate that the proposed approach effectively handles data imbalance and improves predictive accuracy. This research serves as a foundation for future work in applying advanced algorithms and Federated Learning to improve multi-class classification in healthcare.
Co-Authors Achmad Holil Noor Ali Adri Gabriel Sooai Agustinus Bimo Gumelar Ahmad Mukhlason Ahmad Muklason Amalia Utamima Amalinda Jayanty Amira Herwindyani Hutasuhut Amna Shifia Nisafani Andreas Agung Kristanto, Andreas Agung Ani Rahmadiani Apol Pribadi Arif Djunaidy Arrizal Kusuma, Moch Farrel Asra Alfathoni Aulia Sidharta, Hanugra Aulia Vinarti Danang Febrian Diah Risqiwati Divka, Princessa Sissy Eko Mulyanto Yuniarno Faizal Mahananto Fajar Kurnia Malays Fandi Cahyo Saputro Febriliyan Samopa Handayani Tjandrasa Hanif Mitsal Mahatta Hardhika Propitadewa Ika Ayu Fajarwati Ilmi Usrotin Choiriyah Imelda Dian Rahmawati Indar Sugiarto Irlando Moggi Prakoso Jeremy Diaz Prasetyo Jihaan Harvi Habibah Kurniaji, Garis Narendra Kusumawardhani, Renny Pradina Lailatul Husniah Laura Wilhelmina Theresia Leivina Kartika Dewi Lia Farihul Mubin M. Fajrul Hakim M. Fiqri Ananda Maria Cendanasari Kurniawan Putri Mauridhi Hery Purnomo Mauridhi Hery Purnomo Meilani, Maulidiya Mochamad Zidan Aqila Kamil Muhammad Ali Fikri Muhammad Arif Nuriman Muhammad Daffa Maulana Muhammad Hisyam Naufal Rafiawan Basara Nazriyah Deni Tsaniyah Nova Eka Budiyanta Novian Tiandini Nur Aini Lestari Nur Khofifah Nur Laila Nur Nindya Risnina Oktania, Teky Budi Perdana, Muhammad Ilham Pujiadi Pujiadi Pujiadi, Pujiadi Purnama, I Putu Adhitya Pratama Mangku Radityo Prasetianto Wibowo Rahma Fauzia Rahmanisa, Fathia Raras Tyas Nurita Raras Tyasnurita Restia Rezalini P. S Retno Aulia Vinarti Rikasakomara, Edwin Riksakomara, Edwin Rizky Praditya Rully Agus Hendrawan Septica Tiara Indah Permatasari Sidharta, Hanugra Aulia Siti Aminatus Zehroh Sudiarti, Yeyen SUGIYANTO Sugiyanto - Supeno M Susiki Nugroho T, Lulus Condro Tresnaning Arifiyah Tri Achmadi Wahyu Ardianto Willy Achmat Fauzi