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All Journal E-Journal Home Economic and Tourism Jurnal Pendidikan Teknologi dan Kejuruan Journal of Nonformal Education Indonesian Journal of Artificial Intelligence and Data Mining Jurnal Ilmiah Telaah SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL PENDIDIKAN TAMBUSAI Data Science: Journal of Computing and Applied Informatics Jurnal Pendidikan dan Keluarga ABDIKARYA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Indo-MathEdu Intellectuals Journal Flawless INCOME: Indonesian Journal of Community Service and Engagement Jurnal Pengabdian Literasi Digital Indonesia
Hayatunnufus Hayatunnufus
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Journal : Indonesian Journal of Artificial Intelligence and Data Mining

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Enhancing Single Nucleotide Polymorphisms Detection from Imbalanced Data: A Study of Resampling Techniques in Machine Learning Algorithms Nurhasanah, Rossy; Arisandi, Dedy; Purnamasari, Fanindia; Hayatunnufus, Hayatunnufus; Simangunsong, Daisy Sere Damara; Pulungan, Aflah Mutsanni
Indonesian Journal of Artificial Intelligence and Data Mining Vol 8, No 1 (2025): March 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/ijaidm.v8i1.32942

Abstract

Identifying the actual Single Nucleotide Polymorphisms (SNPs) by sourcing Next Generation Sequencing (NGS) data emerges an imbalanced problem due to the inherent high error rate of NGS technology. The imbalance problem has been found to have a negative impact on machine learning algorithms because it produces biased models and poor performance, particularly in detecting actual SNP that belong to the underrepresented class in question.   This study evaluates the effectiveness of several resampling techniques, including Borderline-SMOTE, Random Undersampling, and Tomek-Link, in enhancing the performance of machine learning algorithms, specifically Random Forest (RF) and Artificial Neural Networks (ANN). Furthermore, we compare these techniques to determine the most effective approach. Our results indicate that Borderline-SMOTE improves the F-Measure of RF from 69.72 to 91.52 (a 31.2% increase) and ANN from 79.75 to 91.32 (a 14.5% increase) and outperforms other resampling methods. These findings highlight the crucial role of resampling techniques and the careful selection of algorithms in improving classification accuracy for imbalanced datasets.
Co-Authors Agustina, Fadiya Aini, Wirdatul Amelia Widiatuti Asri, Diahning Aulia Azizah Ayuning, Geby , Denada Betris Sonita Br Sirait, Friska Pegrisentia Chairani, Vici Syahril Darmurtika, Linda Ayu Dedy Arisandi Dewi, Desi Hastika Dewi, Siska Miga Divia Indri Paramita Dwi Septiarini Eka Putri, Nela Aprilia Enjely, Ramona Fabitiary, Annisa Rizqa Fadilah, Rahmi Fandiga, Irfan Fatmawati, Eva Febrina, Eci Feriantano Sundang Pranata Fransisca, Devi Dwi Hanafi, Hafizul Fahri Harlini, Siti Miki Hidayatullah, M Wildan Hutasuhut, Nurul Inayah Ibrahim, Taupik Ida Ayu Putu Sri Widnyani Ika Parma Dewi Indra Saputra Ismail, Mazeni Isnanto Isnanto Jaya, Nurhadi Khunaefi, Rafli Komala, Yulia Laily, Rohisotul Linardita Ferial, Linardita Lindawati, Ayu Mandalika, Mandalika Marbun, Resida Damiana Mardani, Nuzra Melda Mahniza Murni Astuti Mursyida, Lativa Muzakiyah Qurrata A'yuni Nafiz Annas Ningrum, Mercylia Noviarti, Geni Eka NURHASANAH, AYU Nurhasanah, Rossy Pratiwi, Novika Pulungan, Aflah Mutsanni Purnamasari, Fanindia R. Sapto Hendri Boedi Soesatyo Rafsanjani, Ayatullooh Rahmadani Rahmadani Rahmiati Rahmiati Reflianto, Reflianto Reni Haerani Resmita, Resmita Ria Andriani Riska Desriani Saputri RIZA, YULIA Rosalina, Linda Rostamailis Rostamailis RR, Maylina Safrina, Adhelia Permata Sahbani, Fazira Sari, Adha Kurnia Setiawati, Erlin Simangunsong, Daisy Sere Damara Sri Melvani Hardi SUKRISTIANI, DWI Surbakti, Suzi Syamsul Arifin SYOFIA MELISA PUTRI T. Henny Febriana Tania, Shifa TATI NURHAYATI Toyib, Abu Yanita, Merita Yasnita Yasnita Yeni Elviza Febrianti Yolalalita, Suci Yolanda, Siska Septia Yuliana Yuliana yulyana sendia martina YUPELMI, MIMI Yusia Peni Yusmar Emmy Katin Yusuf, Rifki Maulana Zera, Yevawelita