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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JOIV : International Journal on Informatics Visualization Knowledge Engineering and Data Science JUTIK : Jurnal Teknologi Informasi dan Komputer JOURNAL OF APPLIED INFORMATICS AND COMPUTING SINTECH (Science and Information Technology) Journal Jurnal RESISTOR (Rekayasa Sistem Komputer) JE (Journal of Empowerment) Journal of Engineering and Scientific Research (JESR) Indonesian Journal of Data and Science Jurnal Scientia Journal of Computer Networks, Architecture and High Performance Computing Jurnal Krisnadana Jurnal Krisnadana International Journal of Artificial Intelligence in Medical Issues TECHNOVATE KOMET Jurnal Nasional Teknologi Informasi dan Aplikasinya
Radhitya, Made Leo
Institut Bisnis Dan Teknologi Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Medicine & Pharmacology Public Health Social Sciences

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Machine Learning-Based Clustering of Viruses Using Taxonomic and Genomic Features for Health Informatics Applications Adityo Permana Wibowo; Made Leo Radhitya; Edi Faizal; Ika Arfiani
International Journal of Artificial Intelligence in Medical Issues Vol. 4 No. 1 (2026): International Journal of Artificial Intelligence in Medical Issues
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/qstvhw47

Abstract

Viruses remain a major concern in global public health due to their potential to cause outbreaks, epidemics, and pandemics. The rapid organization and analysis of virus-related data are important for supporting computational virology, health informatics, and pandemic preparedness. This study proposes an unsupervised machine learning approach to cluster viruses based on taxonomic and genomic characteristics. The dataset consisted of 70 virus records with attributes including family, genus, genome type, strand type, and envelope status. Since the dataset did not contain predefined epidemiological labels or risk categories, the analysis was designed as an exploratory clustering task rather than a supervised prediction task. Data preprocessing was performed by removing duplicates, handling missing values, standardizing categorical attributes, and transforming selected features using One-Hot Encoding. Three clustering algorithms were evaluated, namely K-Means, Agglomerative Clustering, and DBSCAN. The clustering performance was assessed using Silhouette Score, Davies-Bouldin Index, and Calinski-Harabasz Score, while Principal Component Analysis was applied for two-dimensional visualization. The results showed that K-Means with 10 clusters achieved a Silhouette Score of 0.7725 and a Davies-Bouldin Index of 0.8186. Agglomerative Clustering obtained the highest Silhouette Score of 0.7754, while DBSCAN produced fewer clusters with lower overall performance. Several biologically meaningful groups were identified, including clusters representing Flaviviridae, Coronaviridae, Herpesviridae, Poxviridae, and enveloped RNA viruses. However, a large proportion of records contained unknown values, which influenced the formation of a dominant incomplete-data cluster. These findings indicate that taxonomic and genomic features can support machine learning-based virus grouping, although data completeness remains a critical factor. This study provides an initial computational framework for AI-driven viral data exploration and may serve as a foundation for future viral risk stratification using enriched epidemiological and clinical features.
Co-Authors Adityo Permana Wibowo Admojo, Fadhila Tangguh Agus Harjoko Aprianti, Ni Nyoman Asana, I Made Dwi Putra Asana, Made Dwi Putra Atmaja, I Made Ari Dwi Suta Atmaja, Ketut Jaya Bagus Tresna Bramstya Edi Faizal Felix Andika Dwiyanto Gede Wirya Wardhana Giri, Gst. Ayu Vida Mastrika Gst. Ayu Vida Mastrika Giri Gunawan, I Komang Agus Bryan Hamada Zein I Dewa Gede Agung Pandawana I Gede Iwan Sudipa I Gusti Agung Indrawan I Made Subrata Sandhiyasa I Made Yoga Apriliana I Nyoman Alit Arsana I Nyoman Gede Arya Astawa I Nyoman Tri Anindia Putra I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Eka Andika Cakra I Wayan Raka Ardana I Wayan Supriana Ida Bagus Gede Sarasvananda Ika Arfiani Ketut Laksmi Maswari Libraeni, Luh Gede Bevi Made Wahyu Adhiputra Naswin, Ahmad Ni Made Diah Nandita Pangestu Ni Made Mila Rosa Desmayani, Ni Made Mila Rosa Ni Putu Widantari Suandana Ni Wayan Jeri Kusuma Olivia Sutriani Jelni Putra, Putu Satria Udyana Raharja, Made Agung Saputra, I Wayan Kelvin Widana Selivan, Diana Semadi, Ketut Ngurah Siti Marlina, Siti Subawa, I Gede Arika Triadi, Wilfridus Bambang Waas, Devi Valentino Wahyudi, I Putu Alfin Teguh Widiantari, Ni Komang Mira Wiguna, I Komang Arya Ganda Wiguna, I Wayan Darma Wijaya, Bagus Kusuma