Analisis Klaster Dampak Kesehatan Akibat Pandemi Covid 19 Metode K-Means dan C4.5 - Anindita, Karina; Wirakusuma, Anak Agung Ngurah Bagus Adhitya; Pamudji, Kristopher May; Budi, Dini Wurnaning; Yudha Putra, I Komang Reka (Program Studi Gizi, Universitas Bumigora, 2025)
The COVID-19 pandemic has had a broad impact on the health system and the socio-economic conditions of communities, including in the Province of West Nusa Tenggara. Inequalities in healthcare access, the prevalence of comorbid diseases, and economic disparities have resulted in varying levels of risk across regions. This study aims to analyze clusters of health impacts resulting from the COVID-19 pandemic in West Nusa Tenggara. The research employed the K-Means and C4.5 Decision Tree methods with a CRISP-DM approach. Secondary data were obtained from the West Nusa Tenggara Provincial General Hospital, the West Nusa Tenggara Health Profile, Statistics Indonesia (BPS) 2022–2023, the 2021 Basic Health Research (Riskesdas), and the World Health Organization (WHO). The variables included COVID-19 cases per 100,000 population, vaccination rates, healthcare facility ratios, prevalence of hypertension and diabetes, and poverty rates. The K-Means results identified three risk clusters: high (Mataram, West Lombok), moderate (Central Lombok, East Lombok), and low (Sumbawa, Dompu, Bima). The C4.5 model achieved an accuracy of 80.67%, with age and comorbidities emerging as dominant factors. These findings highlight the potential of data mining analysis as a foundation for post-pandemic mitigation policies and strengthening regional health system resilience.