Pemetaan Penyakit Hewan Ternak di Timor Tengah Selatan Menggunakan GIS dengan Metode K-Means Clustering - Rasti Lani; Yampi R Kaesmetan (JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital, 2025)
South Central Timor Regency in East Nusa Tenggara Province faces serious challenges in controlling livestock diseases that impact livestock farmers' welfare and food security. rainfall patterns due to climate change impacts. This study aims to develop a WebGis-based Geographic Information System (GIS) to map the distribution of livestock diseases in the region. This system is expected to assist the Animal Husbandry Service in planning efforts to control and prevent diseases more effectively and on target. The method used is K-Means Clustering to group areas based on disease prevalence, disease type, and environmental factors that influence its spread. Accurate spatial data is collected from various sources and integrated into the WebGis platform, resulting in a livestock disease distribution map that can be easily accessed by related parties. The expected results of this study are the availability of fast, accurate, and efficient disease distribution information to support planning for animal disease control and prevention actions. The developed WebGis allows access to real-time and data-based information, thus supporting more strategic decision-making in improving livestock resilience in South Central Timor Regency