Pemutakhiran Zona Musim (ZOM) Provinsi Aceh Menggunakan Data Blending Berbasis Non-Hirarki K-Means Clustering

Abstract

Climatologically, Aceh is influenced by global, regional, and local phenomena strongly influenced by the hilly mountain topography. Aceh is also surrounded by Indian Ocean in the west, Malacca Strait in the east and Andaman Sea in the north that making climate conditions more varied. The old season zone is not compatible to explain this condition. This paper makes an updated analysis by combining the observational and satellite data for rainfall activity explanation. We use k-means clustering based on the analysis of blending data between observation data and satellite imaging that produces more specific and updated season zone (ZOM). The clusters obtained are newly season zones that provide more specific mapping for dry and rainy season information. The updated season zone of 15 ZOM clusters based on k-means can figure a clear variation that means the accuracy of difference rainfall value can be more precise. From this research, the updated season zone can provide effective planning about strengthened from various government sectors in the future that can give a better policy to the public community.