Penerapan Algoritma K-Medoids dalam Menentukan Daerah Rawan Banjir di Kabupaten Karawang

Abstract


 
 
 Flood disasters often occur during the rainy season. Karawang is one area that is often flooded. Based on the risk index from BNPB, the flood disaster in Karawang affected 84% of the community, so efforts need to be made to reduce and overcome flood disasters. These problems are the beginning of efforts that need to be known which areas are prone to flooding. Therefore, this study aims to determine flood-prone areas in Karawang as an initial effort in tackling flood disasters. The research was conducted by classifying flood-prone areas using the k-medoids algorithm. K-Medoids uses the partition clustering method to group lists and objects into a number of clusters. This algorithm uses objects in a collection of objects that represent a cluster. The attributes used are flood-causing factors such as rainfall, elevation (soil height), population density, and distance to the river. The results of the study found three potential floods, namely low, medium, and high. There are 1 sub-district with low flood potential, 24 sub-districts with moderate flood potential, and 5 sub-districts with high flood potential. The test results using the silhouette coefficient get a value of 0.370.