Clustering Titik Panas Bumi Menggunakan Algoritme Affinity Propagation - Barik Kresna Amijaya; Muhammad Tanzil Furqon; Candra Dewi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
Forest and land fires are catastrophic and can disrupt the activity of living things around the fire location. Forest and land fires should be prevented by knowing the cause of the fire. One of the ways of fire prevention is to monitor the hotspot. The hotspot is an area where the temperature is relatively higher compared to the area around which the satellite is detected. The area is represented in a point that has certain coordinates. hotspot needs to be grouped or clustered to know the similarity of each point and easy to do monitoring. Clustering is the process of grouping data into clusters, so that objects that exist within a cluster have a high similarity with each other and very different from the objects that exist in other clusters. Affinity Propagation method is a method used to perform data grouping by specifying the exemplar as data centers. Affinity Propagation performs clustering by searching for responsibility value and availability of each data to find the right exemplar. In this research has done clustering using Affinity Propagation with the best silhouette coefficient value that is 0.317818 with 125 data and formed 44 clusters.