Clustering Titik Panas Bumi Pada Potensi Kebakaran Hutan Menggunakan K-Affinity Propagation
DOI:
https://doi.org/10.30872/eksponensial.v15i2.1299Keywords:
k-affinity propagation, hotspots, standard deviations, exemplars, clusterAbstract
K-Affinity Propagation is a development of affinity propagation from Brendan J. Frey and Delbert Dueck. The purpose of this research is to cluster geothermal hotspots on potential forest fires in Indonesia using K-Affinity Propagation for the period July 2022 and obtain optimal cluster results using standard deviation with ratio calculations. The optimal cluster results are 4 clusters, with the number of members in cluster 1 being 12 members with copies in West Sumatera Province, the number of members in cluster 2 being 12 members with copies in Southeast Sulawesi Province, the number of members in cluster 3 being 4 members with copies in Central Sulawesi Province, the number of members in cluster 4 being 1 member with copies in North Sulawesi Province. The optimal cluster results using standard deviation with the smallest ratio value is cluster 4 with a ratio value of 0.057.