Clustering Menggunakan Algoritma DBSCAN (Density-Based Spatial Clustering of Applications with Noise) untuk Data Hasil Produksi Potensi Pertanian Studi kasus : Kabupaten Gresik; Clustering Data of Agriculture Product Using DBSCAN (Density-Based Spatial Clustering of Applications with Noise) Algorithm Case study : Kabupaten Gresik

RUDIANTO, Subanar

2011 | Disertasi | PROGRAM STUDI S2 ILMU KOMPUTER

DBSCAN(Density-Based Spatial Clustering of Aplication with Noise) Algprthm is a clustering algorithm which is developed by density-based. This algorthm make clusters area where they have their own high density, and find those clusters in arbitrary shape in spatial database with noise. On this method, noise is used to present area which they have low density. That noise is used to be apart area where they have different cluster, on object in data spatial. To find a cluster, DBSCAN is used to a set maximum density point connected by Eps and MinPts parameter. Eps parameter is used to determine radius of set points of different cluster and MinPts parameter used to give constraint of points number which to be part of cluster in Eps radius.

Kata Kunci : Clustering, DBSCAN, Noise