Application of Spatial Decision Tree in Identifying Mangrove Area using C4.5 Algorithm

dc.contributor.author	Sitanggang, Imas Sukaesih
dc.contributor.author	Napthalena
dc.contributor.author	Wijaya, Sony Hartono
dc.date.accessioned	2015-09-30T02:25:24Z
dc.date.available	2015-09-30T02:25:24Z
dc.date.issued	2009
dc.identifier.uri	http://repository.ipb.ac.id/handle/123456789/76373
dc.description.abstract	East Borneo is one of provinces fn Indonesia that has potential coast teritory for mangrove's growth. This work uses a spatio/ data mining method, especially spatio/ decision tree using C4.5 algorithm to develop a classifier to predict new data of mangrove area. We use the Spatial Join Index (SJI} and the complete operator to apply the conventional closslfication technique In the spatial database. The SJI is created using topological relations to find relations between two spatio/ objects, then the result Is simplified using the complete operator. The result shows that classes of mangrove area ore described by four attributes: slope, topography, substrate, and land use. The classifier contains 23 rules with 60,669' accuracy.	en
dc.language.iso	en
dc.relation.ispartofseries	August 10-11. 2009;
dc.subject.ddc	Spatial decision tree	en
dc.subject.ddc	C4.5	en
dc.subject.ddc	Spatial join index	en
dc.subject.ddc	Complete operator	en
dc.title	Application of Spatial Decision Tree in Identifying Mangrove Area using C4.5 Algorithm	en