Klasifikasi Data Spasial Untuk Kemunculan Hotspot Di Provins! Riau Menggunakan Algoritme Id3

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DC Field	Value	Language
dc.contributor.author	Fernando, Vikhy
dc.contributor.author	Sitanggang, lmas Sukaesih
dc.date.accessioned	2015-08-10T03:15:04Z
dc.date.available	2015-08-10T03:15:04Z
dc.date.issued	2014
dc.identifier.isbn	978-802· 7049 H!·9	-
dc.identifier.uri	http://repository.ipb.ac.id/handle/123456789/75967
dc.description.abstract	Forest fires is one of environmental issues that occurs almost every year in Indonesia, including in Riau Province. It causes negative impacts for human life. Large spread hotspot data can be analyzed using spatial data mining techniques namely spatial decision tree algorithms. The algorithm results a spatial decision tree from which we can obtain classification rules. This work developed spatial decision trees using the 103 algorithm. The highest accuracy of the tree is 70.80%. The classification model which consists 125 classification rules can be used to predict hotspots occurrence.	en
dc.language.iso	id
dc.publisher	Fakultas Matematika dan Ilmu Pengetahuan Alam Institut Pertanian Boger
dc.title	Klasifikasi Data Spasial Untuk Kemunculan Hotspot Di Provins! Riau Menggunakan Algoritme Id3	en
dc.type	Article	en
dc.subject.keyword	Classification	en
dc.subject.keyword	Hotspot	en
dc.subject.keyword	103 Algorithm	en
dc.subject.keyword	Spatial decision tree	en
Appears in Collections:	Proceedings

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