| 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 |
