Analisis Spasial Untuk Prediksi Persebaran Banteng (Bos javanicus d�Alton 1832) di Luar Kawasan Konservasi (Kasus di Perum Perhutani, KPH Banyuwangi Selatan)
| Main Authors: | , HARYO AJIE DEWANTO, , Wahyu Wardhana, S.Hut., M.Sc. |
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| Format: | Thesis NonPeerReviewed |
| Terbitan: |
[Yogyakarta] : Universitas Gadjah Mada
, 2014
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| Subjects: | |
| Online Access: |
https://repository.ugm.ac.id/129735/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=70132 |
Daftar Isi:
- Habitat is area where organisms live and interact with their environments. Habitat have various characteristics that make only certain organisms possible to live in that areas. Banteng has very wide range of exploration, like there in Banyuwangi, it is widely spread along the southern Banyuwangi. Banteng can also be found inside the production forest that is organized by KPH Banyuwangi Selatan. Therefore, spatial analysis is needed to predict the banteng distribution and to figure out habitat�s variables that are matter-most for their lives. This research was done to find out the important variables of banteng�s habitat and the distribution prediction by using HSI MAP, and to compare between the prediction map with empirical data of banteng�s existence. This research was done by using spatial analysis combined with AHP method also known as weighting method. This method has three key variables to determine banteng�s habitat relevance. Those variables are ecologic variable (NDVI and water springs), topographic variable (height and slope), and disturbance factor (road). Analysis result shows that habitat suitability variable which have the biggest impact is topographic and ecologic factor by 47% and disturbance factor by 6%. In KPH Banyuwangi Selatan�s area, very-high-relevance score is 53% and high-relevance score is 47%. Thus, we can say that KPH Banyuwangi Selatan have habitat character that is relatively suitable for banteng. HSI map can be used as banteng�s distribution prediction tool, because banteng distribution on locations on map which has high habitat relevance, after being compared with empirical data.