| dc.contributor.author | Buono, Agus | |
| dc.contributor.author | Agmalaro, Muhammad Asyhar | |
| dc.contributor.author | Mushthofa | |
| dc.contributor.author | Faqih, Muhammad | |
| dc.date.accessioned | 2016-05-19T07:40:04Z | |
| dc.date.available | 2016-05-19T07:40:04Z | |
| dc.date.issued | 2012-09 | |
| dc.identifier.uri | http://repository.ipb.ac.id/handle/123456789/80631 | |
| dc.description.abstract | Knowledge of weather and etimate, especially rainfall is significantly necded in agricultural sector. Accurate
information of raintall can be used to determine the planting pattern and time appropriately, 50 that farrners can avoid
crop failure caused by floods due to high rainfall and drought due to low rainfall. Techniques of statistical downscaling
(SD) using a global circulation model output (GCM) are cornrnonly used as a primary tool to learn and understand the
etimate system. The airn ofthis research was to develop an SD model using support vector rcgression (SVR) with GCM
as input to prcdict monthly rainfall in the district of Indramayu. The research results showcd that GCM can be used to
prcdict the average value of monthly rainfall. The best rcsult of prcdiction is at the Bondan Station having an average
correlation of 0.766. | id |
| dc.language.iso | en | id |
| dc.publisher | Bogor Agricultural University (IPB) | id |
| dc.publisher | AFITA/WCCA2012 | id |
| dc.publisher | Bogor Agricultural University (IPB) | id |
| dc.title | Statistical Downscaling Model Based-on Support Vector Regression to Predict Monthly Rainfall: A Case Study in Indramayu District | id |
| dc.type | Article | id |
| dc.subject.keyword | Statistical downscaling | id |
| dc.subject.keyword | global cireulation model | id |
| dc.subject.keyword | support vcctor rcgression | id |
| dc.subject.keyword | monthly rainfall | id |
