| dc.contributor.author | ALAMSYAH, PADEMI | |
| dc.contributor.author | ANWAR, CHAIRIL | |
| dc.contributor.author | SETYAWAN, DWI | |
| dc.contributor.author | HANUM, LAILA | |
| dc.date.accessioned | 2017-09-07T03:58:07Z | |
| dc.date.available | 2017-09-07T03:58:07Z | |
| dc.date.issued | 2016-12-09 | |
| dc.identifier.isbn | 978-602-757-793-0 | |
| dc.identifier.uri | http://repository.umy.ac.id/handle/123456789/14365 | |
| dc.description | Malaria is a public health problem in District of Ogan Komering Ulu South
Sumatra. Annual Malaria Incidence (AMI) in 2012 cases of malaria 10 0/00, 2013
increased 26 0/00 and of 2014 decreased 170/00. The pattern spreading of malaria to the
height of a place, closely related. The area at an elevation of above 1000 m above sea
level the less found Anopheles mosquito. The aim to analyze the spatial distribution
patterns of malaria incidence by area elevation of sea surfaceand mapping malaria risk
zone. This ecological study, analyze the correlation between elevation and spreading
of malaria case. The data and the data elevation of sea surface. The result show that
R2=0.84 mean 84% elevation GIS approach and Multiple Linear Regression analysis is
a potentially useful tool. R Square on statistics regression models was 0.84, that 84% of
malaria cases were in uenced by the extent of the height of the sea surface in hectares.
In value Signi cance F of 0.00 or below 0.05, then the regression can be used to predict
the incidence of malaria. The result of statistical analyze showed p= 0.00; Ftable= 3.4
showed the elevation factor in uence to the incidence of malaria signi cantly. This study
con rms that, elevation factor in uence spread of malaria in District of Ogan Komering
Ulu, South Sumatra province. | en_US |
| dc.description.abstract | Malaria is a public health problem in District of Ogan Komering Ulu South
Sumatra. Annual Malaria Incidence (AMI) in 2012 cases of malaria 10 0/00, 2013
increased 26 0/00 and of 2014 decreased 170/00. The pattern spreading of malaria to the
height of a place, closely related. The area at an elevation of above 1000 m above sea
level the less found Anopheles mosquito. The aim to analyze the spatial distribution
patterns of malaria incidence by area elevation of sea surfaceand mapping malaria risk
zone. This ecological study, analyze the correlation between elevation and spreading
of malaria case. The data and the data elevation of sea surface. The result show that
R2=0.84 mean 84% elevation GIS approach and Multiple Linear Regression analysis is
a potentially useful tool. R Square on statistics regression models was 0.84, that 84% of
malaria cases were in uenced by the extent of the height of the sea surface in hectares.
In value Signi cance F of 0.00 or below 0.05, then the regression can be used to predict
the incidence of malaria. The result of statistical analyze showed p= 0.00; Ftable= 3.4
showed the elevation factor in uence to the incidence of malaria signi cantly. This study
con rms that, elevation factor in uence spread of malaria in District of Ogan Komering
Ulu, South Sumatra province. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Environmental Science, Sriwijaya Univercity, Palembang | en_US |
| dc.subject | malaria, spatial analysis, anopheles mosquitoes, geographic information systems (GIS), elevation of sea surface | en_US |
| dc.title | MALARIA OCCURRENCE FACTOR ANALYSIS BASED ON ELEVATION OF SEA SURFACE IN THE DISTRICT OF OGAN KOMERING ULU, SOUTH SUMATRA | en_US |
| dc.type | Book | en_US |
