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-  2018 

Geographically Weighted Regression to Predict the Prevalence of Hypertension Based on the Risk Factors in South Kalimantan

DOI: http://dx.doi.org/10.18860/ca.v5i3.5879

Keywords: GWR, , Kernel function. Adaptive Gaussian, prevalence hypertension

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Abstract:

Hypertension is one of the disease is not contagious diseases which is a public health problem. Uncontrolled Hypertension can trigger a degenerative diseases such as congestive heart failure, renal failure and vascular disease. Hypertension is called the silent killer because his nature the condition is asymptomatic and can cause a fatal stroke. With the increasing prevalence of cases of degenerative diseases, one only hypertension, then the researchers want to predict the variables very big role as one of the risk factors of Genesis hypertension. With clearly know the risk factors that play against genesis hypertension is expected to be used as a reference for the prevention and control so that they can reduce the prevalence of hypertension and prevent deaths from degenerative diseases, especially hypertension. The results of the study showed that the results of the modeling the prevalence of hypertension in South Kalimantan Province using linier regression there is no factor that affect the genesis of hypertension. The prevalence of hypertension spread spatially because there are heterogenitas between the location of the observation that means that observations of a location depends on the observations in another location that the distance is near so do spatial regression modeling with Adaptive Gaussian kernel function, meghasilkan 5 groups. Group I consists of the districts Tanah Laut and Tanah Bumbu; group II, Kota Baru; Group III consists of Banjar, Kota Banjar Baru, Kota Banjarmasin; Group IV on the Barito Kuala Regency and the Group V consists of Tapin, H S Selatan, H S Tengah, H S Utara, Tabalong, Balangan

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