Cervical cancer model in Indonesia using geographically weighted regression (GWR)

Abstract

Cervical cancer is a type of malignancy emerging from cervix. This is a type of a cancer seen in women having regular oral contraceptives, infected with papillomavirus, having multiple pregnancies or by sexual relation with one or more men. This research will make numbers of patients of cervical cancer models in the all of provinces in Indonesia with Geographically Weighted Regression (GWR) using gaussian function and bisquare function. In this research will be fine the significant of variables for models of each region in Indonesia. In addition, the researchers will be fine the best model for patients of cervical cancer models using Akaike Information Criterion (AIC). In this research have been found the best models was Geographically Weighted Regression (GWR) using gaussian function, causes value of AIC least than value of AIC of Geographically Weighted Regression (GWR) using bi-square function.