Modeling of dengue hemorrhagic fever cases in AWS Hospital Samarinda using bi-responses nonparametric regression with estimator spline truncated

Abstract

Research on innovations in the field of statistics implemented in the health sector. This research is the development of birespon nonparametric regression model with spline truncated approach. The purpose of this research is to model and determine the factors affecting the Dengue Hemorrhagic Fever Cases in AWS Hospital Samarinda using Bi-responses Nonparametric Regression with estimator Spline Truncated. The data used in this study were data on the platelet count of dengue fever patients when they first checked blood and after three days of treatment in 2022 as well as factors that were thought to have an effect. From the research results, the best model was biresponse nonparametric regression with three knot points where the minimum GCV value was 97.77 and R2 value of 89.88%. Based on the test results, the factors affecting the response variable were the number of hematocrit and the level of hemoglobin in DHF patients.