A COMPARISON OF M-ESTIMATION AND S-ESTIMATION ON THE FACTORS AFFECTING IR DHF IN EAST JAVA IN 2017 - Mardiana Mardiana; Arief Wibowo; Mahmudah Mahmudah; Pipit Festi W (The Indonesian Journal of Public Health, 2021)
ABSTRACTRobust regression on M estimation and S estimation is the Ordinary Least Square (OLS) regression on the data outlier. East Java is one of the provinces in Indonesia with a high case fatalitiy rate (1.34%). The raising of  Dengue Haemoragic Fever (DHF) in East Java has been influenced by climate, population density, human behavior, and environmental sanitation. This study aimed to compare robust regression research by using M estimation and  S estimation on the factors that affect IR DHF. This was done to get the best model regression on the data outlier based on the biggest R2 adjusted and the smallest MSE. This study utitlized observational research with a non-reactive research design using secondary data. The independent variable consisted of population density, healthy behavior, healthy living environment house, and precipitation in East Java in 2017. The dependent variable was incident rate of DHF in 2017. The population included 38 regencies in East Java, while the sample was 35 regencies/cities selected using simple random sampling. The analysis used robust regression on M estimation and S estimation weighting by Tukey’s Bisquare. Robust regression on S estimation was found to be the best robust regression on data outlier with R2 adjusted (0.996) and MSE (0.229). Robust regression on S estimation  was = 54.826 + 0.011 (population density) – 0.136 (% healthy behavior) - 0,404 (% healthy house ) - 0,005 (precipitation).Some factors that affect IR DHF can be the main focus for the prevention and control of DHF for the government and society.  Keywords: robust regression, outlier, estimation, estimation, DHF