@article{Pramesti_Susanti_Pratiwi_2022, title={Parameter Estimation Robust Regression Method of Moment (MM) in Cases of Maternal Death in Indonesia}, url={http://repository.urecol.org/index.php/proceeding/article/view/1922}, abstractNote={<p>Regression analysis is used to determine the relationship between the dependent and <br>independent variables with a parameter estimator. The parameter estimator that is <br>usually used is the Least Squares Method (LSM), this requires a classical assumption <br>test. Some cases have normality assumptions that are unfulfilled because there are <br>outliers so the result regression parameter estimates are not accurate so that robust <br>regression is used in the analysis. Robust regression is a regression analysis method that <br>can withstand outliers. The purpose of this study is the application of robust regression <br>estimation Method of Moment (MM) with Tukey Bisquare weighting in the case of data <br>on the number of maternal deaths in Indonesia 2020 with the number of maternal deaths <br>as a dependent variable, and with independent variables such as the number of pregnant <br>women who experience bleeding, the number of diabetics in pregnancy, and the number <br>of HIV positive in pregnancy. The result showed that every one unit increase of three <br>independent variables had a positive effect on the number of cases of maternal deaths, <br>each of which was 2,8064; 2,5014; 1,1577.</p>}, journal={Prosiding University Research Colloquium}, author={Pramesti, Putri Ayu and Susanti, Yuliana and Pratiwi, Hasih}, year={2022}, month={Jun.}, pages={96–103} }