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Parameter Estimation Robust Regression Method of Moment (MM) in Cases of Maternal Death in Indonesia Putri Ayu Pramesti; Yuliana Susanti; Hasih Pratiwi
Prosiding University Research Colloquium Proceeding of The 15th University Research Colloquium 2022: Bidang MIPA dan Kesehatan
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

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Abstract

Regression analysis is used to determine the relationship between the dependent and independent variables with a parameter estimator. The parameter estimator that is usually used is the Least Squares Method (LSM), this requires a classical assumption test. Some cases have normality assumptions that are unfulfilled because there are outliers so the result regression parameter estimates are not accurate so that robust regression is used in the analysis. Robust regression is a regression analysis method that can withstand outliers. The purpose of this study is the application of robust regression estimation Method of Moment (MM) with Tukey Bisquare weighting in the case of data on the number of maternal deaths in Indonesia 2020 with the number of maternal deaths as a dependent variable, and with independent variables such as the number of pregnant women who experience bleeding, the number of diabetics in pregnancy, and the number of HIV positive in pregnancy. The result showed that every one unit increase of three independent variables had a positive effect on the number of cases of maternal deaths, each of which was 2,8064; 2,5014; 1,1577.