PEMODELAN KASUS KEMATIAN IBU HAMIL DI JAWA TENGAH DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) DAN MIXED GWR - Salma, Anugrah Rawiyah; Sugito, Sugito; Sa’adah, Ardiana Alifatus (Jurnal Gaussian, 2024)
Global maternal mortality reduction remains a part of The Sustainable Development Goals (SDGs). Maternal death in Central Java increased in 2021, with the leading cause is related to Covid-19. Maternal mortality in Central Java is demonstrated using Geographically Weighted Regression (GWR) for addressing the spatial heterogeneity aspects. Cross Validation is used to determine the optimal bandwidth and Euclidean distance used to discover the weighting matrix. Independent variables such as number of nurse, number of primary clinic, and household percentage with safe water supply are identified as local variables, whereas other independent variables, such as complications from delivery management and number of poverty are identified as global variables, hence the Mixed GWR model, which combine both local and global variables, is used. Based on the value of AIC, MSE, also adjusted , the optimal model for analyzing the maternal mortality is Mixed GWR with fixed Gaussian weighting.