Cloud-Based Multinomial Logistic Regression for Analyzing Maternal Mortality Data in Postpartum Period
Radite Purwahana, Suryono Suryono, Jatmiko Endro Suseno · 2018
The analysis used in dealing with maternal mortality factors in the postpartum period can be used as a reference in preventing maternal death in the postpartum period. Appropriate analysis is needed to reduce maternal mortality rates in the postpartum period. This study uses multinomial logistic regression to analyze the data of mothers dying in the postpartum period based on the main variables causing maternal death. Multinomial logistic regression process is carried out by looking at data records of variables that influence maternal mortality. In the first experiment using data from midwife visits for seven days, the results of the multinomial logistic regression process with the highest maternal mortality occurred on the fourth day with anogenital variables reaching a percentage of 32.4% of the causes of maternal death. Multinomial logistic regression processes are combined with cloud computing technology so that data can be processed more quickly and can be used together.