KLASIFIKASI FAKTOR YANG BERPENGARUH DALAM KEHAMILAN TIDAK DIINGINKAN MENGGUNAKAN METODE ALGORITMA DECISION TREE - Ula Mir'aatunnas Pratiwi; Mursyidul Ibad (LPPM Universitas Bina Bangsa, 2022)
Unwanted pregnancy (KTD) in Indonesia has increased every year. Unwanted pregnancy is one of the factors causing miscarriage, abortion, low birth weight and premature birth. Of course, this also has an impact on increasing the risk of maternal and child mortality. This research aims toanalyze classificationfactors that influence unwanted pregnancies using the decision tree algorithm method. This research is an non reactive or unobstrusive research. The research design used was cross-sectional using secondary data from the 2019 KKBPK Performance and Accountability Survey (SKAP). The population in this study were couples of childbearing age (PUS) in Indonesia with sample 46,220 currently married women aged 15-49 years. Analysis of the data used in this study using the decision tree CART algorithm. The results of this study indicate thatpThe classification system is formed with an accuracy level of 84.5% on training data, and 84.6% on testing data. The tree construction that was formed resulted in 13 classifications of factors related to KTD with the highest classification (94%) namely PUS who had children who were still alive 2, lived in urban areas, mother's age at first marriage was 25 years, and when family planning decisions were made by themselves. yourself (mother), service provider, spouse (husband).