| dc.description.abstract | Asphyxia neonatorum is a newborn emergency in the form of respiratory depression that continues, causing various complication even death. According to RISKESDAS Indonesia 2007, 78,5% of infant mortality occur in an early neonatal days with the greatest cause due to asphyxia neonatorum. Therefore, a tool for early detection of risk and potential of asphyxia neonatorum in each pregnancies is needed. Early identification of pregnant woman with birth asphyxia / asphyxia neonatorum risk can be done by implementing Rule Based Reasoning approach with Forward Chaining method followed by Case Based Reasoning approach is a system. The data analyzed and used as the case base in this research obtained from maternity of pregnant mother and infant medical record from RSKIA Sadewa Yogyakarta. The data analyzed and used are fetal heart rate (FHR), maternal age, gestational age, maternal blood pressure, fetal presentation, amniotic water condition, placental abnormalities, preeclampsia / eclampsia, umbilical cord, maternal BMI (body mass index), history of maternal disease, obstetric and gynecological history, fetal weight estimates, alcohol / drugs consumption, congenital defects, hemoglobin levels, fetal number and antenatal care status. System receives pregnancy control data as an input, then processes the FHR data with RBR. Cases with normal FHR values are then processed with CBR resulting in APGAR score prediction. Obstetrician can verify those cases so it can become new knowledge for the system and system can generate more reliable prediction result. System testing in this research indicate that the level of system validity is 95.45% with Kappa score of 0.9, the system functional acceptance rate of 100%, and the level of ease of use (usability) of 85.46%. Based on these three tests, the system is in the 'Excellent' category with a system quality rating of 93.64%. | en_US |
