Implementation of Risk Factor Detection System Using k-NN Method to Reduce Maternal Mortality Rate at Sumbersari Primary Health Centre - Prakoso, Bakhtiyar Hadi; Yunus, Muhammad; Rahagiyanto, Angga; Vestine, Veronika; Suyoso, Gandu Eko Julianto; Deharja, Atma (Indonesian Journal Publisher, 2025)
The Maternal Mortality Rate has become a major issue for the Indonesian government as it can be used to measure the reproductive health level of a country. In 2023, the maternal mortality rate in Jember Regency was recorded at 150 per 100,000 live births. Sumbersari Primary Heath Centre is one of Primary Health in Jember, located in the city. Still had cases of maternal mortality, with two recorded cases The Jember Regency government has implemented various interventions, including the implementation of integrated antenatal care (ANC), the preparation of emergency obstetric and neonatal management guidelines, and collaboration with educational institutions to support pregnant women, strengthen maternal and neonatal referrals, and enhance the PONED and PONEK maternity teams. In line with these programs, there is a need for synergy in utilizing information technology to support the Jember government’s efforts to reduce maternal mortality rates through the creation of an early detection system to predict maternal deaths. This research will develop an early detection system for maternal mortality using the KNN method. The attributes used include gestational age, weight, haemoglobin, blood pressure A, blood pressure B, facial swelling, stillbirth, breech birth, bleeding during pregnancy, hydramnios, post-term pregnancy, transverse presentation, preeclampsia/eclampsia, anaemia, tuberculosis, malaria, and heart failure. The system development will utilize the prototype method. The test results show that the system can be used to predict maternal mortality with an accuracy