Development of A Detection Tool in Pregnant Women and Its Recommendations in Utilizing Artificial Intelligence - Oktaviani, Nur Hilda; Widyawati, Melyana Nurul; Kurnianingsih, Kurnianingsih (Journal of Maternal and Child Health, 2024)
Background: Chronic Energy Deficiency (CED) can be experienced by women of reproductive age (WUS) aged 15–45 years old since adolescence then continues during pregnancy and breastfeeding due to low energy and nutrient reserves. Health technology innovation that utilizes artificial intelligence, i.e. Digital mid-uppr arm circumference (MUAC) which is a digital measurement tool that can make it easier to read anthropometric measurement results, especially in measuring upper arm circumference to detect pregnant women who experience CED. Subjects and Method: This was a Research and Development with a pre-experimental design with an on shot case study. The number of samples is 100 Subjects, which is done 3 times each month for 3 months. The sample was selected by purposive sample. The analysis used artificial intelligence. Results: Digital MUAC level of accuracy in detecting CED in pregnant women and its recommendations that utilize artificial intelligence, an accuracy level of 100%. Conclusion: The CED detection tool Digital MUAC, is a tool capable of detecting CED and providing recommendations based on the results of CED detection in pregnant women who utilize artificial intelligence by having accurate measurement results with an accuracy value of 100%.