Information system for diagnosing Neonatal Jaundice using rule-based algorithm

Abstract

Neonatal jaundice often occurs in newborns characterized by a yellow discoloration of the sclera and baby's skin due to high levels of bilirubin in the blood. The occurrence of jaundice needs done identified to the development of hyperbilirubinemia which has the potential to become a toxic that can cause kernicterus. Detection of jaundice by manual (visual) is still often done by parents and health workers, so that the results of the diagnosis obtained are less accurate. This study proposes an innovative used of information systems in detecting jaundice using the SDLC (Systems Development Life Cycle) method with a waterfall model. Retrieval of data in this study with a quasi experiment using non-probability sampling with consecutive sampling on 48 newborn respondents. The result of this study indicate that the information system that has been built can detect jaundice faster as much as 2.1 minutes with an accuracy rate of 91.7%, can provide appropriate solutions and an effective level of use of information systems of 90.5% which can be used as an innovation in helping overcome jaundice problems.