Decision Tree Algorithm In Analyzing The Incidence Of Neonatal Sepsis At Ulin Hospital Of Banjarmasin In 2016
- DOI
- 10.2991/smichs-17.2017.15How to use a DOI?
- Keywords
- Asphyxia, Baby's Body Temperature, Birth Weight, Gestational Age, Neonatal Sepsis, Premature Rupture of Membranes
- Abstract
Objective: To analyze the factors most related to the incidence of neonatal sepsis at Ulin Hospital of Banjarmasin in 2016. Method: This research used Rapid Miner simulation model with population of all newborns at Ulin Hospital of Banjarmasin in 2016 and the sample size was 210 infants consisting of 105 infants with neonatal sepsis and 105 infants without neonatal sepsis. The analysis used Algorithm C.45 (Decision Tree) to see the accuracy level, and Root Mean Squared Error. Results: The factors most closely related with the incidence of neonatal sepsis were gestational age 33.5 weeks with the strong power of relationship (0.643), accuracy rate of 80.95%, and mean error rate of 0.401. Conclusion: Infants born with a gestational age < 33.5 weeks are at risk of having neonatal sepsis while those born with a gestation age > 33.5 weeks are at risk when the born with asphyxia complication, birth weight 3875, and temperature> 37oC accompanied by labor trauma. Infants born with body temperature 37oC are at risk of having neonatal sepsis when it is accompanied by pregnancy complication such as premature rupture of membranes
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Fitri Yuliana AU - Novita Dewi Iswandari AU - Topan Aditya Rahman PY - 2017/12 DA - 2017/12 TI - Decision Tree Algorithm In Analyzing The Incidence Of Neonatal Sepsis At Ulin Hospital Of Banjarmasin In 2016 BT - Proceedings of the 2nd Sari Mulia International Conference on Health and Sciences 2017 (SMICHS 2017) PB - Atlantis Press SP - 117 EP - 123 SN - 2468-5739 UR - https://doi.org/10.2991/smichs-17.2017.15 DO - 10.2991/smichs-17.2017.15 ID - Yuliana2017/12 ER -