Deteksi Kesehatan Janin Menggunakan Decision Tree dan Feature Forward Selection - Sulihati, Indah; Syukur, Abdul; Marjuni, Aris (Forum Kerjasama Pendidikan Tinggi, 2022)
Fetal health is very important, it is important for prospective mothers to know from an early age, until now a mother’s sense of ignorance abpout fetal health is very lacking and can result in fetal death. This is due to the lack of curiosity possessed by prospective moyhers and the lack of socialization and infrastructure from related parties about fetal health. Basically, the growth and development of a prospective fetus is very important so that it can be born healthy and without any obstacles at all.The pupose of this study was to detect fetal health using a decision tree classification algorithm with forward feature selection. This experiment was conducted using a public dataset of 2.126 patient data. The results showes that classification using a decision tree algorithm using a decision tree algorithm without feature selection resulted in an accuracy of 89.84%. While the use of the forward selection feature in this decision tree algorithm produces an accuracy of 91.06%.This shows that the use of the forward selection feature can increase accuracy by 1.22%.