Klasifikasi Infertilitas (Ketidaksuburan) pada Wanita menggunakan Algoritma Naïve Bayes

Abstract

The presence of a baby is a dream for every married couple, especially for those who have long married However, not all married couples can get biological offspring easily, it is caused by the presence of infertility (infertility). Infertility is problems with the reproductive system characterized by failure to get pregnant after 12 months or more of being married and having sex at least 2-3 times a week regularly regularly without using contraception. Based on the WHO report, globally it is estimated that There are cases of infertility in 8-10% of couples, which is about 50 million to 80 million couples. The aim of this research is to use the Nave Bayes algorithm for the classification of infertility in children women can help public knowledge, especially married couples to detect early infertility that makes it difficult to get offspring, considering infertility in women is a case that is no less important than other health problems. The evaluation and validation process uses rapidminer for the classification of infertility in children women with the algorithm used, namely nave Bayes, has very high accuracy high with an accuracy value of 91.67%. Based on the results of the classification of infertility in women with the nave Bayes algorithm can help the community to detect early perform a medical examination.