Partus referral classification using backpropagation neural network

Abstract

The number of maternal mortalities in Indonesia keeps increasing significantly. The same thing occurs to the number of fetal mortalities which is not less than maternal ones. It is a given knowledge that the condition of expectants is mostly vulnerable to various disorders. Therefore, there is a high possibility of the occurrence of any maternal and fetal mortality. Things most likely to go wrong when the partus occurs and if the disorders are not treated as fast as possible, it will be very dangerous for the expectants. To minimize such occurrences, medical officers have been using a certain method named screening to detect which partus case which potentially has high risk before it is too late. Nevertheless, the results of screening are not always accurate. In this paper, we are going to come up with any other way, which is data mining computation. Data mining has known to be able to help human solving problems as well as a promising region for data classification. Most medical problems have been classified using data mining. Backpropagation Neural Network method will be used in this paper to classify partus referral cases. Thus, Backpropagation Neural Network will be compared to other algorithms to know if it is a better algorithm for this case based on real data of cohort register. The result of the researches confirms that Backpropagation Neural Network is the best of all three methods (Backpropagation Neural Network, C4.5 and Naive Bayes Classifier) used to classify partus referral.