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Abstract

Premature labor is a condition of the birth of a baby less than 37 weeks with a fetal weight of less than 2500 grams. Where the rate of premature infant delivery leading to death increased from 2000 to 2014 by 8.5%. Classification for early handling of premature labor is one of the solutions that is often studied. Some of the classification algorithms that are often used are C4.5 and Random Forest. From the two algorithms, the best algorithm will be selected by looking at the highest level of accuracy to be selected. From the calculation results of the Random Forest algorithm, an accuracy of 99.38% was obtained with an AUC of 0.988. Meanwhile, the achievement of the C4.5 algorithm is 98.75% with an AUC of 0.5. Therefore, from the results that can be compared with the accuracy values of the two algorithms, it is concluded that the Random Forest algorithm is better accurate to overcome premature data when compared to the C4.5 algorithm