Perbandingan Algoritma Decision Tree (C4.5) Dan Naïve Bayes Pada Data Mining Untuk Identifikasi Tumbuh Kembang Anak Balita (Studi Kasus Puskesmas Kartasura) - Listiana, Mila; , Drs. Sujalwo, M.Kom; , Dedi Gunawan S.T., M.Sc (2015)
Puskesmas is one of health agencies located in the sub-district. Health agencies as an effort in support of good service necessary management of working order , neat and thoroughly so that will produce rapid information , proper and accurate. In health agency lots of data from which every year increase. One of them is growth and data development of toddler. But with so much data growth and development of toddler also getting harder these data studied further, and generally the data is only used as an archive only. Utilization of data mining techniques are expected to help in the growth and development of toddler overcome unfavorable currently. At this research we compared the techniques classification of performance decision tree method (C4.5) and Naive Bayes. Attributes are used consisted of Gender, Age, Weight, Time, Regional and growth and development. By using each training data and testing data as much as 304 Data. Results of research conducted, based on the value of accuracy and the recall of Naive Bayes is higher than the decision tree is to the value accuracy of 75.66% for decision tree and 76.97% for Naive Bayes. For the value recall of Naive Bayes its more superior is 96.89% compared decision tree is 89.78%. Although in this research the level Precision was higher decision tree is 85.23% compared Naive Bayes is 84.17%. The final result of this research is Naive Bayes method is better used than in the decision tree method with a total value of 250.67% for decition tree and 258.03% for Naive Bayes.