OPTIMASI BACKWARD ELIMINATION PADA KLASIFIKASI PENYAKIT ISPA MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER

ISPA cases in Indonesia are still a problem that threatens the health of various age groups, especially toddlers. The process of handling ISPA needs to be carried out quickly and precisely, one of the process is by classifying ISPA. This research classifies ISPA using the NaiveeBayessClassifier algorithm with the addition of variable selection BackwardeElimination. The NaiveeBayessClassifier algorithm has the advantage of testing category-type data with a fast calculation process and high accuracy. The NaiveeBayessClassifier test obtains an accuracy of 79,41%. The addition of Backward Eliminationnto the NaiveeBayessClassifier algorithm aims to select irrelevant variables and is able to increase the previously accuracy of 7,84%, so that obtains an accuracy of 87,25%. This point out that the performance of the selection variable BackwardEElimination is effective in optimizing the performance of the NaiveeBayessClassifier in classifying ISPA.