PENERAPAN ALGORITMA NAÏVE BAYES UNTUK PENENTUAN CALON PENERIMA BEASISWA PADA SMK PASIM PLUS SUKABUMI

Abstract

Every institution in particular school lots of scholarship devoted to students, whether or not capable of achieving good results. The scholarship is intended to help ease the burden of costs for students who get it. With a large number of students who apply to receive scholarships and criteria of assessment that much anyway, so not all students who apply for scholarships can be granted. SMK Pasim Plus Sukabumi does not yet have a system which can assist in the determination of scholarship recipients more effectively and efficiently. The Naive Bayes algorithm method is expected to be able to assist in the determination of the prospective grantee. Naive Bayes algorithm is one method of data mining contains ten classification data mining is most popular among the other algorithm-the algorithm. Naive Bayes method also assessed potential both in classifying documents than other classification methods in terms of accuracy and computational efficiency. From the test results by measuring the performance of the naive Bayes algorithm using the method of testing the Confusion Matrix and ROC Curve, the naive Bayes algorithm is known that have Accuracy namely 96.67% by value of the AUC that is 0.990. See the value of the naive Bayes algorithm AUC the naive Bayes algorithm, then include the group classification is very good, because the results of his AUC values between 0.90-1.00. naive Bayes algorithm for it is expected to produce a decent Scholarship candidates, so that the school can help in taking decisions more quickly, more effectively and efficiently..