Klasifikasi Kemandirian Siswa SMA/MA Double Track Menggunakan Metode Naive Bayes

  • Miftahul Walid Universitas Islam Madura
  • Finantun Halimiyah Universitas Islam Madura
  • Hozairi . Universitas Islam Madura
Keywords: Kemandirian Siswa, Naive Bayes Clasifier, Python

Abstract

Abstract- SMA /MA Double Track is a high school that carries out regular KBM (Teaching and Learning Activities) activities and organizes skills training activities side by side by utilizing local wisdom. The large number of participants in the SMA / MA Double Track program caused the East Java Provincial Education Office to have difficulty in determining the independence of participants. This is due to the absence of a method used to classify the independence of high school / MA Double Track students. Therefore, in this study tried to do a classification of student independence in SMA / MA Double Track. The method used is the Naive Bayes Classifier method because the Naive Bayes Classifier method is able to carry out the double track SMA / MA independence classification process with a good level of accuracy. The data set used was 40 data, with details of 30 training data and 10 test data, the input feature used consisted of six features, including (C1) making products, (C2) selling products, (C3) having a product catalog, (C4) having an online store, (C5) creating marketing media and (C6) sales transaction data, while for labels or outputs consisting of one feature, namely status. The results of the classification using the Naive Bayes Classifier method have an accuracy of 70%, from 10 test data there are 7 correct prediction data and 3 incorrect data. The research contribution is able to help the East Java Provincial Education Office map participants of the SMA / MA Double Track program who are independent (work or entrepreneurship) so that they are able to plan policies for next year.

 

Author Biographies

Miftahul Walid, Universitas Islam Madura

 

 

Finantun Halimiyah, Universitas Islam Madura

 

 

Hozairi ., Universitas Islam Madura

 

 

Published
2023-01-08