PENERAPAN ALGORITMA C4.5 UNTUK PREDIKSI EFEKTIVITAS PEMBELAJARAN DARING SELAMA MASA PANDEMI COVID-19 PADA SISWA SMA NEGERI KOTA BEKASI
The COVID-19 pandemic has changed all aspects of life, one of which is teaching and learning activities. Changes in teaching and learning activities also change the standard of effectiveness in online learning. Effectiveness in online learning has several different indicators from face-to-face learn...
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2021-07-21.
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100 | 1 | 0 | |a Bari Anandanu WIbowo, . |e author |
245 | 0 | 0 | |a PENERAPAN ALGORITMA C4.5 UNTUK PREDIKSI EFEKTIVITAS PEMBELAJARAN DARING SELAMA MASA PANDEMI COVID-19 PADA SISWA SMA NEGERI KOTA BEKASI |
260 | |c 2021-07-21. | ||
500 | |a http://repository.upnvj.ac.id/11201/1/ABSTRAK.pdf | ||
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500 | |a http://repository.upnvj.ac.id/11201/7/DAFTAR%20RIWAYAT%20HIDUP.pdf | ||
500 | |a http://repository.upnvj.ac.id/11201/11/LAMPIRAN.pdf | ||
500 | |a http://repository.upnvj.ac.id/11201/9/ARTIKEL%20KI.pdf | ||
520 | |a The COVID-19 pandemic has changed all aspects of life, one of which is teaching and learning activities. Changes in teaching and learning activities also change the standard of effectiveness in online learning. Effectiveness in online learning has several different indicators from face-to-face learning. In this study, what will be investigated is predicting the effectiveness of online learning based on available indicators using the classification method. The classification method used in this study is the C4.5 algorithm decision tree classification method. Data was collected by distributing questionnaires to high school students in Bekasi City. The data that has been collected will be pre-processed with data cleaning and selection. The data is then applied to the C4.5 algorithm process by training and testing the data. The results obtained in this study are in the use of the C4.5 algorithm, it was found that all indicators affect the effectiveness of online learning and the performance of the C4.5 algorithm, getting an average accuracy of 69% after evaluating with the k-fold cross validation method with a k value of 4. | ||
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655 | 7 | |a NonPeerReviewed |2 local | |
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