Analisa Aktifitas Siswa di E-Learning Untuk Memprediksi Kelulusan Dengan Algoritma CART
Abstract
Abstrak
SMAN 1 Pare sudah cukup lama menerapkan E-learning dengan menggunakan moodle, namun “Logs” yang tersimpan di Moodle belum termanfaatkan.Dengan menggunakan metode CART, aktifitas siswa yang terekam di Logs Moodle dianalisa dan dimanfaatkan untuk memprediksi kelulusan siswa pada suatu mata pelajaran.
Proses Algoritma CART adalah dengan melakukan pemilahan untuk setiap decision node menjadi dua cabang yang digunakan untuk membentuk candidate split. Selanjutnya dipilih Candidate split untuk penyusunan inisial partisi pada root node dan decision node berikutnya, adapun kriteria pemilihan tersebut berdasarkan nilai goodness of split yang terbesar.
Penerapan Algoritma CART ini diujikan pada dua kategori data, yaitu data training dan data testing dengan perbandingan 80:20, dan diperoleh hasil pada data training dengan tingkat akurasi 75,9%. Adapun pada data testing diperoleh hasil dengan tingkat akurasi 78,43%.
Kata kunci:Logs, Moodle, CART, data training, data testing.
SMAN1Parehas applied the E-learning by usingModul, but the"Logs" arestoredinthe Moodleuntapped. Byusingthe CARTmethod, students’s activity arerecordedinthe LogsMoodleanalyzedandusedtopredict thestudents' graduationina subject.
CARTalgorithmis aprocessby sortingforeachdecisionnodeinto twobrancheswhichare usedtoform thecandidatesplit. Furthermorechoose the candidatesplitforthe preparation ofthe initialpartitionfor the rootnodeandthe nextnodedecision, while theselection criteriaarebased onthe value ofthe goodness ofa splitisgreatest.
Application ofthe CARTalgorithmwas testedontwocategoriesof data, ietraining dataandtesting datawith80:20ratio, and theobtainedresultson thetraining datawithan accuracyrate of75.9%. Theresultsobtainedontesting datawithan accuracyrate of78.43%.
Keywords : Logs, Moodle, CART, training data, testing data.
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