PREDIKSI TINGKAT KELULUSAN SISWA ELEARNING BERBASIS ALGORITMA FUZZY C-MEANS
Abstract
Sulitnya melakukan prediksi sebuah kelompok belajar melahirkan banyak metode dalam pengukuran, metode tersebut antara lain clustering. Pada metode ini termasuk jenis unsupervised sebab tidak terdapat satu atributpun yang digunakan untuk memandu proses pembelajaran, semua data diperlakukan sama. Pada pengelompokan ini data yang diproses bersifat kuantitatif sehingga setiap item data mendapat porsi dan perlakuan sama, kondisi datapun juga mirip satu dengan yang lainnya. Data yang diolah berasal dari data primer berupa kelompok jumlah login, akses materi, jumlah membuat thread diforum diskusi, jumlah tanggapan forum komentar diskusi dan jumlah mengerjakan soal latihan. Metode pengolahan dengan algoritma Fuzzy C-Means, adapun data yang diolah sebanyak 257 pengguna khususnya siswa atau mahasiswa. Atribut yang diolah terdiri dari 5 item aktifitas. Untuk hasil akhir terbentuk 2 kelompok dimana kelompok pertama dinyatakan lulus sesuai prediksi dan kelompok kedua tidak lulus. Hasil ini nantinya dibandingkan dengan data real atau empiris sehingga diperoleh jumlah siswa yang lulus dan tidak, sehingga dapat ditarik kesimpulan tingkat keakuratan metode ini dalam jumlah persen. Untuk nilai setiap kelompok diperoleh atribut login 11.961 s/d 27.921, akses materi pembelajaran 10.678 s/d 15.059, membuat thread 3.875 s/d 5.059, keaktifan diforum 9.741 s/d 23.329 dan mengerjakan soal ujian 9.751 s/d 13.420 dinyatakan lulus. Keakuratan diperoleh 78 persen sesuai dengan prediksi algoritma fuzzy c-means. Untuk pengukuran keefektifan algoritma ini digunakan SSE(sum of square error).
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