Model Prediksi Dropout Mahasiswa Menggunakan Teknik Data Mining

Muchamad Taufiq Anwar, Lucky Heriyanto, Fadhla Fanini

Abstract


Salah satu permasalahan yang ada di Perguruan Tinggi XYZ adalah tingginya jumlah mahasiswa yang putus studi (dropout / DO), sehingga diperlukan upaya untuk minimalisasi jumlah mahasiswa yang dropout.  Penelitian ini bertujuan untuk membangun sebuah model yang dapat memprediksi apakah seorang mahasiswa akan lulus ataukah dropout. Data diambil dari data akademis mahasiswa angkatan 2014-2019. Pemrosesan awal data dilakukan dengan Python dan pemodelan dilakukan dengan menggunakan algoritma C4.5 / J48 pada perangkat lunak WEKA (Waikato Environment for Knowledge Analysis). Hasil menunjukkan bahwa atribut yang paling menentukan apakah seorang mahasiswa DO atau lulus adalah Indeks Prestasi Semester 1 dan Indeks Prestasi Semester 2, dengan akurasi model mencapai sebesar 90.6%.

Keywords


model prediksi putus studi; dropout; data mining C4.5; J48

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References


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DOI: https://doi.org/10.26877/jiu.v7i1.8023

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