KLASIFIKASI KETEPATAN WAKTU LULUS MAHASISWA JURUSAN MATEMATIKA UNIVERSITAS PATTIMURA MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER
DOI:
https://doi.org/10.30605/proximal.v7i2.4153Keywords:
Ketepatan Waktu Lulus Mahasiswa, Naïve Bayes Classifier, K-Fold Cross Validation, KlasifikasiAbstract
Perguruan Tinggi memiliki peranan yang besar dalam mencetak sumber daya manusia yang kompeten, sehingga kualitas dan akreditasi Perguruan Tinggi menjadi hal yang perlu diperhatikan. Salah satu indikator yang mempengaruhi kualitas dan akreditasi Perguruan Tinggi adalah persentasse mahasiswa lulus tepat waktu. Oleh karena itu, perlu adanya perhatian khusus dari Perguruan Tinggi mengenai ketepatan waktu lulus mahasiswa. Dengan melihat lima faktor yang mempengaruhi ketepatan waktu lulus mahasiswa yakni Usia Masuk Perguruan Tinggi, Jenis Kelamin, Akreditasi Asal SMA, Jalur Penerimaan dan IPK diharapkan dapat memberikan prediksi mahasiswa tersebut lulus tepat waktu atau tidak. Metode yang digunakan dalam mengklasifikasi ketepatan waktu lulus mahasiswa adalah metode Naïve Bayes Classifier, karena metode ini memiliki akurasi yang tinggi dan dapat bekerja lebih baik pada kasus di dunia nyata. Hasil klasifikasi ketepatan waktu lulus mahasiswa Jurusan Matematik Tahun Akademik 2015/2016 sampai 2019/2020 dengan menggunakan metode Naïve Bayes Classifier dengan K-Fold Cross Validation untuk K=5 sampai K=10 bantuan software Rapid Miner berhasil diklasifikasikan ketepatan waktu lulus mahasiswa dengan persentase keakuratan tertinggi yaitu untuk K= 10 sebesar 70% dan nilai error sebesar 30% serta nilai AUC 72%, yang artinya model pada metode Naïve Bayes Classifier diklasifikasikan dengan baik.
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