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Dandy Pramana Hostiadi
Ni Luh Putri Srinadi
I Made Darma Susila

Abstract

Dosen memiliki kewajiban Tridarma yaitu wajib melaksanakan pendidikan, penelitian dan pengabdian kemapada masyarakat. Terdapat beberapa variabel yang dapat digunakan dalam mengukur kualitas kinerja dosen, seperti motivasi, kepemimpinanan, budaya organisasi, dan pelatihan. Beberapa penelitian sebelumnya memodelkan pengukuran dengan pendekatan klaisifikasi. Namun model klasifikasi perlu dioptimalkan untuk mendapatkan hasil yang optimal, misalnya dalam dengan pengukuran kemiripan data kinerja dosen sehingga mampu mendapatkan model yang optimal. Metode pengukuran kemiripan data dapat digunakan agar dapat mengelompokkan berdasarkan kelompok pola data dan mengurangi data yang bersifat redundant. Semakin banyak data yang memiliki kemiripan maka model akan mengklasifikasikan lebih cepat dan tepat. Penelitian ini melakukan optimasi klasifikasi menggunakan pengukuran kemiripan yaotu euclidean distance untuk mengelompokkan data sehingga didapatkan kelompok data yang serupa dan digunakan dalam pengukuran klasifikasi. Metode klasifikasi yang digunakan adalah naive bayes, dan optimasi menunjukkan model memiliki performa yang lebih baik dibandingkan tanpa menggunakan metode analisis kemiripan data dengan akurasi sebesar 0.757, precision 0.763, recall 0.757 dan F1-score adalah 0.755,. Pendekatan yang diusulkan dapat digunakan di perguruan tinggi untuk mengukur kinerja dosen yang menggunakan metode klasifikasi dengan hasil yang tepat dan cepat.

Article Details

How to Cite
Hostiadi, D. P., Ni Luh Putri Srinadi, & I Made Darma Susila. (2023). Optimasi Klasifikasi Naive Bayes Menggunakan Analisis Kemiripan Data Untuk Mengukur Kinerja Dosen. Jurnal Sistem Dan Informatika (JSI), 17(2), 81 - 88. https://doi.org/10.30864/jsi.v17i2.519
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