Implementasi Algoritma Naive Bayes Untuk Memprediksi Predikat Ketuntasan Belajar Siswa Pasca Pandemi Covid 19

Abstract

During the Covid-19 pandemic, SMA Negeri 3 Selong changed learning activities from what was originally face-to-face, but currently learning is being transferred to the Online Learning System (SPADA) using several existing platforms. Judging from the level of plurality of students' thinking patterns during the implementation of online learning there are many problems that arise, one of which is the instability of the internet network, the various hendpone media devices owned by students and the lack of student knowledge in using online platforms. The purpose of this study was to determine the indicator of the problem in the predicate of student learning completeness of class XII SMAN 3 Selong during the post-COVID-19 pandemic. The method used to solve this problem is the Naïve Bayes algorithm. Naive Bayes is a method of probabilistic reasoning. And in the future the results of this study are expected to be able to provide the right solution in solving problems in online learning.

Implementasi Algoritma Naive Bayes Untuk Klasifikasi Penerima Beasiswa (Studi Kasus Universitas Hamzanwadi)

“…Confussion Matrix Confusion Matrix ini meliputi informasi tentang kelas yang sebenarnya dan kelas prediksi. Confusion Matrix adalah salah satu alat ukur berbentuk matrik 2x2 yang digunakan untuk mendapatkan jumlah ketepatan algoritma yang dipakai[3].Rumus untuk menghitung nilai akurasi adalah sebagai berikut[12]:…”