CD Skripsi

Prediksi Prestasi Belajar Siswa Menggunakan Algoritma Naive Bayes Classifier Di Smkn 1 Barumun

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ABSTRACT
Prediction is an attempt to look at past conditions to predict future conditions. Prediction of student achievement is something that is very important in the world of education that can increase quality graduates. This study aims to implement the Naïve Bayes Classifier Algorithm to predict student achievement for one semester at SMKN 1 Barumun. The initial data used was 1191 student data before preprocessing, the amount of data after the preprocessing process became 1039 student data with a ratio of 80% and 20%, where for training data there were 831 and data testing amounted to 208 student data with 6 criteria or attributes for the requirements student achievement consisting of the average value of assignments, average midterm scores, average final exam scores, average number of class attendance, average practicum scores and average attitude values used for the classification process. Predictive results from data testing obtained 129 students categorized as outstanding students and 79 students categorized as underachieving. Testing data with Split Validation resulted in an accuracy of 96.15%, 94.16% precision and 100% recall. Testing data with Cross Validation as much as 10 times of testing resulted in an average accuracy of 97.60%, 92% precision and 100% recall.
Keywords: Naïve Bayes Classifier Algorithm, Confusion Matrix, Cross Validation, Prediction, Achievement

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

1903111396

Penerbit

Pekanbaru : Universitas Riau – FMIPA – Sistem Informasi., 2023

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

1903111396

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

SISTEM INFORMASI

Info Detail Spesifik

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Pernyataan Tanggungjawab

PUJA

Versi lain/terkait

Lampiran Berkas

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