Klasifikasi Prestasi Belajar Mahasiswa Menggunakan Variabel Nilai Dan Kehadiran : Studi Kasus Politeknik XYZ

Isrofi, Helmi (2022) Klasifikasi Prestasi Belajar Mahasiswa Menggunakan Variabel Nilai Dan Kehadiran : Studi Kasus Politeknik XYZ. Undergraduate thesis, Politeknik Negeri Jember.

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Abstract

In this study, researchers made a classification of learning achievement using value and attendance variables. In making this system, the authors use the Naive Bayes method as a method of calculating the classification data to be tested. To determine student learning achievement, detailed data processing is needed so that it can provide concrete values based on student grades and attendance. This problem often occurs in schools/universities, one of which is the XYZ Polytechnic, where there is no system for determining the level of student achievement. Therefore, Classification of Student Learning Achievement Using Value and Attendance Variables: Case Study of the xyz Polytechnic was created as a way to be able to classify grades and attendance in order to determine the level of student achievement concretely. For this research, the researcher conducted observations and interviews at the UPT where the xyz polytechnic case study was conducted to obtain test data in the database as testing material. Using value and attendance variables as initial input indexes and processed using the Naive Bayes method in order to produce accurate accurate values for classifying grades on student achievement.

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDK
Thesis advisorAgustianto, KhafidurrohmanNIDN0011129102
Uncontrolled Keywords: Naive Bayes, prestasi belajar, nilai, kehadiran, klasifikasi, data
Subjects: 410 - Rumpun Ilmu Teknik > 450 - Teknik Elektro dan Informatika > 458 - Teknik Informatika
Divisions: Jurusan Teknologi Informasi > Prodi D4 Teknik Informatika > Tugas Akhir
Depositing User: Helmi Isrofi
Date Deposited: 07 Dec 2022 01:39
Last Modified: 07 Dec 2022 01:40
URI: https://sipora.polije.ac.id/id/eprint/17949

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