PERBANDINGAN METODE NAIVE BAYES DAN K-NEAREST NEIGHBOR UNTUK KLASIFIKASI KELULUSAN MAHASISWA TEKNIK INFORMATIKA UNIVERSITAS SRIWIJAYA

MALA, HUSNITA and Efendi, Rusdi and Saputra, Danny Matthew (2020) PERBANDINGAN METODE NAIVE BAYES DAN K-NEAREST NEIGHBOR UNTUK KLASIFIKASI KELULUSAN MAHASISWA TEKNIK INFORMATIKA UNIVERSITAS SRIWIJAYA. Undergraduate thesis, Sriwijaya University.

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Abstract

Student graduation is one of the areas included in the Internal Quality Assurance Standards (SPMI) of a university. Factors that can influence student graduation include the Semester Achievement Index (IPS) score, GPA, and Graduation Status. One of the methods that can be used to perform classfication is the Naive Bayes and K-Nearest Neighbor methods. The results obtained in the Naive Bayes methods test got an accuracy value of 43,3%, a precision value of 52,94%, and a recall value of 57,27%. And K-Nearest Neighbor method gets an accuracy value of 53,3%, a precision value of 32,08% and a recall value of 42.15%

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Perbandingan Metode Naive Bayes dan K-Nearest Neighbor, klasifikasi
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 11343 not found.
Date Deposited:	27 May 2021 03:11
Last Modified:	27 May 2021 03:11
URI:	http://repository.unsri.ac.id/id/eprint/46615

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