PERBANDINGAN ALGORITMA K-NEAREST NEIGHBOR DAN SUPPORT VECTOR MACHINE DALAM MEMPREDIKSI KELULUSAN MAHASISWA

DEAZ, ZAKI ILHAMY and Utami, Alvi Syahrini and Miraswan, Kanda Januar (2022) PERBANDINGAN ALGORITMA K-NEAREST NEIGHBOR DAN SUPPORT VECTOR MACHINE DALAM MEMPREDIKSI KELULUSAN MAHASISWA. Undergraduate thesis, Sriwijaya University.

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Abstract

Students are an important asset for any educational institution. Therefore, student graduation rates need to be noticed and considered. The percentage of on-time graduation of students is one of the points of accreditation assessment in higher education. With this, action is needed from the institution in the form of monitoring and evaluating student graduation. One way that can be done is by using classification to predict student graduation. In this study, the performance of the K-Nearest Neighbor and Support Vector Machine algorithms will be compared in predicting student graduation. For K-NN, tried 15 values of k ranging from 1 to 15. The results showed that the highest accuracy was obtained by the value of k = 4 with an accuracy of 82%. For SVM, using the linear method obtained an accuracy of 77%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Algoritma
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Zaki Ilhamy Deaz
Date Deposited:	19 Sep 2022 04:59
Last Modified:	19 Sep 2022 04:59
URI:	http://repository.unsri.ac.id/id/eprint/79012

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