PERBANDINGAN METODE SUPPORT VECTOR MACHINE DAN RANDOM FOREST DALAM KLASIFIKASI WAKTU LULUS MAHASISWA UNIVERSITAS SRIWIJAYA

RAHMAN, ARIEF and Rini, Dian Palupi and Satria, Hadipurnawan (2024) PERBANDINGAN METODE SUPPORT VECTOR MACHINE DAN RANDOM FOREST DALAM KLASIFIKASI WAKTU LULUS MAHASISWA UNIVERSITAS SRIWIJAYA. Undergraduate thesis, Sriwijaya University.

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Abstract

Accreditation is a benchmark in assessing the quality and feasibility of universities. One of the accreditation assessments in universities is the percentage of student graduation. So, the percentage of late graduation and Drop Out (DO) can affect the assessment. Therefore, there is a need for a technique in classifying student graduation time that can help provide recommendations for making policies and preventing students from being late in their studies. This research aims to compare the performance of the Support Vector Machine and Random Forest methods. Both methods produce accuracy that can be used as a reference in comparing the performance of the two methods. The data used in this research is 243 data of Informatics Engineering students of Sriwijaya University consisting of 102 data on time and 141 data of students who did not graduate on time. The results of this study indicate that the accuracy of the Support Vector Machine method obtained the highest average accuracy value of 0.79 on the RBF kernel with parameter configuration C = 10, while Random Forest obtained the highest average accuracy value of 0.77 on the N-estimator parameter configuration = 50.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Klasifikasi, Ketepatan Waktu Lulus, Support Vector Machine, Random Forest.
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:	ARIEF RAHMAN
Date Deposited:	12 Sep 2024 02:00
Last Modified:	12 Sep 2024 02:00
URI:	http://repository.unsri.ac.id/id/eprint/157160

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