IMPLEMENTASI ALGORITMA SUPPORT VECTOR MACHINE DAN ANT MINER UNTUK KLASIFIKASI PREDIKAT KELULUSAN MAHASISWA ORGANISASI DAN NON-ORGANISASI

SEPTRIANI, RIZKA and Utami, Alvi Syahrini and Darmawahyuni, Annisa (2023) IMPLEMENTASI ALGORITMA SUPPORT VECTOR MACHINE DAN ANT MINER UNTUK KLASIFIKASI PREDIKAT KELULUSAN MAHASISWA ORGANISASI DAN NON-ORGANISASI. Undergraduate thesis, Sriwijaya University.

	Text RAMA_55201_09021381924139.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy
	Text RAMA_55201_09021381924139_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (5MB) | Request a copy
	Text RAMA_55201_09021381924139_0022127804_8968340022_01_front_ref.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_55201_09021381924139_0022127804_8968340022_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_55201_09021381924139_0022127804_8968340022_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (258kB) | Request a copy
	Text RAMA_55201_09021381924139_0022127804_8968340022_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (1MB) | Request a copy
	Text RAMA_55201_09021381924139_0022127804_8968340022_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (172kB) | Request a copy
	Text RAMA_55201_09021381924139_0022127804_8968340022_06.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (128kB) | Request a copy
	Text RAMA_55201_09021381924139_0022127804_8968340022_07_ref.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (132kB) | Request a copy
	Text RAMA_55201_09021381924139_0022127804_8968340022_08_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (211kB) | Request a copy

Abstract

Student academic performance is one of the benchmarks for the success of a university, especially the management of study programs. In addition to lecture activities carried out officially in various universities, there are also other lecture activities that can be followed by students, so that it can make students not maximize their learning activities so that they become negligent and have an impact on the final grade and study period. Therefore, the author conducted research to model the classification of graduation predicates of student who participated in organizations and non-organizations using the Support Vector Machine algorithm method and the Ant Miner algorithm. This research uses data on students who have graduated, research use data collection methods through the academic community of the Faculty of Computer Science, Informatics Engineering Study program, Sriwijaya University so that accurate data will be obtained. The accuracy rate obtained by using the support vector machine algorithm using a linear kernel and a C value parameter of 10 gets an accuracy of 0.80 or equivalent to 80% while the accuracy rate obtained using the M value parameter of 10 gets an accuracy of 0.62 or equivalent to 62%. this proves that the support vector machine algorithm method is better than the ant miner algorithm in the classification process in this research.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	IMPLEMENTASI ALGORITMA
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ1-1570 Mechanical engineering and machinery
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Rizka Septriani
Date Deposited:	31 Aug 2023 02:38
Last Modified:	31 Aug 2023 02:38
URI:	http://repository.unsri.ac.id/id/eprint/128120

Actions (login required)

View Item