Skripsi
IMPLEMENTASI ALGORITMA SUPPORT VECTOR MACHINE DAN ANT MINER UNTUK KLASIFIKASI PREDIKAT KELULUSAN MAHASISWA ORGANISASI DAN NON-ORGANISASI
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.
Inventory Code | Barcode | Call Number | Location | Status |
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2307004797 | T128120 | T1281202023 | Central Library (REFERENS) | Available but not for loan - Not for Loan |
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