Skripsi
PERBANDINGAN ALGORITMA BACKPROPOGATION DAN SUPPORT VECTOR MACHINE (SVM) UNTUK PREDIKSI MASA STUDI MAHASISWA AKTIF BERORGANISASI
In a college, students not only have the opportunity to learn as usual but also to develop skills that can be honed by participating in one or more organizations on and off campus. Many people think that being involved in organizations will prolong a student's study duration, but that is not entirely true. Many of these students focus on their organizations while still performing well in their studies. In this research, a comparison between the Backpropagation and Support Vector Machine (SVM) algorithms is conducted. The accuracy level obtained from both methods will be used as a reference to compare the performance of these algorithms. During the training of the Backpropagation algorithm, the best accuracy achieved was 72% with a learning rate parameter of 0.1 and 0.001. On the other hand, the Support Vector Machine achieved the best accuracy of 81% with a parameter value of C = 10 and a Polynomial kernel.
Inventory Code | Barcode | Call Number | Location | Status |
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2307005638 | T124650 | T1246502023 | Central Library (Referens) | Available but not for loan - Not for Loan |
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