Perbandingan Algoritma Decision Tree dan Support Vector Machine Dalam Pemilihan Calon Mahasiswa Penerima KIP-K
-
Nayaka Al Syahreal Kanaka
*
Universitas Indo Global Mandiri, Palembang,
Indonesia
- Rudi Heriansyah Universitas Indo Global Mandiri, Palembang, Indonesia
- Shinta Puspasari Universitas Indo Global Mandiri, Palembang, Indonesia (*) Corresponding Author
Abstract
KIP Kuliah is tuition assistance from the government for high school / equivalent graduates who have good academic potential but have economic limitations. There are many things that should be considered by universities before selecting prospective students who receive KIP Lecture so that selection can be done using machine learning and classification algorithms. In this research, two machine learning algorithms will be used including: Decision Tree and Support Vector Machine (SVM). Furthermore, these two algorithms will be tested and compared the final results. Both algorithms have different results. The highest level of accuracy, precision, recall, and F1 score is 100%. This value can be achieved by the Decision Tree algorithm because the dataset used is suitable for it to solve. Therefore, the Decision Tree algorithm is recommended to be used in selecting KIP College student candidates.
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