Selection and Recommendation Scholarships Using AHP-SVM-TOPSIS

Putra, M Gilvy Langgawan
Ariyanti, Whenty
Cholissodin, Imam

Journal of Information Technology and Computer Science
Vol. 1 No. 1: June 2016

Abstract. Gerakan Nasional Orang Tua Asuh Scholarship offers a number of scholarship packages. As there are a number of applicants, a system for selection and recommendation is required. we used 3 methods to solve the problem, the methods are AHP for feature selection, SVM for classification from 3 classes to 2 classes, and then TOPSIS give a rank recommendation who is entitled to receive a scholarship from 2 classes. In testing threshold for AHP method the best accuracy 0.01, AHP selected 33 from 50 subcriteria. SVM has highest accuracy in this research is 89.94% with Sequential Training parameter are λ =0.5, constant of γ =0.01 , ε = 0.0001, and C = 1. Keywords: Selection, Recommendation, Scholarships, AHP-SVM-TOPSIS