Selection and Recommendation Scholarships Using AHP-SVM-TOPSIS




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


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How to Cite

Putra, M. G. L., Ariyanti, W., & Cholissodin, I. (2016). Selection and Recommendation Scholarships Using AHP-SVM-TOPSIS. Journal of Information Technology and Computer Science, 1(1), 1–13.