Selection and Recommendation Scholarships Using AHP-SVM-TOPSIS | Zendy

M. Gilvy Langgawan Putra | Zendy; Whenty Ariyanti | Zendy; Imam Cholissodin | Zendy

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Selection and Recommendation Scholarships Using AHP-SVM-TOPSIS

Author(s) -

M. Gilvy Langgawan Putra,

Whenty Ariyanti,

Imam Cholissodin

Publication year - 2016

Publication title -

journal of information technology and computer science

Language(s) - English

Resource type - Journals

eISSN - 2540-9824

pISSN - 2540-9433

DOI - 10.25126/jitecs.2016111

Subject(s) - analytic hierarchy process , topsis , scholarship , selection (genetic algorithm) , support vector machine , computer science , rank (graph theory) , artificial intelligence , feature selection , constant (computer programming) , machine learning , operations research , mathematics , political science , law , combinatorics , programming language

. 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 , e = 0.0001, and C = 1. Keywords: Selection , Recommendation, Scholarships , AHP-SVM-TOPSIS

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