Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Vol 9 No 1: Februari 2020

Fuzzy Multi-Attribute Decision Making untuk Klasifikasi Potensi Kewirausahaan Berdasarkan Theory of Planned Behavior

Nova Rijati (Institut Teknologi Sepuluh Nopember)
Diana Purwitasari (Institut Teknologi Sepuluh Nopember)
Surya Sumpeno (Institut Teknologi Sepuluh Nopember)
Mauridhi Hery Purnomo (Institut Teknologi Sepuluh Nopember)



Article Info

Publish Date
05 Feb 2020

Abstract

Indonesia government has launched a program to encourage youth entrepreneurship as a strategy to improve national economy. This paper proposes a method to find an entrepreneurial potential based on academic behavior features that are extracted from the Higher Education Database PDDikti. The proposed approach applies the Fuzzy Multi-Attribute Decision Making (FMADM) technique. Rules for extracting features of student academic behavior were following Theory of Planned Behavior (TPB) and resulting in 14 features. The FMADM model combines Fuzzy Simple Additive Weighting and Fuzzy Technique for Order Preference by Similarity to Ideal Solution, which is called FSAW-TOPSIS. Friedman Test demonstrated that FSAW-TOPSIS gives more optimal solution with the highest Mean Rank of the potential entrepreneurial value of 2.96. Besides, through Hamming Distance Test, FSAW-TOPSIS results the best order with a 98% percentage and ranking of the smallest Squared Error of 0.3%, which makes the proposed model offered a better solution. It can be concluded that using TPB variables in PDDikti environment with FSAW-TOPSIS technique provides an optimal recommendation on student entrepreneurship potential, which can be used as a part of a decision-making system for higher education management.

Copyrights © 2020






Journal Info

Abbrev

JNTETI

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

Description

Topics cover the fields of (but not limited to): 1. Information Technology: Software Engineering, Knowledge and Data Mining, Multimedia Technologies, Mobile Computing, Parallel/Distributed Computing, Artificial Intelligence, Computer Graphics, Virtual Reality 2. Power Systems: Power Generation, ...