Sinkron : Jurnal dan Penelitian Teknik Informatika
Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022

ANALISIS PERBANDINGAN PEMBOBOTAN ROC DAN FULL CONSISTENCY METHOD (FUCOM) PADA MOORA DALAM PENGAMBILAN KEPUTUSAN

Prayoga, Nanda Dimas (Unknown)
Zarlis, Muhammad (Unknown)
Efendi, Syahril (Unknown)



Article Info

Publish Date
12 Aug 2022

Abstract

Decision support system is a system that can assist companies in making policy. There are several methods in a decision support system, one of which is the MOORA method. The MOORA method does not have a systematic weight determination. In several studies, the determination of the weight value is determined by experts in their field so that the value is less objective. So in this study, the Rank Order Centroid (ROC) and Full Consistency Method (FUCOM) weighting methods will be used systematically and objectively which will be applied to the MOORA method and a comparison of the results of these methods will be carried out with the calculation of the accuracy of the confusion matrix. The purpose of this study was to analyze the results of the weighting comparison using Rank Order Centroid (ROC) and Full Consistency Method (FUCOM) on the MOORA method so as to produce good accuracy. Based on the results of the study, testing with ROC weights on MOORA obtained results of 77.78% accuracy, 84% precision and 84% recall. While testing with ROC weights on MOORA obtained results of 77.78% accuracy, 84% precision and 84% recall. And testing with ROC+FUCOM weights on MOORA obtained 91.67% accuracy, 94% precision and 94% recall. So it can be concluded that the ROC+FUCOM weighting on MOORA produces good accuracy.

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Journal Info

Abbrev

sinkron

Publisher

Subject

Computer Science & IT

Description

Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial ...