Implementasi Sistem Fuzzy untuk Proses Pendukung Keputusan Menggunakan Metode Inferensi Minimum (Studi Kasus pada Sistem Pendukung Keputusan Pembelian Sepeda Motor)
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Institusion
Universitas Sumatera Utara
Author
Novaldy, Andika (STUDENT ID : 061401050)
(LECTURER ID : 0027017403)
(LECTURER ID : 0004097901)
(LECTURER ID : 0027017403)
(LECTURER ID : 0004097901)
Subject
Datestamp
2022-12-15 07:56:58
Abstract :
Today many brands and types of motorcycles sold in the market allowing users to be difficulty in determining the choices that fit their needs. Along with those problems there are also an increasing use of computers, one is the use of computers in providing the best decision on an issue, in this case is motorcycles selection. That is why it was designed a decision support system for motorcycle selection to allow users choicing a motorcycle that suited to their needs. This application was built using fuzzy logic and minimum inference method. Fuzzy logic is very flexible because it can tolerance a state when the data is not completely correct or completely wrong, so it will very suitable when the available data were only in qualitative form. The requested input is the criteria of motorcycle specifications in qualitative form and the results is recommendation of the best motorcycle according to user input sorted by the level of conformance. The method of testing was conducted using BlackBox Method which have proved that the whole process of the application running correctly. Furthermore, it used questionnaire to obtain input from respondents overall rated very well with the percentage value 86.3%. Universitas
Today many brands and types of motorcycles sold in the market allowing users to be difficulty in determining the choices that fit their needs. Along with those problems there are also an increasing use of computers, one is the use of computers in providing the best decision on an issue, in this case is motorcycles selection. That is why it was designed a decision support system for motorcycle selection to allow users choicing a motorcycle that suited to their needs. This application was built using fuzzy logic and minimum inference method. Fuzzy logic is very flexible because it can tolerance a state when the data is not completely correct or completely wrong, so it will very suitable when the available data were only in qualitative form. The requested input is the criteria of motorcycle specifications in qualitative form and the results is recommendation of the best motorcycle according to user input sorted by the level of conformance. The method of testing was conducted using BlackBox Method which have proved that the whole process of the application running correctly. Furthermore, it used questionnaire to obtain input from respondents overall rated very well with the percentage value 86.3%. Universitas
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