Pemodelan Sistem Fuzzy Dengan Menggunakan Matlab

Authors

  • Afan Galih Salman Bina Nusantara University

DOI:

https://doi.org/10.21512/comtech.v1i2.2349

Keywords:

fuzzy logic, soft computing, fuzzy system, decision making

Abstract

Fuzzy logic is a method in soft computing category, a method that could process uncertain, inaccurate, and less cost implemented data. Some methods in soft computing category besides fuzzy logic are artificial network nerve, probabilistic reasoning, and evolutionary computing. Fuzzy logic has the ability to develop fuzzy system that is intelligent system in uncertain environment. Some stages in fuzzy system formation process is input and output analysis, determining input and output variable, defining each fuzzy set member function, determining rules based on experience or knowledge of an expert in his field, and implementing fuzzy system. Overall, fuzzy logic uses simple mathematical concept, understandable, detectable uncertain and accurate data. Fuzzy system could create and apply expert experiences directly without exercise process and effort to decode the knowledge into a computer until becoming a modeling system that could be relied on decision making.
Dimensions

Plum Analytics

References

Kusumadewi, S. (2002). Analisis dan Desain Sistem Fuzzy Menggunakan Tool Box MATLAB. Jakarta: Penerbit Graha Ilmu.

Kusumadewi, S., & Purnomo, H. (2004). Aplikasi Logika Fuzzy untuk Mendukung Keputusan. Yogyakarta: Graha Ilmu.

Marimin. (2005). Teori dan aplikasi sistem pakar dalam tehnologi manajerial. Bogor: IPB Press.

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Published

2010-12-01

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Section

Articles
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