Plag_Lovebirds type identification designing based on color using automaton theory

Sumarno, Sumarno Plag_Lovebirds type identification designing based on color using automaton theory. Asosiasi Dosen PkM Indonesia (ADPI).

Text Lovebirds type identification designing based on color using automaton theory.pdf Download (3MB)

Abstract

Lovebirds are a unique and legendary bird species that can attract most bird lovers in Indonesia. The colors and types are also varied, ranging from valves, non-valves, colorful feathers starting from the lungs, eyes, chest, tail wings, and so forth. In addition to a variety of colors, the birds singing is also another attraction for bird lovers. But for the general public as well as beginner Lovebirds hobbyists, it is difficult to know the type of each Lovebirds they meet or have. This is due to the lack of knowledge they have about Lovebirds, so we need a system that can help them in solving problems to find out the name of the species on a specific basis. Expert systems are computer programs that simulate the reasoning of an expert with expertise in a particular area of knowledge. Expert systems work based on theory, rules, and knowledge base. The theory is the necessary foundation in making an expert system as a substitute for an expert's logic mindset. Automaton theory of intelligent abstract modeling recognition machine is one theory that can work on a system to resolve uncertainty according to predetermined rules, especially reading the input of words or context-free language, and then can conclude whether the writing is following the state of the regulation set in the programming language. The results of this study resulted in an expert system application to identify Lovebirds based on the color of feathers found in the body of the lovebird using finite-state Automata.

Item Type:	Other
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Engineering > School of Computer Engineering
Depositing User:	Mr sumarno sumarno
Date Deposited:	05 Mar 2021 02:25
Last Modified:	06 Oct 2021 07:28
URI:	http://eprints.umsida.ac.id/id/eprint/8353

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