Lovebirds type identification designing based on color using automaton theory

  • Sumarno Sumarno Universitas Muhammadiyah Sidoarjo
  • Danang Tri Prasetiyo Universitas Muhammadiyah Sidoarjo
Keywords: Expert System, Lovebirds, Automaton Theory

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.

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Published
2019-11-29
How to Cite
Sumarno Sumarno, & Danang Tri Prasetiyo. (2019). Lovebirds type identification designing based on color using automaton theory. International Journal on Orange Technologies, 1(2), 35-46. Retrieved from https://journals.researchparks.org/index.php/IJOT/article/view/359
Section
Articles