A rule-based method for living organisms classification

• Published in: IOP conference series. Materials Science and Engineering Vol. 403; no. 1; pp. 12082 - 12089
• Main Authors: Desiani, A, Arhami, M, Firdaus, Maiyanti, S I
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.09.2018
• Subjects: Chaining; Classification; design search research; expert system; Expert systems; Knowledge representation; Living Organism; Organisms; Taxonomy
• ISSN: 1757-8981; 1757-899X; 1757-899X
• DOI: 10.1088/1757-899X/403/1/012082

The implementation of an expert system for classification of a living organism could help researchers to classify an organism without having to face the complexities of a dichotomous key. This paper proposes a new system that can inference and give a solution for classification living organisms based on rule-based in taxonomy biology. The knowledge in taxonomy is represented by the rules-based method as a set know ledge for the system. the system is named as the expert system for living organisms. the system can be a solution to overcome obstacles in biological research caused by the problem of identification of living organisms. The system opens the possibilities to integrate other automated taxonomy systems because It can be used not only for a specific species but for all of other living organisms. The expert system of the classification is applied Peffer's DSRCM as a framework and guidelines. Forward chaining modified with backward chaining used as reasoning technique in the system. The expert system has tested on some groups respondent where all of the respondents give scores around 80-90 for the performance system. It shows that the system works well for classification living organims.