Optimization of FIS Tsukamoto using particle swarm optimization for dental disease identification

摘要

In the field of dentistry, there are several types of dental diseases. A wide variety of dental diseases become a difficulty for among doctors or medical students to identify the disease. The existence of a decision support system for doctors or medical students to define the disease on the determination of disease using fuzzy logic is still not optimal to generate accuracy point. In this research, the optimization of the decision-making results in a dental recommendation disease using Tsukamoto Fuzzy Inference System. Optimization using Particle Swarm Optimization PSO has been done on the membership degree function to get better results. The result shown accuracy point value reached 88% from average accuracy testing.