Analisa Tingkat Trauma Kecelakaan dengan Menerapkan Metode Fuzzy Mamdani
Abstract
When a person experiences a traffic accident it always impacts the victims and their families up to the person who sees the accident. As for the impact in the form of physical and psychological impacts, physical impacts such as emotional as a stress reaction, depression and psychological factors such as anxiety, brain scans and anxiety responses that cause situations out of control. Therefore, in the future, the work of doctors will be greatly helped by an expert system that is filled with a number of knowledge (all types of drugs and their effects) that the experts themselves do not necessarily remember. Expert systems can add knowledge to medical personnel as a reference material to determine the possibility of diagnosing someone's psychology during trauma after an accident and its solutions. This study applies an expert system for the diagnosis of one of the fuzzy inference methods is Mamdani. Mamdani uses the min-max operator in the process of implication and composition of rules, so it is often referred to as the min-max method. Based on the description above, it can be seen that the fuzzy method is one method that has been widely used in software development for the diagnosis of a disease. The expert system modeling is to determine the level of accident trauma based on symptoms felt by patients. The results of the depression level of workers are obtained from the Fuzzy Mamdani algorithm by identifying the symptoms they experience. And Fuzzy Mamdani went well in analyzing the symptoms arising from the trauma.
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