Sistem Pakar Diagnosis Penyakit Sinusitis Menggunakan Metode Fuzzy Tsukamoto

Abstract

Sinusitis is one of the ENT diseases that is often found in medical practice. Very often people are not aware of the presence of this disease because education about this disease can be a factor in public ignorance of the dangers of sinusitis, thus increasing the risk of delays in treatment that should be done. This research aims to build an expert system based on the Tsukamoto fuzzy method that is able to diagnose sinusitis accurately according to expert knowledge so that it can help the public to recognize sinusitis that is being suffered, considering the cost of handling and consulting a doctor is relatively expensive. Fuzzy Tsukamoto has the ability to handle uncertain data so that it is appropriate to be implemented in processing sinusitis symptoms which are often difficult to distinguish from other ENT disease symptoms. This system is built and designed using IF-THEN rules implemented in fuzzy sets to get accurate diagnosis results. The results of the system evaluation show that this sinusitis diagnosis expert system provides results that are in accordance with the manual diagnosis made by ENT specialists and has a good accuracy rate of 81.82%. And based on the results of the User Acceptance Test (UAT) also shows that this system can provide accurate information and help early recognition of sinusitis. Thus, this expert system is expected to be a useful reference for the community in identifying and treating sinusitis more efficiently and relatively cheaply.