Penerapan Metode Fuzzy untuk Mengetahui Penyakit Radang Kelopak Mata (Blepharitis)

Abstract

Blepharitis or inflammation of the eyelids is one of the common eye diseases, characterized by inflammation of the edges of the eyelids that can cause discomfort, irritation, and even visual disturbances. This disease can be chronic with recurrent symptoms such as red eyes, itching, watering, and the appearance of crust on the eyelashes. Proper and prompt diagnosis is necessary so that medical treatment can be carried out effectively and further complications can be prevented. This study aims to design and build an expert system based on the Fuzzy Logic method in helping diagnose blepharitis. The fuzzy method was chosen because it is able to handle the uncertainty of symptom data that often arises in the medical diagnosis process. This system is developed through the identification of the common symptoms of blepharitis, then processed using the fuzzy membership function to determine the type of disease based on the degree of symptom onset. The output of the system is in the form of the results of the diagnosis of blepharitis along with initial treatment recommendations that can be used as a reference for users. The results of the system test show that the application of fuzzy logic is able to provide diagnosis results that are quite accurate, fast, and easy to understand both medical personnel and the general public. This system is expected to help increase public awareness about the importance of early detection of blepharitis, as well as being a tool in the initial medical decision-making process. However, the limitations of this study lie in the limited amount of data and coverage of the type of blepharitis, so further development is needed, both in expanding the knowledge base, increasing the variety of symptoms, and improving system interaction with users.