Quality Performance of X-Ray Aircraft Using Fuzzy Logic Based on Linear Regression

History records several adverse effects on the human body due to X-ray exposure. In 1897 in America, 69 cases of skin damage due to X-rays were reported, while in 1902 the number reported increased to 170 cases. In 1911 in Germany, 94 cases of tumors due to X-rays were also reported. This problem is caused by deviations in the accuracy of the X-ray output. To meet the requirements of the right standards, a suitability test is required on the X-ray machine. The purpose of this experiment is to obtain the best radiographic quality by evaluating optimal parameters such as kVp, mA, and exposure time so that the radiation output value is still within the tolerance limit. The methods used are linear regression and fuzzy logic, which are techniques for constructing line graphs between two data variables, namely x and y, where x is the setting and y is the measurement result, then the difference value (error) is obtained. The results of the difference values are grouped based on the passing value of the X-ray suitability test in table 1. From the results obtained, the % error value tested is a value below e-Max 10%, namely the average error % kVp of 1.47%, mA 0.078%, and t 2.35%, meaning that if converted to fuzzy logic, the radiation output quality value is very good.