<![CDATA[The measurement of lecturer performance is done in terms of objectivity and the absence of measurable variables used, so that the assessment variables used in the measurement process are based on one's perception. Inaccuracy in measuring lecture performance can be applied with the fuzzy mamdani method so that measurements become more precise. Weighting is done for each parameter that refers to the Key Performance Indicator. To support the performance of the lecturer, the data was obtained from lecturer data in the Faculty of Engineering which was processed to get the output. The formation of fuzzy mamdani rules has 79 rulebases from experts, from the results of research that has been done, the input variables for fuzzy calculations in this system are the Education, Research, Community Service, Self-development and output variables namely the lecturer performance value. The fuzzy set used in each fuzzy variable is not good, moderate, and good. The Mamdani fuzzy method is a mathematical framework used to present uncertainty, obscurity, inaccuracy. In fuzzy mamdani done in stages (a) the formation of the fuzzy set, (b) the application of the implication function, (c) forming the rules, (d) affirmation (defuzzification). From the results of the study, obtained a comparison of measurements with KPI without fuzzy and KPI with fuzzy which produces fluctuating values, where KPI using fuzzy has better results than KPI without fuzzy. In the fuzzy mamdani method produces values that move smoothly, this difference is shown from the significance value (2-tailed) produced is smaller than α = 0.05 which is 6.09 x 10-5, so that the KPI uses fuzzy significantly different from KPI without fuzzy. ]]>
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