<![CDATA[Lecturer performance learning requires knowledge, namely a process to evaluate lecturer performance during the learning process, learning is carried out every semester using 20 variables. The research objective is to analyze the most influential lecturer performance variables with the concept of Principle Component Analysis (PCA) technique with the help of Minitab software. Where is the principle of PCA namely reducing data to make it easier to get information and evaluation for lecturers by using 20 variables to be analyzed in the Principle Component Analysis (PCA) technique, of the 20 variables there are 4 PC variables (Principle Components) to be analyzed namely PC1, PC9 , PC11 and PC16, namely PC1(0.24), PC9(0.5), PC11(0.35) and PC16(0.4) with maximum eigenvalue (1.6978), from the results of 4 PC variables it turns out that PC9 and PC11 are the most related or influential variables of all variables or components]]>
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