<![CDATA[Controlling the quality of learning is very important and influences the accreditation of study programs at the Faculty of Mathematics and Natural Sciences Udayana University, as a guarantor of the quality of graduates. Apply pricipal component analysis to reduce the number of determinant attributes of learning quality, with the aim of looking at the data structure with fewer variables. The control chart is a multivariate control chart that is used to view the potrait of the quality of learning in the Mathematics and Natural Sciences Faculty, using new variables obtained from principal component analysis. The results obtained from principal component analysis show that the contribution of the learning quality indicators is univen. The potrait of the quality of learning at the Faculty of Mathematics and Natural Sciences obtained from the individual-moving range (I-MR) and the control chart shows the need for corrective actions and monitor regularly to improve the quality of learning.]]>
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