Penentuan Tenaga Kependidikan Berprestasi Dengan Menggunakan Metode Profile Matching

Abstract

The quality of an educational staff can be seen from the realization of the employee's work targets (SKP) which is supported by the results of the assessment that have been determined by colleagues and the leadership of the education staff itself. The determining factors are work overload which is calculated from (SKP realization value – SKP target value) + attitude behavior value. In this case, after the behavioral assessment at Udayana University is only accumulated in a simple mathematical manner, where colleagues and leaders fill out a satisfaction questionnaire and each question has an assessment, it will be accumulated and taken on average to be accumulated with excess workload. This of course can lead to inappropriate results because the things given are very subjective which results in perfect scores, but not objective, so that it is difficult for HR to determine employees who have the right attitude. Profile Matching is the process of comparing the actual data value of a profile to be assessed with the expected profile value, so that differences in competence (also called GAP) can be known. The smaller the resulting GAP, the greater the weight value. Implementation of Profile Matching on data of outstanding education personnel at Udayana University is carried out by making several aspects such as administration, leadership, and personality as core factors and secondary factors. The results of the implementation at Gambar 8 show that the use of the profile matching method for this case has been successfully implemented, in the implementation of this method it does not assume that the highest value is the best value, but demands that the ideal value used is the maximum value so that expectations do not exceed the ideal value, and changes in the weight of the criteria affect the resulting alternative decisions, so it should be noted that the filling percentage of core factor, secondary factor, and the presentage of aspect needs to be adjusted to the data conditions, to get objective results.