Decision Support for Selection of The Best Teachers Recommendations MCDM-AHP and ARAS Collaborative Methods

Abstract

The role of the teacher is very important for the progress of the nation which can increase the dignity of the nation. The quality of education can increase thanks to the support of teachers who have good dedication in developing the learning process, especially in curriculum development. The teacher's biggest contribution is to make students ready to become the nation's credible successors. The purpose of this study is to provide an assessment in the selection process of teachers in an objective and selective manner. Method recommendations that can be raised in this study are collaborative methods that play a role in multi-criteria selection, namely MCDM-AHP and ARAS. Both of these methods can be said to be able to implement a selective and credible selection process for teachers which is carried out through the stages of data conversion and normalization which in turn can determine decision support in the multi-criteria selection process. The results of this study provide the best solution in selecting alternatives with a multi-criteria barometer for measurements with the ARAS method. The resulting decision support for the selection process of twenty teachers resulting in the best assessment can be seen from the optimization function which is based on the maximum value default divisor basis. The results obtained from obtaining the highest utility value of the twenty alternatives, the top three values that can be drawn as support for decision making are owned by A3 with a utility weight of 0.891, followed by the two highest ratings A17 and A14 with respective weights of 0.888 and 0.884.