Pengembangan Model Sistem Pendukung Keputusan Dengan Kombinasi Metode Fuzzy Tahani Dan Topsis Dalam Penilaian Kinerja Instruktur - Safrizal, Safrizal; Susianto, Susianto (STIKOM Tunas Bangsa Pematangsiantar, 2019)
The instructor is the main academic implementer in the Institute for Aviation Education and Training (LPP). One of the factors that influence the success of LPP Aviation in improving student quality is the commitment and performance of instructors. One method used is to conduct an instructor performance appraisal process. The large number of Instructors in LPP Aviation is a separate issue in the assessment process, considering the process is based on subjectivity and has a great chance of making mistakes in the decision making, namely the selection of instructors who do not meet the desired standards and are not in accordance with the determination of instructor performance evaluation priorities. For this reason, a decision support system is needed in conducting the instructor's performance appraisal process. The Multi Attribute Decision Making (MADM) model has been widely used by decision makers to solve decision making problems with a variety of methods that can be used to find the best solution, but from these methods can still be developed with the aim of providing maximum decision results. In this research a decision support system model will be built with a combination of two methods, namely the Fuzzy Resistant method and TOPSIS which aims to manipulate the success data of instructors who are ambiguous by conducting a search for appropriate and accurate data for the criteria used in the assessment process LPP Aviation instructor performance by using Fuzzy-Resistant to get priority criteria in the form of rules, then ranking will be done by using TOPSIS in getting the quality of teaching conducted by LPP Aviation Instructors as the best instructor selection. The results of the flight instructor's performance evaluation with a combination of the Fuzzy Resistant method and TOPSIS, are based on 250 data tested samples, therefore, the accuracy value is 93%.