Open AccessApplication of AHP Analysis to Increase Employee Career Paths in Decision Support Systems
Author(s) -
Julius Santony,
Faisal Amir,
Sumijan Sumijan,
Rice Novita
Publication year - 2019
Publication title -
journal of physics: conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
ISSN - 1742-6588
DOI - 10.1088/1742-6596/1339/1/012030
Subject(s) - analytic hierarchy process , ranking (information retrieval) , hierarchy , computer science , process (computing) , decision support system , selection (genetic algorithm) , knowledge management , process management , operations research , management science , machine learning , engineering , artificial intelligence , economics , market economy , operating system
Employee career paths are one way for companies to improve employee performance in educating their students. The problem of manager in decision making uses the selection of methods and assessment processes subjectively so that the process is not in accordance with the goals of the career path. Therefore, an Analytical Hierarchy Process (AHP) method is needed to help make decisions. In this study, using the criteria of Planning, Teaching, Evaluating and Learning. Ranking results obtained that Learning criteria are very important criteria with calculation results of 0.602 when compared to the other three criteria. The Decision Support System (DSS) application provides the final results obtained from testing the calculation that the alternative Employee C is the best employee with a calculation of 0.227 compared to the other alternatives. The DSS application using the AHP method has a data accuracy rate of 86.67% and can be used as a support for manager decisions to make recommendations for increasing employee career paths.