Open AccessImplementation of AHP and SAW Methods for Optimization of Decision Recommendations
Author(s) -
Deborah Kurniawati,
Febri Nova Lenti,
Rudi Wahyu Nugroho
Publication year - 2021
Publication title -
journal of international conference proceedings
Language(s) - English
Resource type - Journals
eISSN - 2622-0989
pISSN - 2621-993X
DOI - 10.32535/jicp.v4i1.1152
Subject(s) - analytic hierarchy process , consistency (knowledge bases) , computer science , decision analysis , decision maker , management science , operations research , optimal decision , decision problem , business decision mapping , hierarchy , decision support system , process (computing) , mathematics , engineering , artificial intelligence , decision tree , statistics , economics , algorithm , market economy , operating system
Differences in interest in decision making are one of the things that must be facilitated in decision support applications. The most basic difference of interest in decision making is the difference in the weight of the importance of each criterion used. Each decision maker has their own interest in the criteria used. If these differences can be facilitated properly, the resulting decision recommendations can be optimal, in this case more in line with the interests of the users. The model is designed using the Analytical Hierarchy Process (AHP) and Simple Additive Weight (SAW) methods, using 5 criteria. The final result of the AHP method is in the form of criteria weights that are in accordance with the interests of decision makers and in accordance with the consistency of the comparisons that have been given. The resulting weight will be used in the final calculation of SAW, namely in the calculation of alternative weights. By using AHP, the weight of the criteria becomes more subjective according to the interests of decision makers. Thus, the resulting alternative recommendations become more optimal because they are in accordance with the needs of decision makers.