Integrating MLP With Algorithm with AHP Modification For Car Evaluation

Abstract

Analytic Hierarchy Process is a well-known technique in decision making to handle the complexity of multicriteria problems based on hierarchical criteria and sub-criteria structures, evaluate alternative problems and rankings, and choose the best alternative. Decision results in the form of the best alternative are obtained based on the priority weight that each attribute has. The weight search process is carried out by forming a pairwise comparison matrix. But the problems that often occur when doing pairwise comparisons, the AHP method cannot provide a consistent comparison value, especially for problems with a large number of criteria and alternatives. Inconsistent pairwise comparisons will result in the weight of the criteria compared cannot describe the actual conditions. To avoid the problem of inconsistency in the AHP method can be done by minimizing the formation of pairwise comparison matrix. This study discusses how the search process weighted on the problem of Multiple Attribute Decision Making (MADM), especially in AHP techniques using a multilayer perceptron network in determining alternative selection. The results of the study prove that the use of multilayer perceptron can provide better results and save time because the creation of a pairwise comparison matrix is smaller.