<![CDATA[In this study, two methods were used to determine the feasibility of giving motorbike credit, namely the Analytical Hierarchy Process (AHP) and the Simple Additive Weighting (SAW) method to determine the weight of the accuracy value in the feasibility of granting motor loans. Results based on the Hierarchical Weighted Factor Matrix with AHP for all criteria normalized hierarchical weighting for all criteria with the elements in each column divided by the total number in the respective column, then you will get the normalized relative weight. The eigenvector value generated from the average relative weight value for each row shows that the most important criterion for customers who wish to apply for credit. Income with a weight of 0.649 or 64.9%, then followed by a family card with a weight of 0.088 or 8.8%, and domicile is 0.21 or 21%. Whereas the results based on ranking using the SAW method for all Kritera whose weighting is normalized is that the V1 ranking is the first rank because it has a value greater than the other values of 1.03 where V1 is the preference value of alternative A1, so that A1 in this case is Yogi Danuarta who be the best alternative or selected prospective customers to get motorbike loans.]]>
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