IMPLEMENTASI APLIKASI JUAL BELI MOBIL BEKAS DENGAN METODE ANALYTICAL HIERARCHY PROCESS DAN NAIVE BAYES

Widi Santoso, Viny Christanti Mawardi, Tri Sutrisno

Abstract


One area of life that is affected by the rapid development and advancement of technology is the automotive sector. Information technology bridges various groups who participate in automotive transaction activities. Therefore, the physical condition and performance of an automotive are determining factors for a buyer who wants to make a purchase.

Not all types of automotive offered meet the buyers' standards, nor do they have a selling price in accordance with the quality described by the seller. The Analytical Hierarchy Process (AHP) method helps determine the type of automotive that suits the buyers' wishes and the Naïve Bayes method helps determine the selling price according to the quality of the automotive offered.

The Analytical Hierarchy Process (AHP) method is a decision support model that describes a complex multi-factor or multi-criteria problem into a hierarchy, which in turn can organize complex problems into a more orderly and systematic manner. The Naïve Bayes method is a classification using probability and statistical methods that predict future opportunities based on past experiences. Naïve Bayes calculates a set of probabilities by adding up the frequency and value combinations from the given dataset. Based on the comparison of the calculation results with the tests carried out, the AHP method obtains an accuracy rate of 100% in displaying the criteria for cars being sold. Meanwhile, the Naïve Bayes method obtains an accuracy rate of 100% in determining whether a dealer is interested in buying a car or not.


Keywords


Analytical Hierarchy Process, Automotive Industry, Car Buying and Selling, Naïve Bayes, Automotive.

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