IMPLEMENTATION TECHNIQUE METHOD FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) IN ASSESMENT OF DOG CHARACTERISTICS SYSTEM

Abstract

Dogs are the most populated animals in 2016 according to a survey of pet populations by the UK's association of animal food makers (PFMA). With so many types of dogs and different characteristics, not all humans can choose the type of dog that suits their situation and condition. These non-conformities cause dogs to be dumped on the streets or abandoned without proper care.
 Therefore the dog characteristics assessment system is made which aims to facilitate the user in choosing the type of dog that is suitable for the user's situation and condition. This system is made using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution). This system is based on the data of dogs registered with the AKC (American Kennel Club). This system uses eight criteria, three criteria for the filter process and five criteria for the weighting process. Of the five weighting criteria, there are three cost attributes and two benefit attributes. In the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest (farthest) distance from the negative ideal solution.
 The results obtained from this assessment system are by theory-based testing 50 times with a 78% suitability match percentage.
 The conclusion obtained from this research is the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is quite efficient to be applied in a dog characteristic assessment system