Implementasi Algoritma K-Nearest Neighbor Dalam Penentuan Jenis Kucing
ABSTRACT Muhammad Ihsan Al-Hafiz, C1655201059, 2021. Implementation of the K-Nearest Neighbor Algorithm in Determining the Types of Cats, Advisor I Hotmian Sitohang M.Kom, Advisor II Elia Zakharia M.T. Cats are one type of mammal that is liked by many people. There are many types of cats that can be found in this world, but not all types of cats can be used as pets by humans. Choosing the type of cat you want is not easy, you have to go through several considerations that must be considered before making a decision. Making the right decision based on the required standard categories, comprehensive information is needed, using existing criteria such as hair length, nose width, nose height, type of food, and type of hair. Then a system for determining the type of cat will be built that determines what type of cat is selected. In this research, it will be developed using the K-Nearest Neighbor method. This K-Nearest Neighbor method can solve a problem that contains ambiguous and uncertainty variables that become clear and definite. Test results using 50 cat data. The system for determining the type of cat using K-Nearest Neighbor using criteria for hair length, nose width, nose height, type of food, and type of hair is made to determine the type of cat for system testing using 50 data, there are 45 appropriate data and 5 data are not in accordance with the value of the match rate of the system is 90% with an error of 10%.