ALGORITHM K-NN IN CLASSIFICING POTENTIAL AREAS OF MEN SINGLES BADMINTON PLAYERS IN INDONESIA

Abstract

Badminton is one sport that is contested at the Summer Olympics. Noted Indonesian badminton player has won 7 gold medals in the event. Until now Indonesia has not been able to add any gold medal from other sports that were competed in the Olympics. No wonder badminton has become a very important sport in Indonesia. Even though badminton is not from Indonesia, but Indonesia has given birth to many badminton legends since the 1960s until now. In the digital age sport science has now been developed in various countries to support athlete and official performance, but if this is not supported by the regeneration of young players, the achievement relay will be interrupted. How important it is to prepare young players with the potential to carry on the tradition of achievement in the badminton branch. Indonesia is one of the countries with a relatively slow regeneration of young players compared to other competing countries such as China, South Korea and Japan. The implementation of the K-Nearst Neighbor algorithm to classify areas with the potential of male singles badminton athletes in Indonesia is one solution so that the parent of Indonesian badminton organizations get a potential single male player. By using 1000 national male singles ranking data in Indonesia and classifying them into 3 regions, Potential areas, enough potential, and no potential.