Decision Support System to Recommend Best Taekwondo Athlete Assessment using AHP and TOPSIS Methods Tirta Dwi Budiarto (a*), Silvester Dian Handy Permana (a), Budi Arifitama (a)
a) Program Studi Teknik Informatika, Universitas Trilogi
Jl. TMP Kalibata No.1, Jakarta 12760, Indonesia
*tirtabudiarto[at]trilogi.ac.id
Abstract
Belt Promotion Test (BLT) in the branch of taekwondo sports becomes a benchmark to find out the extent of the potential possessed by athletes during the training period. The assessment team was formed by Sabeums who already hold the black belt level and 1 kukkiwon. However, the current assessment process has not been able to provide an objective assessment of taekwondo athletes to be given level jumps as a prize for the best athletes in BLT. The assessment team does not conduct an assessment process that is in accordance with the BLT assessment provisions to assess the performance of each athlete. Then a Decision Support System (DSS) is needed to find the best athletes in BLT. This study applies the Analytical Hierarchy Process (AHP) method which is useful for calculating the weights of each criterion. The AHP method is combined using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to get compiled tests and improve computing quickly and efficiently. The use of AHP and TOPSIS methods is done in order to make decisions more accurately in providing recommendations for the assessment of the best taekwondo athletes. This research is expected to provide an objective assessment of the best taekwondo athletes. The results of the application of the AHP and TOPSIS algorithms are able to provide an assessment of the best taekwondo athletes based on the criteria assessed. AHP and TOPSIS algorithms provide the best athlete ratings to Jasmine Alisha Khaira Wilda with a final value of 0.642.
