Open AccessBadminton player scouting analysis using Frequent Pattern growth (FP-growth) algorithm
Author(s) -
Luki Ardiantoro,
Nani Sunarmi
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1456/1/012023
Subject(s) - indonesian , computer science , set (abstract data type) , athletes , field (mathematics) , software , algorithm , data mining , mathematics , linguistics , pure mathematics , programming language , physical therapy , medicine , philosophy
FP Growth algorithm is widely used to analyze patterns from a huge amount of data with (frequent) repeated items. The objective of this research is to analyze playing pattern a badminton player, one of a popular sport in Indonesia. The data set was generated from a technical stroke during the game. The model used in this study was Jonathan Christie a top Indonesian badminton player. The method of data collection was done by dividing the playing field into various areas of the game. Observations were made by using the software, to calculate and classify the types of stroke that carried out by the athlete. The result of this research; the tactical approach of Jonathan Christie during this match was described. The data obtained would be very useful for the coach to improve the athlete’s performance. Another advantage obtained was the analysis of the athlete’s performance can be done with a quantitative approach so that it can enrich the current methods. As the conclusion, the FP Growth algorithms were able to describe the game pattern of a badminton athlete, JC by using PHP and MySQL. Sport science has become a necessity to develop to increase athletes’ competitiveness.