PENCARIAN BAKAT (TALENT SCOUTINGI) RENANG PADA ANAK MENGGUNAKAN ALGORITMA K-NEAREST NEIGBORS

AR. RISQI, NADIAH IZZATI and Rini, Dian Palupi (2025) PENCARIAN BAKAT (TALENT SCOUTINGI) RENANG PADA ANAK MENGGUNAKAN ALGORITMA K-NEAREST NEIGBORS. Undergraduate thesis, Sriwijaya University.

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Abstract

Swimming requires an objective and efficient talent identification system. This study develops a machine learning-based system using the K-Nearest Neighbors (KNN) algorithm to predict young athletes' potential based on anthropometric and motor skill data. The dataset consists of 50 normalized samples evaluated through K-Fold Cross Validation (K=5 and 10). Test results show the optimal configuration at K=2 with 60% accuracy for both validation methods. Although the overall accuracy remains below 65%, this system can serve as a preliminary tool for talent scouting, particularly for short and long distance categories. These findings indicate the need for further development in terms of data quantity and more optimal classification methods.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	K-Nearest Neighbor, Talent Scouting, Antropometri, Renang
Subjects:	Q Science > Q Science (General) > Q1-295 General Q Science > Q Science (General) > Q300-390 Cybernetics > Q325.5 Machine learning T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Nadiah Izzati Ar Risqi
Date Deposited:	22 Sep 2025 03:22
Last Modified:	22 Sep 2025 03:22
URI:	http://repository.unsri.ac.id/id/eprint/184438

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