year 11, Issue 1 (Spring 2023)
Ann Appl Sport Sci 2023, 11(1): 0-0 |
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Ermawan Susanto * 
1, Mujriah Bayok2 , Rabwan Satriawan3 , Rifqi Festiawan4 , Dennis Dwi Kurniawan5 , Firmansyah Putra6
1, Mujriah Bayok2 , Rabwan Satriawan3 , Rifqi Festiawan4 , Dennis Dwi Kurniawan5 , Firmansyah Putra6
1- Department of Physical Education & Sport, State University of Yogyakarta, Indonesia , ermawan@uny.ac.id
2- Department of Sport & Health Education, Universitas Pendidikan Mandalika, Lombok, Indonesia
3- Department of Physical Education, STKIP Taman Siswa, West Nusa Tenggara, Indonesia
4- Department of Physical Education, Jenderal Soedirman University, Indonesia
5- Department of Physical Education & Sport, State University of Yogyakarta, Sleman, Indonesia
6- Gradute School, State University of Yogyakarta, Sleman, Indonesia
2- Department of Sport & Health Education, Universitas Pendidikan Mandalika, Lombok, Indonesia
3- Department of Physical Education, STKIP Taman Siswa, West Nusa Tenggara, Indonesia
4- Department of Physical Education, Jenderal Soedirman University, Indonesia
5- Department of Physical Education & Sport, State University of Yogyakarta, Sleman, Indonesia
6- Gradute School, State University of Yogyakarta, Sleman, Indonesia
Abstract: (3445 Views)
Background. The importance of predicting talents in children is so that hidden sports talents have opportunities to be developed.
Objectives. This study aims to predict the talent level of children 12-15 years old in athletics.
Methods. The research used the ex-post facto descriptive method. The population is 507 children, consisting of 283 boys and 224 girls in two cities, Salatiga City and Lombok City. Samples were selected by random cluster sampling. The instrument uses ten kinds of predictive tests, including height, weight, the span of the arm, length of leg, sit & reach, standing broad jump, 40 m sprint, 10-second step frequency, shaken, and 800 m run. Data collection techniques using talent prediction tests. Data analysis using Criterion-Referenced Standards.
Results. The results showed that there were 17 children (2%) in the very talented category, 30 children (9%) talented, 91 children (16.5%) moderately gifted, and 349 children (72.5%) under-talented. Prediction test results from Salatiga showed that there were four talented in sprint and jump, two talented in jump, and one expert in throw numbers. The distribution of talent shown from Lombok is five proficient in sprint and jump, three capable in a sprint, and two talented in throw numbers. Talent identification prediction tests are proven to predict the potential talent of children in athletics. The cities of Salatiga and Lombok are the centers of athletic seedlings that are used as benchmarks for achievement.
Conclusion. This test can predict the level of athletic talent in children aged 12-15 years old.
Objectives. This study aims to predict the talent level of children 12-15 years old in athletics.
Methods. The research used the ex-post facto descriptive method. The population is 507 children, consisting of 283 boys and 224 girls in two cities, Salatiga City and Lombok City. Samples were selected by random cluster sampling. The instrument uses ten kinds of predictive tests, including height, weight, the span of the arm, length of leg, sit & reach, standing broad jump, 40 m sprint, 10-second step frequency, shaken, and 800 m run. Data collection techniques using talent prediction tests. Data analysis using Criterion-Referenced Standards.
Results. The results showed that there were 17 children (2%) in the very talented category, 30 children (9%) talented, 91 children (16.5%) moderately gifted, and 349 children (72.5%) under-talented. Prediction test results from Salatiga showed that there were four talented in sprint and jump, two talented in jump, and one expert in throw numbers. The distribution of talent shown from Lombok is five proficient in sprint and jump, three capable in a sprint, and two talented in throw numbers. Talent identification prediction tests are proven to predict the potential talent of children in athletics. The cities of Salatiga and Lombok are the centers of athletic seedlings that are used as benchmarks for achievement.
Conclusion. This test can predict the level of athletic talent in children aged 12-15 years old.
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APPLICABLE REMARKS
APPLICABLE REMARKS
• It is suggested that Indonesia should use a sports science approach through a prediction test of athlete talent. According to the results of this study, the athlete's talent prediction test is very helpful in getting information about potential athletes.
• The athletic talent identification program is emphasized only at 12-15 years. According to the study results, this age is a safe range for implementing the talent prediction test. Meanwhile, after 15 years, it is included in the category of talent development.
• Anthropometric measurements and biomotor tests in predicting talent are highly recommended. Test items can also be added with others to complete.
• Based on the results, this athletics talent prediction test can be applied to all regions of Indonesia with the characteristics of children in the age range of 12-15 years. Despite the selection of locations in two cities that are centers of excellent athletes.
• The test item compiled by the researcher is made with easy steps so that it can be used by regional trainers and sports teachers and does not require costly equipment.
• The city of Lombok has a higher number of talented athletes due to an intense training culture factor marked by a large number of athletic clubs. This confirms that the culture of practice influences the results of the aptitude prediction test.
• Considering the results, it is also recommended to look at other factors such as physiological, psychological, sociological, and cultural to see the prize optimally.
• The athletic talent identification program is emphasized only at 12-15 years. According to the study results, this age is a safe range for implementing the talent prediction test. Meanwhile, after 15 years, it is included in the category of talent development.
• Anthropometric measurements and biomotor tests in predicting talent are highly recommended. Test items can also be added with others to complete.
• Based on the results, this athletics talent prediction test can be applied to all regions of Indonesia with the characteristics of children in the age range of 12-15 years. Despite the selection of locations in two cities that are centers of excellent athletes.
• The test item compiled by the researcher is made with easy steps so that it can be used by regional trainers and sports teachers and does not require costly equipment.
• The city of Lombok has a higher number of talented athletes due to an intense training culture factor marked by a large number of athletic clubs. This confirms that the culture of practice influences the results of the aptitude prediction test.
• Considering the results, it is also recommended to look at other factors such as physiological, psychological, sociological, and cultural to see the prize optimally.
Type of Study: Original Article |
Subject:
Sport Management and its related branches
Received: 2022/01/18 | Accepted: 2022/05/11
Received: 2022/01/18 | Accepted: 2022/05/11
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