year 11, Issue 1 (Spring 2023)                   Ann Appl Sport Sci 2023, 11(1): 0-0 | Back to browse issues page


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Rohmat Nurjaya D, Ma'mun A, Rusdiana A, Gaffar Abdullah A, Cholik Mutohir T. A Fuzzy Logic Model for Talent Identification and Selection Indonesian Junior Rowing Athletes. Ann Appl Sport Sci 2023; 11 (1)
URL: http://aassjournal.com/article-1-1164-en.html
1- Sports Coaching Education Study Program, Faculty of Sports and Health Education, Indonesia University of Education, Bandung, Indonesia , dede-rohmat-n@upi.edu
2- Sports Education Study Program, Graduate School, Indonesian University of Education, Bandung, Indonesia
3- Sport Science Study Program, Faculty of Sports and Health Education, Indonesian Education University, Bandung, Indonesia
4- Sport Science Study Program, Faculty of Sports Science, State University of Surabaya, Jawa Timur, Indonesia
Abstract:   (1154 Views)
Background. Investigations in talent identification are mostly based on determining effective parameters, more specifically the determination of norms for Indonesian junior rowing athletes.
Objectives. This research aimed to design a smart model in talent identification and selection for rowing athletes based on the weighting of priority criteria generated from the analytic hierarchy process (AHP) of anthropometric, biomotor, psychological, physiological, and technical variables from fuzzy logic.
Methods. The method was mixed methods research (MMR), it involves the use of both quantitative and qualitative methods in a study. Furthermore, it selected important criteria through a hierarchical analytical process of anthropometric, biomotor, psychological, physiological, and technical variables. The norms of elite rowing junior athletes aged 16-18 years were used as a comparative index. Furthermore, the smart model is designed based on fuzzy logic using MATLAB software.
Results. The athletes were categorized into unmatched, semi-matched, matched, brilliant, and rare groups. The fuzzy testing of all talent identification and selection criteria for rowing athletes shows that Indonesian rowing male athletes must be in the "brilliant" classification or equal to 88.5% supported by anthropometric criteria, 10.6% supported by physiological criteria, and 89.4% supported by biomotor criteria.
Conclusion. Leg height and length, muscle power and leg strength, self-confidence and motivation, specific endurance, catch, drive, and recovery parameters were demonstrated as the main criteria and weighted by the analytic hierarchy process. This smart model analyzes these variables on the norms of elite rowing junior athletes and makes specific results from player talent. Therefore, It is a reliable and useful method for decision-making in talent identification and the selection of rowing athletes at a young age.
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APPLICABLE REMARKS
• The use of fuzzy logic in this study has shown a model as a tool for identification and selection in rowing sports.
• Fuzzy logic is very helpful in minimizing the element of subjectivity in talent identification and talent selection in rowing.

Type of Study: Original Article | Subject: Exercise, Training and Health
Received: 2022/10/11 | Accepted: 2022/12/23

References
1. Breitbach S, Tug S, Simon P. Conventional and Genetic Talent Identification in Sports: Will Recent Developments Trace Talent? Sports Med. 2014;44(11):1489-503. [DOI:10.1007/s40279-014-0221-7] [PMID]
2. Abbott A, Button C, Pepping GJ, Collins D. Unnatural selection: Talent identification and development in sport. Nonlinear Dynamics Psychol Life Sci. 2005;9(1):61-88.
3. Burgess DJ, Naughton GA. Talent development in adolescent team sports: a review. Int J Sports Physiol Perform. 2010;5(1):103-16. [DOI:10.1123/ijspp.5.1.103] [PMID]
4. Martindale RJ, Collins D, Daubney J, Martindale RJJ, Collins D, Daubney J. Talent Development : A Guide for Practice and Research Within Sport. Quest. 2005;57:353-75. [DOI:10.1080/00336297.2005.10491862]
5. Taylor P, Gulbin J, Weissensteiner J, Oldenziel K, Gagné F. European Journal of Sport Science Patterns of performance development in elite athletes. 2013;(March):37-41. [DOI:10.1080/17461391.2012.756542] [PMID]
6. Pickering C, Kiely J, Grgic J, Lucia A, Coso J del. Can Genetic Testing Identify Talent for Sport ? Genes (Basel). 2019;10:972. [DOI:10.3390/genes10120972] [PMID] [PMCID]
7. Pankhurst A, Collins D. Talent Identification and Development: The Need for Coherence Between Research, System, and Process. Quest. 2013;65(1):83-97. [DOI:10.1080/00336297.2012.727374]
8. Vaeyens R, Güllich A, Warr CR, Philippaerts R. Talent identification and promotion programmes of olympic athletes. J Sports Sci. 2009 Nov;27(13):1367-80. [DOI:10.1080/02640410903110974] [PMID]
9. Barreiros A, Côté J, Fonseca AM. From early to adult sport success: Analysing athletes' progression in national squads. Eur J Sport Sci. 2014;14(SUPPL.1):37-41. [DOI:10.1080/17461391.2012.671368] [PMID]
10. Pearson DT, Naughton GA, Torode M. Predictability of physiological testing and the role of maturation in talent identification for adolescent team sports. J Sci Med Sport. 2006;9(4):277-87. [DOI:10.1016/j.jsams.2006.05.020] [PMID]
11. Howe MJA, Davidson JW, Sloboda JA. Innate talents: Reality or myth? Behavioral and Brain Sciences. 1998;21(3):399-442. [doi:10.1017/S0140525X9800123X] [pmid:10097018] [DOI:10.1017/S0140525X9800123X] [PMID]
12. Lidor R, Côté J, Hackfort D. ISSP position stand: To test or not to test? The use of physical skill tests in talent detection and in early phases of sport development. Int J Sport Exerc Psychol. 2009;7(2):131-46. [DOI:10.1080/1612197X.2009.9671896]
13. Harre D. Principles of sports training based on experience and scientific research in the German Democratic Republic. Berlin: Sportverl. Berlin: Sportverl.; 1982.
14. Mirkolaee EG, Mohammad S, Razavi H, Amirnejad S. A Mini-Review of Track And Field's Talent-Identification Models in Iran and Some Designated Countries. Ann Appl Sport Sci. 2013;1(3):17-28.
15. Ko B. Sports Talent Identification and Selection in Korea. Int J Appl Sport Sci. 2014;26(2): 99-111. [DOI:10.24985/ijass.2014.26.2.99]
16. Abbott A, Collins D. A Theoretical and Empirical Analysis of a "State of the Art" Talent Identification Model. High Abil Stud. 2002;13(2):157-78. [DOI:10.1080/1359813022000048798]
17. Secher NH, Vaage O. Rowing performance, a mathematical model based on analysis of body dimensions as exemplified by body weight. Eur J Appl Physiol Occup Physiol. 1983;52(1):88-93. [DOI:10.1007/BF00429031] [PMID]
18. Bourgois J. Anthropometric characteristics of elite male junior rowers. Br J Sports Med. 2000;34(3):213-6. [DOI:10.1136/bjsm.34.3.213] [PMID] [PMCID]
19. Slater GJ, Rice AJ, Mujika I, Hahn AG, Sharpe K, Jenkins DG. Physique traits of lightweight rowers and their relationship to competitive success. Br J Sports Med. 2005;39(10):736-41. [DOI:10.1136/bjsm.2004.015990] [PMID] [PMCID]
20. Altenburg D, Mattes K, Steinacker J. Manual for Rowing Training. 2nd ed. Rheinbreitbach: Limpert Verlag GmbH, Wiebelsheim; 2012.
21. Jones G, Hanton S, Connaughton D. What is this thing called mental toughness? An investigation of elite sport performers. J Appl Sport Psychol. 2002;14(3):205-18. [DOI:10.1080/10413200290103509]
22. Lorains M, Ball K, MacMahon C. An above real time training intervention for sport decision making. Psychol Sport Exerc. 2013;14(5):670-4. [DOI:10.1016/j.psychsport.2013.05.005]
23. Noori M, Sadeghi H. Designing smart model in volleyball talent identification via fuzzy logic based on main and weighted criteria resulted from the analytic hierarchy process. J Adv Sport Technol. 2018;2(1):16-24.
24. Huang HC, Lin CT, Hu CS. Analysis of Selection Indicators of Badminton Players by the Delphi Method and Analytic Hierarchy Process. Int J Comput Sci Inf Technol. 2015;7(1):19-31. [DOI:10.5121/ijcsit.2015.7103]
25. Nisel, S., & Özdemir M. Analytic hierarchy process & analytic network process in sport: a comprehensive literature review. Int J Anal Hierarchy Process, 8(3). 2016; [DOI:10.13033/ijahp.v8i3.448]
26. Lorains M, Ball K, MacMahon C. Performance analysis for decision making in team sports. Int J Perform Anal Sport. 2013;13(1):110-9. [DOI:10.1080/24748668.2013.11868635]
27. Budak G, Kara İ, İç YT. Weighting the Positions and Skills of Volleyball Sport by Using AHP: A real life application. IOSR J Sport Phys Educ. 2017;4(01):23-9. [DOI:10.9790/6737-0401012329]
28. Nurjaya D, Abdullah AG, Ma'mun A, Rusdiana A, Nurjaya DR, Gafar Abdullah A. Rowing Talent Identification Based On Main And Weighted Criteria From The Analytic Hierarchy Process (AHP). J Engin Sci Technol. 2020;15(6):3723-3740.
29. Williams AM, Reilly T. Talent identification and development in soccer. J Sports Sci. 2000;18(9):657-67. [DOI:10.1080/02640410050120041] [PMID]
30. Poppleton, W. L., Salmoni AW. Talent Identification in Swimming. Journal of Human Movement Studies. J Hum Mov Stud. 1991;20:85-100.
31. Schorer J. Talent Development In Sport: Practical Application Of Talent Id And Development In Rowing. Canada. 2014.
32. Rees T, Hardy L, Güllich A, Abernethy B, Côté J, Woodman T, et al. The Great British Medalists Project: A Review of Current Knowledge on the Development of the World's Best Sporting Talent. Sports Med. 2016;46(8):1041-58. [DOI:10.1007/s40279-016-0476-2] [PMID] [PMCID]
33. Penichet-Tomás A, Pueo B. Performance conditional factors in rowing. Retos. 2017;(32):238-40. [DOI:10.47197/retos.v0i32.56067]
34. Bompa T, Buzzichelli C. Periodization Training for Sports. 3rd Editio. Champaign: Human Kinetics; 2015. 368 p.

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