Development of a web-based system for storing and accessing kinesthetic motor skills data of young volleyball players

Along with the development of the world of sport today, efforts to manage the sport of volleyball are very important to implement, both in management in society, education, and management at the local, national and international levels. The aim of this study was to develop an instrument capable of identifying players’ movements, based on dominant movements in volleyball games, using technology integrated with a system for later storage on the web. The research method had four stages, namely (1) preliminary study, (2) validation by experts, (3) acceptance test, and (4) usefulness test. Validation was carried out by volleyball experts, sports talent identification experts, and coaches, with assessment indicators including suitability, accuracy, ease, and practicality. Acceptance testing was carried out by applying the instrument to 120 young volleyball players to collect categorization data. The results showed that the instrument was effective and feasible to use in identifying the kinesthetic movements of young volleyball players, and providing recommendations for players with good kinesthetic movement abilities. This instrument is expected to help sports teachers and volleyball coaches in identifying players’ movements more easily.

Authors

Institutions

Publication Details

Journal
SPORT TK-Revista EuroAmericana de Ciencias del Deporte
Published
2025-04-25
DOI
https://doi.org/10.6018/sportk.660131
Primary Topic
Sports and Physical Education Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a web-based system for storing and accessing kinesthetic motor skills data of young volleyball players

Sepriadi Sepriadi, Endang Sepdanius, Muhamad Sazeli Rifki, Hermanzoni et al.
SPORT TK-Revista EuroAmericana de Ciencias del Deporte
Sports and Physical Education Research
article

Development of a web-based system for storing and accessing kinesthetic motor skills data of young volleyball players

Sepriadi Sepriadi, Endang Sepdanius, Muhamad Sazeli Rifki, Hermanzoni, Ariando Ariston, Raudhatul Hanifah, Alnedral
article en

Abstract

Along with the development of the world of sport today, efforts to manage the sport of volleyball are very important to implement, both in management in society, education, and management at the local, national and international levels. The aim of this study was to develop an instrument capable of identifying players’ movements, based on dominant movements in volleyball games, using technology integrated with a system for later storage on the web. The research method had four stages, namely (1) preliminary study, (2) validation by experts, (3) acceptance test, and (4) usefulness test. Validation was carried out by volleyball experts, sports talent identification experts, and coaches, with assessment indicators including suitability, accuracy, ease, and practicality. Acceptance testing was carried out by applying the instrument to 120 young volleyball players to collect categorization data. The results showed that the instrument was effective and feasible to use in identifying the kinesthetic movements of young volleyball players, and providing recommendations for players with good kinesthetic movement abilities. This instrument is expected to help sports teachers and volleyball coaches in identifying players’ movements more easily.

SPORT TK-Revista EuroAmericana de Ciencias del DeporteVol. 14
State University of Padang (ID)
Openalex Percentile: Top 83%
Sports and Physical Education Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.