Indoor Air Pollutants Data Correlation Analysis Enhancing Sports Training Information Systems (Case Study: East Jakarta - Indonesia)

Air quality has garnered significant attention from researchers in the twenty-first century. It is widely recognized that air pollution is a critical public health issue and a significant environmental challenge on a global scale, prompting increased focus from the scientific community. Indoor air pollutants pose a substantial risk to human health, resulting in millions of deaths each year. Various factors influence the quality of air in sports facilities. Elevated levels of CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> exceeding 1000 ppm can lead to sick-building syndrome, impacting athletic performance and sports outcomes. This research aimed to examine the relationship between air pollutant levels to aid in developing sports training information systems. The study employed a quantitative approach, collecting primary data independently through sensor-based measurements, descriptive analyses, and Spearman correlation. Indoor air pollutants pose a significant risk to human health, leading to millions of deaths annually. Various pollutants contribute to indoor air pollution, highlighting the importance of identifying their primary sources and concentrations and devising effective strategies for managing and enhancing indoor air quality. The findings reveal a strong positive correlation between <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{PM}_{1}, \text{PM}_{2.5}$</tex>, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{PM}_{10}$</tex>. Humidity exhibits a minimal association with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{PM}_{1}, \text{PM}_{2.5}$</tex>, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{PM}_{10}$</tex>, with correlations ranging from 0.27 to 0.29. A moderate negative correlation of 0.58 exists between humidity and temperature. Temperature and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{PM}_{1}, \text{PM}_{2.5}, \text{PM}_{10}$</tex>, and CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> demonstrate low negative correlations, ranging from −0.32 to −0.35. The correlation between CO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\text{PM}_{1}, \text{PM}_{2.5}, \text{PM}_{10}$</tex>, and humidity yields low negative values of −0.03, −0.01, −0.01, and −0.14, indicating their insignificance.