| Issue |
E3S Web Conf.
Volume 650, 2025
The 10th International Conference on Energy, Environment, and Information Systems (ICENIS 2025)
|
|
|---|---|---|
| Article Number | 02039 | |
| Number of page(s) | 10 | |
| Section | Environment | |
| DOI | https://doi.org/10.1051/e3sconf/202565002039 | |
| Published online | 10 October 2025 | |
Statistical quality control analysis in monitoring air pollution: Indoor particulate matters, temperature, and humidity (case study: South Jakarta, Indonesia)
1 Information Systems, Sampoerna University, South Jakarta, Greater Jakarta 12780, Indonesia
2 Industrial Engineering, Sampoerna University, South Jakarta, Greater Jakarta 12780, Indonesia
3 Management, Sampoerna University, South Jakarta, Greater Jakarta 12780, Indonesia
4 Computer Science, Respati Indonesia University, East Jakarta, Greater Jakarta 13890, Indonesia
* Corresponding author: tika.lestari@sampoernauniversity.ac.id
Assessing air quality is essential for minimizing exposure to harmful pollutants and creating strategies for cleaner air. Detailed air quality monitoring offers valuable insights into pollution sources, trends, and potential health risks. Quality Control (QC) is a fundamental component of process monitoring and improvement across various industries. Traditionally applied in manufacturing and industrial settings, QC principles have increasingly been adapted for use in environmental and public health monitoring due to their reliability in ensuring data accuracy and identifying abnormal patterns. Analysis in monitoring air pollution using statistical quality control has an objective to detect patterns and trends in particulate matter levels over time, track variations in air quality to ensure it remains within acceptable limit to identify potential sources of indoor air pollution. Based on the result of quality control analysis it shows that the implementation of Hotelling’s T2 control chart effectively demonstrated all variables indicating that the indoor air quality process is currently stable and under statistical control.
© The Authors, published by EDP Sciences, 2025
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