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This paper attempts to develop statistical modeling for air-conditioning analysis in Jakarta, Indonesia, during an emergency state of community activity restrictions enforcement (Emergency CARE), using a variety of parameters such as PM10, PM2.5, SO2, CO, O3, and NO2 from five IoT-based air monitoring systems. The parameters mentioned above are critical for assessing the air quality conditions and concentration of air pollutants. Outdoor air pollution concentration variations before and after the Emergency CARE, which was held in Indonesia during the COVID-19 pandemic on July 3-21, 2021, were studied. An air quality monitoring system based on the IoT generates sensor data that is collected from a government-integrated data portal, and that can be analyzed statistically. There are two main types of ANOVA (Analysis of Variance): one-way (or unidirectional) and two-way, which are applied to the collected sensor data and hypotheses calculated using ANOVA. ANOVA one-way was found to be more effective for analyzing air quality condition data. During emergency CARE, the average concentrations of PM10, PM2.5, and O3 from the air quality monitoring system show values that have exceeded the standard Air Quality Index (AQI), while the concentrations of CO, NO2, and SO2 are still below the applicable AQI values. It stated that air pollution in Jakarta worsened during the implementation of Emergency CARE. [ABSTRACT FROM AUTHOR]