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This study aims to analyze the formation of deliberative democracy in political education within the National Democratic Party (NasDem) of DKI Jakarta. By employing the concept of deliberative democracy, we argue that the NasDem Party of DKI Jakarta applies a democratic intersubjective dialogue process in decision-making regarding internal party political education. Although research on political education in general within political parties in Indonesia has been widely discussed, this paper complements previous studies by considering democratic inter-agent interactions and analyzing the discourse of deliberative democracy in political education within the NasDem Party of DKI Jakarta. Through qualitative exploration with descriptive case studies of two informants, field findings indicate that interactions in political education within the NasDem Party of DKI Jakarta are democratic in line with the party's ideological foundation, which guarantees internal democracy and promotes public democratization. Additionally, political parties also engage in empowering active members through participatory procedures and facilitate deliberative decisions in legitimizing internal political education from the village level to the provincial level. These findings contribute to an intra-party deliberative democracy model aimed at empowering members and offering a political public forum that prioritizes deliberation in influencing decisions. [ABSTRACT FROM AUTHOR]

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]