This study aims to determine the effect of the principal's digital leadership on vocational teachers' reflection practice, mediated by the variables of trust, self-efficacy, and work involvement. This study uses path analysis with modeling using SEM (AMOS). The sample of this research is 637 (N=340 females and N=297 males) vocational high school teachers in Malang Raya, East Java, Indonesia. The researchers have used a purposive random sampling technique to meet the objectives of this research. The investigators have used a 86 item questionnaire to collect data on the studied variables. Based on the fit model's estimation, there is a direct and indirect relationship between the five variables used. The variables of trust, self-efficacy, and job involvement contributed significantly to intervening variables. It can be concluded that the moderating variable strengthens the framework for the relationship between digital leadership and teacher reflective practices. The new relationship formed is a direct contribution of digital leadership to work engagement with a magnitude of 0.120 and a direct relationship made between digital leadership and the reflective practice of teachers of 0.168. This relationship has a positive impact on teacher actions. These results indicate that the teacher appreciates the Principal's leadership, who both supports facilitates the learning process in using technology in the learning process. Moreover, teachers feel motivated and excited to reflect on their learning because of the leaders who have digital characters. The teacher considered leaders with digital personalities more open and tended to free them to manage the class.

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Coronavirus disease 19 (COVID19) is a disease caused by the new coronavirus called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease has infected almost the entire world with a total of 47.5 million sufferers and a death toll of 1.2 million people so that WHO categorizes it as a global pandemic. The COVID19 case in Indonesia still shows an increasing trend even though various prevention efforts have been made. Proven efforts to reduce the spread of COVID19 include limiting physical interactions between humans or physical distance, maintaining the cleanliness of hands and limbs by washing with soap, and limiting outdoor activities by staying at home. Several government and private agencies have required employees to report their health conditions via web pages. Real-time and accurate mobile applications can help prevent the spread of COVID19. This research will develop a real-time monitoring and command system using mobile applications and cloud computing technology. The application will collect GPS-based location data, the number of people in the vicinity identified via Bluetooth, and the user's body condition in the form of temperature and oxygen levels in the blood. User data is stored and processed in a real time database in cloud computing which can be accessed through an application on the user's smartphone. The database also stores data on Covid19 sufferers and where they live. The application provides alerts when in a crowd and notifies the status of the region the user is in. Advice is given by the app when the recording of the body condition points to the early symptoms of COVID19.

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The original queen honey bee migration (QHBM) was developed for independent action on solving efficient mobile routing in WSN. In this paper, we enhanced the original QHBM using Binary testing injection on the cooperative node's selection on IoT system. We also added a new cost function for making nodes' coalition, implementing the threshold value for modified QHBM (mQHBM for short), and demonstrating the mQHBM-CMIMO in fair comparison with another previous algorithms. Our research portrayed that mQHBM can perform better than its competitors such as Fuzzy-BT, Neuro Fuzzy and PSO in terms of network lifetime and the end to end delay.