The design and development of the next-generation power-efficient CIGS solar cells are at the research forefront due to their potential applications in renewable energy. Due to rich fundamental properties such as chemical and physical structures of the CIGS layer, cell scaffolding, and its promising applications like low cost, easy integration, and high efficiency, the CIGS-based solar cell systems are of considerable interest and received tremendous attention. In this article, we review the CIGS solar cells from the point of view of structural engineering. We explain the intrinsic parts of crystalline, optical, and electronic structures of the CIGS absorber layer up to the extrinsic part of the cell multilayer structure. For intrinsic structure, we primarily review the modification of the crystallinity or chemical composition of the CIGS and the effects that these modifications have on the physical properties such as the adjustment of the bandgap grading, effect of impurity or doping, selenization, oxidation processes, and the surface morphology and structure orientation. For extrinsic structure, the effect of substrates, electrical back contact, windows, n-buffer, grid, and antireflection layers will be discussed further, as well as the possibility of their tandem use with other solar cell thin films.

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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.

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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