This article discusses the design of a hydroponic planting process monitoring system based on the internet of things. This device uses an ESP32 microcontroller board as the main controller. The parameters that were monitored and acquired were the conditions of the hydroponic growing media. Those parameters are; water pH, water temperature, water turbidity level, and ambient air temperature and humidity. The five parameters are measured by analog sensors integrated with the ESP32. These parameters affect the growth process and the quality of crop yields. This article also describes the calibration method for each sensor used for parameter measurement. Then the monitoring of these parameters is carried out by utilizing a real-time database, namely Google Firebase. This platform is very suitable for all IoT-based monitoring and control applications. Measurement result data is uploaded and saved to the real-time database. Then paired by Android-based applications. This application was created to be used by hydroponic farmers who use this device. Thus the results of monitoring can be used to optimize the process of growing hydroponic plants.

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Final Project as a Research is one of the main requirements for the graduation of undergraduate students from universities. Supervisory guidance is one way to find solution for student research problems. The final project guidance process involves multiple parts: campus administration, supervisors, and students. However, this process is often difficult to carry out properly because of the busyness of each individual, both lecturers and students. As a result, the process for carrying out the final project was hindered. Another thing that makes the completion of the thesis slow is the administrative service procedure to complete the final project which is too time consuming. This research aims to simplify and speed up the process of completing the student's final project. The prototype method is used to develop the final project management information system. This information system is designed using use case diagrams, rich picture diagrams, and entity relation diagrams. Tests were carried out using the black box method. The result of the research is a final project management information system which makes the student's final project completion process more efficient and effective. This information system facilitates administrative services and monitoring of the final project because it is performed systematically and can be controlled in real time.

<span lang="EN-US">The characteristics of the photovoltaic module are affected by the level of solar irradiation and the ambient temperature. These characteristics are depicted in a V-P curve. In the V-P curve, a line is drawn that shows the response of changes in output power to the level of solar irradiation and the response to changes in voltage to ambient temperature. Under partial shading conditions, photovoltaic (PV) modules experience non-uniform irradiation. This causes the V-P curve to have more than one maximum power point (MPP). The MPP with the highest value is called the global MPP, while the other MPP is the local MPP. The conventional MPP tracking technique cannot overcome this partial shading condition because it will be trapped in the local MPP. This article discusses the MPP tracking technique using an evolutionary algorithm (EA). The EAs analyzed in this article are genetic algorithm (GA), firefly algorithm (FA), and fruit fly optimization (FFO). The performance of MPP tracking is shown by comparing the value of the output power, accuracy, time, and tracking effectiveness. The performance analysis for the partial shading case was carried out on various populations and generations.</span>

Technology develops very fast marked by many innovations both from hardware and software. Multicore servers with a growing number of cores require efficient software. Kernel and Hardware used to handle various operational needs have some limitations. This limitation is due to the high level of complexity especially in handling as a server such as single socket discriptor, single IRQ and lack of pooling so that it requires some modifications. The Kernel Bypass is one of the methods to overcome the deficiencies of the kernel. Modifications on this server are a combination increase throughput and decrease server latency. Modifications at the driver level with hashing rx signal and multiple receives modification with multiple ip receivers, multiple thread receivers and multiple port listener used to increase throughput. Modifications using pooling principles at either the kernel level or the program level are used to decrease the latency. This combination of modifications makes the server more reliable with an average throughput increase of 250.44% and a decrease in latency 65.83%.