Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
Information and communication technology (ICT) development gives great impact on organization’s growth. Organization growth can cause change of structure in the organization, whether it is predictably happened or in a sudden. Education sector also can have impact on structural change, that’s why succession planning is important. Education Institution needs to prepare the successor in a systematic and continuous program. The way to improve the succession planning process is by implementing Machine Learning. This paper uses Systematic Literature Review to find the trends of implementation machine learning in education sector. The result shows three types of trends such as concept, research and thesis or dissertation product. These three trends also come with some factor to improve succession planning and the implementation of machine learning
In order to make the charging process of the battery easier, it needs to possess a design tool with suitable characteristics. One of the main characteristics of the battery is the State of Charge (SoC) or simply the battery capacity, which is calculated with the help of the initial voltage value. In this process, a 100Wp photovoltaic panel with 12V DC voltage is applied. The method used is experimental and simulation/modeling, and its purpose is to optimize the efficiency of the process of battery charging. Furthermore, the Arduino microcontroller, which functions are a detector during battery charging, was used to determine the current and voltage sensor controller circuit. The voltage and SoC on the battery are automatically monitored via the LCD and on the SD card using the data logger shield module. ICM algorithm used for modeling-simulation in this study is one of the MPPT type used by photovoltaic systems that work at optimum conditions, thereby producing maximum power. The results showed that the battery charging simulation increased by 0.05% every 30 minutes. Furthermore, the simulation validation using Matlab/Simulink is carried out with data following the prototype design, at an efficiency of 88.37%