Forecasting is apply because of complexity and uncertainty faced by high-dimensional data available in the fields of bioinformatics, chemometrics, banking and other applications. A process for systematically estimating what is most likely to happen in the future based on past and present data requires an appropriate forecasting model, so that the difference between what happens and the estimated results can be minimized. To get the right method, a measuring technique is needed to detect the accuracy of forecasting value. In this paper we discuss the technique of measuring forecasting accuracy with Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) using the Random K-Nearest Neighbor (RKNN) method. With the two measuring technique for the horizontal modeling above, the smallest MSE and MAPE values are chosen (the smallest error value). From the results of the analysis of the calculation of forecasting accuracy measurement values during training with RKNN, the MAPE accuracy value is 0.728427% and MSE is 0.545751, while the smallest accuracy value is achieved using MSE which is 0.545751.
The seating chart created in the classroom is one way for teachers in the class to remember students’ names one by one and by remembering students’ names, it means there is a teacher concern [4][5]. In addition it becomes the basis for developing sense of community in classroom [4][5]. In this paper discusses combination of computers and wireless sensors to make information seating chart system digitally in classroom. The system will be updated automatically if a student sits down a seat. Sensor section was placed to the student’s seat and server section was used to display seating chart to teacher. It was working as planned. This was evidenced by the stored data (the seat’s number and RFID code of the student’s card) into the MySQL database on the server. The future work will create a Graphical User Interface to be installed the server, so that teacher will use it easy.
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