This study aims to determine the effectiveness of the assessment of mathematics learning during the COVID-19 pandemic at SDK Ndona 2, Ndona District, Ende Regency. This type of research is qualitative research with data collection techniques in this study carried out by means of observation, interviews, and documentation. After the data was collected, the data were analyzed qualitatively. The results of this study indicate that the effectiveness of assessing mathematics learning during the COVID-19 pandemic only focuses on the cognitive assessment of students, therefore teachers have other techniques in carrying out mathematics learning assessments so that they can provide a real picture of students' abilities. The conclusion from the results of this study is that during this pandemic the assessment of mathematics learning has been effective. This is because the assignment given by the teacher is not done by students but is served by someone else (parents, siblings)
This research was conducted to improve the mathematics learning outcomes of elementary school students by using the Problem Based Learning model. The method used in this research is Classroom Action Research. Class IV SDK Ndona 2 students totalling 16 students are the subjects in this study. The results before the action were taken, namely, in the pre-cycle, only 6 students or 37.5% completed, in the first cycle increased to 10 students or 62.5% who completed learning mathematics and in the second cycle increased again to 14 students who completed learning mathematics or 87, 5%. This study is said to be successful because it achieves performance indicators, namely more than 80% of all students with a minimum standard of more than 70. Based on the results of the study, it can be concluded that learning with the Problem Based Learning model can improve learning outcomes in mathematics students.
The current revival and intensified research on machine learning take place while an intensified focus of companies on digitalization developed. The willingness and acceptance to apply innovative methods in industry has grown. Gray box or hybrid process modeling represents the combination of rigorous (white box) process modeling with machine learning (black box) models. In recent applications, the presented method has been utilized for process models at Evonik. This article describes the workflow for developing hybrid process models and is meant to share the experiences made during the process.
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