This paper implements artificial neuralnetworkin predictingthe understanding level ofstudent'scourse. By implementing artificial neural network based on backpropagation algorithm, an institution can give a fair decision in prediction level of students' understanding of particular course / subject. This method was chosen because it is able to determine the level of students' understanding of the subject based on input from questionnaires given. The study was conducted into two ways, namely training and testing. Data will be divided into two parts, the first data for the training process and the second reading data of the testing process. The training process aims to identify or search for goals that are expected to use a lot of patterns. Thus, it will be able to produce the best pattern to train the data. After reaching the goal of training which is based on the best pattern, then it will be tested with new data to seeat the accuracy of the target data using Matlab 6.1 software. The results show that it can accelerate the process of prediction of students' understanding. By using architectural models 6-50-1 as the best model, some architectural models are tested and the result of prediction is reach to 87.75%. In other word, this model is good enough to make predictions on the level of students' understanding of the subject.
The insistence on improving the quality of education always emerges, particularly from the government. Almost in every opportunity and meetings, the central government always urges all parties, particularly the providers of education, to improve the quality of education. Simultaneously, public also pleads the central government to act quickly in this matter. There are strong behavior and response from each party showing that quality improvement is necessary and urgent. In reality, even though this issue has been encouraged for many years, the quality of education is still poor anywhere. This study aims to find out the reason and its solution. Integrated Quality Management (IQM) is one of the alternatives to overcome this issue. The IQM encourages "continuous improvement" and the mindset of continuous improvement.
This study elaborates on the quality of family education in fulfilling childcare rights. The results of the study found that family resilience is a factor that influences the quality of childcare. The resilience of the family in this study was measured by three indicators, namely education and parental knowledge regarding care, parental involvement in child care, availability and adequacy of time to communicate with children. This study found that the quality of education and knowledge of parents related to childcare is still weak, with only 27.9% of fathers and 36.9% of mothers seeking information on caring for children before marriage and only 38.9% of fathers and 56.2% of mothers seek information on caring for children after marriage. Parental involvement directly in the process of parenting is also still low, only 26.2% of Fathers and 25.8% of Mothers stated that the process of parenting was not helped and was not transferred to others. The quantity and quality of communication time of parents with children is also still very minimal, in quantity the average time to communicate with children is only 1 hour per day which is 47.1% for Father and 40.6% for mother. The weak education of parents in the process of fulfilling child care rights has the potential to lead to not maximally developing children in the family.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.