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Novhirtamely Kahar
Reny Wahyuning Astuti
Desviana Valencia

Abstract

Monitoring the development of early childhood is very important, especially for children aged 4-6 years, because at that time it was a golden age that required more attention in order to stimulate child development to the maximum. This research is expected to be able to help educators to determine the development that occurs in students. The method used in this research is the perceptron method. The perceptron method is a simple Artificial Neural Network (ANN) method that uses a training algorithm to classify linearly, while the input data that becomes the criteria for this research are Moral Religious Values (MRV), Physical Motoric (PM), Cognitive, Social Emotional, Language, and Art. While the output of the data that has been processed is in the form of selected development indicators, this indicator is divided into three, namely Very Good Development [1 1], Evolves According to Expectations [1 0], and Begins to Develop [0 1]. After analyzing the monitoring of early childhood development by applying the perceptron method and the processing it using the Matlab R2009a application, the research concluded that the perceptron method was proven to be able to determine the target output and the actual appropriate ouput reached 68%.

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