Abstract

This paper focuses on the proving of the associated factor for the caries status among preschool children in Bachok, Kelantan. This research paper is mainly focused on the potential factor that most contributing to Early Childhood Caries (ECC). There are two methodologies approaches in this research paper which is Decision Tree Analysis (DTA) and Multi-Layer Perceptron (MLP). The results from both analyses can be used to assist the public and also the stakeholder to control the prevalence of ECC in the future. Results from both analyses are also very useful to redesign the health treatment among pre-school children, to educate the parents, teachers, and to improve the service which offered by the ministry of health from time to time by focusing the most influential factors which lead to ECC in the local community. According to the result of Decision Tree Analysis, the most factor that leads to caries status among preschool children are father’s occupation, household income, children’s weight and the type of water used in their house. While using Multi-Layer Perceptron (MLP) neural networks modeling, the factor can be summarized as household income factor, children’s weight, father occupation and also the type of water used in their house. From the results of the Decision Tree and Multi-Layer Perceptron (MLP) reveals that the top three factors lead to ECC were household income factor, children’s weight, father’s occupation. This information will provide a very useful information to forecast ECC status among preschool children.

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