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Analysis of Factors Affecting Developmental Delay by Age in Early Childhood with Data Mining Techniques |
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| รหัสดีโอไอ | |
| Creator | Ittipol Duangkaew |
| Title | Analysis of Factors Affecting Developmental Delay by Age in Early Childhood with Data Mining Techniques |
| Contributor | Saiyan Saiyod |
| Publisher | Faculty of Information Science and Technology, Mahanakorn University of Technology |
| Publication Year | 2562 |
| Journal Title | Journal of Information Science and Technology |
| Journal Vol. | 9 |
| Journal No. | 2 |
| Page no. | 44-55 |
| Keyword | Late Development, Data Mining Technique, Decision tree, k-Nearest Neighbor, Naive Bayes |
| URL Website | https://tci-thaijo.org/index.php/JIST |
| Website title | Journal of Information Science and Technology |
| ISSN | 2651-1053 |
| Abstract | The purpose of this research was to analyze factors affecting developmental delay in each age group of 4 preschool children, namely 9, 18, 30 and 42 months, which were evaluated by the surveillance and promotion manual. Early Childhood Development (DSPM). By requesting information support from Khon Kaen Provincial Public Health Office. Data is from October 2016 to September 2017. The researchers studied factors affecting early development in early childhood from previous medical and public health research. Get 24 factors. The model was constructed using data mining techniques such as Decision Tree technique, K-Nearest Neighbors technique and Na?ve Bayes technique. Testing was performed using the K-fold Cross-validation method. validation, the results showed that the Decision Tree technique is the most accurate in predicting all 4 developmental stages which are 9 months of age at 87.50%, 18 months of age at 84.70%, 30 months of age at 83.60 and 42 months of age at 82.90%. |
