The model for Stroke risk behavior assessment model in the elderly Damnoen Saduak District Ratchaburi with data mining techniques

Abstract

This research has reasons for the study and development of the communication model, the management regulation that causes the systemic disease without knowing the patient group information used in the research of the disease patients in the provincial Takhae district, selected from the provinces. The 610 sets contain Part 1, Personal Data and Part 2, Disease Safety Stream. Elements used in the development of Weka, Microsoft Excel Office 16, are used to collect Google Forms data. Practice and program Adobe Photoshop 2019 is used to design the background of the user model.This research uses automated tree data analysis techniques, fire, 5 nearby algorithms, J48, LMT, RandomTree, REPTree, and RandomForest to obtain the values that The most appropriate and accurate model was developed as a survey of the relationship to musculoskeletal disease by the decision tree technique. The results showed that the LMT algorithm had a data validity and skill that used 10x cross validation to divide the data with a 97.7% validity value with a good thermal value of 97.7. % Has 97.7% aesthetics, 97.7% of the favor and 97.7% of the prosperity, which includes Guitree J48, RandomForest, RandomTree, and RERTree.