{"title":"基于C4.5算法的儿童发育迟缓分类","authors":"Muhajir Yunus, M. K. Biddinika, Abdul Fadlil","doi":"10.15575/join.v8i1.1062","DOIUrl":null,"url":null,"abstract":"Stunting is a disease caused by malnutrition in children, which results in slow growth. Generally, stunting is characterized by a lack of weight and height in young children. This study aims to classify stunting in children aged 0-60 months using the Decision Tree C4.5 method based on z-score calculations with a sample size of 224 records, consisting of 4 attributes and 1 label, namely Gender, Age, Weight, Height, and Nutritional Status. The results of the study obtained a C4.5 decision tree where the Age variable influenced the classification of stunting with the highest Gain Ratio of 0.185016337. Meanwhile, the evaluation of the model using the Confusion matrix resulted in the highest accuracy of 61.82% and AUC of 0.584.","PeriodicalId":32019,"journal":{"name":"JOIN Jurnal Online Informatika","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Classification of Stunting in Children Using the C4.5 Algorithm\",\"authors\":\"Muhajir Yunus, M. K. Biddinika, Abdul Fadlil\",\"doi\":\"10.15575/join.v8i1.1062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stunting is a disease caused by malnutrition in children, which results in slow growth. Generally, stunting is characterized by a lack of weight and height in young children. This study aims to classify stunting in children aged 0-60 months using the Decision Tree C4.5 method based on z-score calculations with a sample size of 224 records, consisting of 4 attributes and 1 label, namely Gender, Age, Weight, Height, and Nutritional Status. The results of the study obtained a C4.5 decision tree where the Age variable influenced the classification of stunting with the highest Gain Ratio of 0.185016337. Meanwhile, the evaluation of the model using the Confusion matrix resulted in the highest accuracy of 61.82% and AUC of 0.584.\",\"PeriodicalId\":32019,\"journal\":{\"name\":\"JOIN Jurnal Online Informatika\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JOIN Jurnal Online Informatika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15575/join.v8i1.1062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOIN Jurnal Online Informatika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15575/join.v8i1.1062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification of Stunting in Children Using the C4.5 Algorithm
Stunting is a disease caused by malnutrition in children, which results in slow growth. Generally, stunting is characterized by a lack of weight and height in young children. This study aims to classify stunting in children aged 0-60 months using the Decision Tree C4.5 method based on z-score calculations with a sample size of 224 records, consisting of 4 attributes and 1 label, namely Gender, Age, Weight, Height, and Nutritional Status. The results of the study obtained a C4.5 decision tree where the Age variable influenced the classification of stunting with the highest Gain Ratio of 0.185016337. Meanwhile, the evaluation of the model using the Confusion matrix resulted in the highest accuracy of 61.82% and AUC of 0.584.