CD Skripsi
Penerapan Algoritma Cart (Classification And Regression Tree) Pada Klasifikasi Pengangguran Terbuka Di Provinsi Riau
CART (Classification and Regression Trees) is a classification method developed for determining decision trees in analyzing the relationship between dependent variables and independent variables. This final project discusses the application of CART to the classification of open unemployment in Riau Province in 2023. Data was obtained from the National Employment Survey (Sakernas) from Badan Pusat Statistic of Riau Province with the independent variables used being gender, education level, age, household status, work training experience, marital status, and residence classification. The results showed that the class of open unemployment data is not balanced so it must be balanced first using SMOTE. The balanced data produces a decision tree which contains information that the independent variables that have a significant influence on unemployment status are gender, household status, marital status, and residence classification
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