Identify Level of Welfare Population Based on Income Levels Using Decision Tree Method

Yunita Ardilla, Yunita and Wilda Imama Sabilla, Wilda and SARAH ASTITI, SAS (2021) Identify Level of Welfare Population Based on Income Levels Using Decision Tree Method. Identify Level of Welfare Population Based on Income Levels Using Decision Tree Method, 13 (2). pp. 15-21. ISSN 2622609x

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Abstract

Identification of population welfare influenced by several factors. This identification is useful to assist the government in classifying the level of welfare population which is useful for providing subsidies to be targeted. Therefore this study aims to determine the level of welfare population based on the level of income per capita using decision tree method. The selection of the best model is based on the calculation value of accuracy, precision, and recall with k-fold cross validation method. Based on experiments that have been done, it can be concluded that the decision tree model produced has good performance with a tree shape model has 622 leaves with tree size 705 of nodes, the model has an accuracy of 86,97%, precision 0.897 and recall 0.917.

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