Abstract
The case of food insecurity is a problem in various regions all over the world, including in Aceh, one of the provinces in Indonesia. This study is purposed to identify the main indicators of food insecurity households in Aceh province in 2019-2020 by using classification tree. By knowing those indicators of households that suffering from food insecurity, the criteria of the food insecurity household can be known. Thus, the alleviation of food insecurity can be carried out precisely at the point of the problem of food insecurity. Identification of this food insecurity indicators can be done by extracting variable importance which can be done from machine learning method named classification tree. In this study, classification tree was implemented to Aceh National Socio-Economy Survey (Susenas) data in 2019-2020. The results of this study indicate that for data 2019, the optimum classification tree model was obtained at the level of minsplit 300 and Complexity Parameter (CP) is 0 with Area Under Curve (AUC) value is 0.697. While, for data 2020 the model was optimum at the level of minsplit 200 and CP is 0 with AUC value is 0.678. The top 5 variables importance for indicators of food insecurity in Aceh Province in 2019 are type of floor, cooking fuel, education of the head of the household, type of roof and floor area. Meanwhile, the top 5 variables importance for food insecurity indicators in Aceh Province in 2020 are cooking fuel, type of floor, education of the head of the household, floor area and number of savers. Variables that each year greatly contribute to Aceh's food insecurity in 2019 and 2020 are the type of floor, cooking fuel, education of the head of the household and floor area.
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