KLASIFIKASI KELAYAKAN PENERIMA BANTUAN SEMBAKO MENGGUNAKAN METODE DECISION TREE

Abstract

Poverty is one of the fundamental problems that is of concern to governments in all countries.  An important aspect to support poverty alleviation strategies is the availability of accurate and targeted poverty data. Staple food is the nine basic needs of Indonesian people, including food or drinks used in daily life. On this basis, the government often organizes basic food assistance programs for those in need. classification is one of the most commonly used prediction techniques to predict new labels or categories based on experience gained from known data. The main purpose of classification is to understand patterns or relationships between input and output variables, so that you can take appropriate decisions or actions based on the available information. Based on the results of the analysis and implementation of the Decision Tree Algorithm for classification of eligibility for basic food aid recipients in the Teluk Agung Village area, Indramayu District, Indramayu Regency, it can be concluded that the model developed has a very high level of accuracy, namely 94.83%. This model has proven effective in classifying various categories that are worthy of receiving assistance, starting from class 1, 2, 3 and not worthy of receiving assistance. The factors used in this model, such as monthly income, have been processed well through stages in the Knowledge Discovery in Databases (KDD) framework, resulting in a reliable classification. With high accuracy and performance, it is hoped that this model can be implemented practically to support decision making in mitigating the risk of non-delivery of basic food aid in the Teluk Agung Village area, Indramayu District, Indramayu Regency.