Analisis Perbandingan Algoritma C4.5 Dan Naive Bayes Dalam Menilai Kelayakan Bantuan Program Keluarga Harapan

Social assistance is a form of government intervention that aims to help people who are in less fortunate economic conditions. This form of assistance can be in the form of cash assistance, food assistance, or health service assistance. Social assistance programs are often aimed at reducing poverty, addressing hunger, and improving the overall well-being of society. Program Keluarga Harapan (PKH) is a form of conditional social assistance launched by the government of Indonesia to help poor and vulnerable families. The Program aims to improve the quality of life of poor families through the provision of cash assistance accompanied by obligations for recipients to meet certain requirements, such as ensuring their children attend school and regular health checks at health facilities. With the PKH, it is expected to improve the access of poor families to education and health services, which in turn will improve the quality of Indonesian human resources. Thus, the author can evaluate the advantages and disadvantages of each method in the context of the data used. In addition, this comparative analysis also aims to provide more informative recommendations for policy makers. If one of the methods proves to be superior, then it can be adopted to improve the selection process for CCT recipients in the future. However, if both methods have balanced performance, a combination or integration of the two can be the optimal solution. By comparing the performance of Naive Bayes and the C4.5 algorithm, the study not only focused on identifying the right recipients, but also provided valuable insights in choosing the most effective analytical tool for the purpose.