KLASIFIKASI PENERIMA BANTUAN SOSIAL DENGAN ALGORITMA RANDOM FOREST UNTUK PENANGANAN COVID 19

Abstract

The Covid 19 outbreak has an impact on the community so that there are family heads who cannot work in general. The policy pursued by the central government is to provide assistance to workers who have salaries below 5 million and other programs. The obstacles faced to the community are not exactly recipients of assistance in accordance with the criteria set by the government. The criteria set by the government are workers who have salaries below 5 million. The purpose of the study can model the recipients of social assistance that is on target, so that the assistance can be useful in the time of the Covid 19 pandemic. This method of approaching research uses knowladge data discovery with the first stage of data obtained by social services in 2020 the second stage of data classification based on the riteri that has been established. The third stage of preprocessing is used to clean up noise data, stage four of the random forest model by using rapid miner tool version 9.9. Stage six discussion of the results of the model produced from random forest. The results expected in the study get a good model so that it becomes a recommendation in determining the recipients of sosial assistance