Penentuan Kelayakan Masyarakat Miskin Penerima Bantuan Menggunakan Metode Naïve Bayes (Studi Kasus: Kabupaten Penajam Paser Utara)

Abstract

Contents Poverty is the inability to meet the necessities of life, such as food, clothing, and shelter. The poor have an average monthly per capita expenditure below the poverty line. The case of poverty in Indonesia is still unresolved; the Government continues to try to give the best to the entire community so that the problem of poverty can at least continue to decrease. One form of government concern for the poor is the assistance program provided to the poor. This study will classify based on data from the North Penajam Paser (PPU) community obtained from the results of the National Socio-Economic Survey (Susenas) to know how the Naïve Bayes method is in determining the eligibility of the poor recipients of assistance. Based on the research that has been carried out, a system for determining the poor recipients of assistance is produced, where the test results get the highest accuracy in the third scenario, namely 60% or 328 training data and 40% or 218 test data, where the accuracy obtained is 77.98%.

Keywords

• Classification
• Poor Society
• Laplace Correction
• Data Mining
• Naïve Bayes