KLASIFIKASI MASYARAKAT MISKIN DI KELURAHAN MARGAJAYA RW 06 MENGGUNAKAN ALGORITMA NAÏVE BAYES

Abstract

Poverty is an urgent social problem, Margajaya Village is one of the areas in West Bogor District with a significant population, and there are still many residents who feel that assistance from the government is not on target. This research aims to classify poor people in Margajaya RW 06 Village using the Naïve Bayes algorithm. The Naïve Bayes algorithm was chosen because of its superiority in computing speed, algorithm simplicity, and good level of accuracy. It is hoped that this research can help the government classify poor people more accurately and efficiently, so that aid distribution can be right on target and reduce social injustice. This research tests the Naïve Bayes algorithm in classifying poor people and looks at the accuracy value of data from poor people in Margajaya RW 06 Village. The results of the research show that using the Naïve Bayes method can provide good and accurate classification results. By implementing this method, it is hoped that harmony can be created in society and equal distribution of social welfare in the Margajaya RW 06 subdistrict area. From the evaluation results using the Confusion Matrix, the accuracy obtained for 135 training data with 134 test data and six attributes used resulted in an accuracy of 92. 54%, recall 91.53%, and precision 100%.