Penerapan Algoritma Naive Bayes Untuk Klasifikasi Penerima Bantuan Surat Keterangan Tidak Mampu


Rukun Warga 002 Kelurahan Meruya Selatan runs a government program, namely assistance for recipients of a certificate of being unable to meet the community's needs and aims to improve the community's welfare. Rukun Warga 002 has community services, namely death certificate services, making ID cards, disability certificates (SKTM), birth certificates, and many more. In carrying out assistance, most of the community complained that they did not get help, while some people were considered capable of getting this assistance. The researcher carried out data processing techniques with observation, literature study, and questionnaires based on this background. In contrast, the data processing used data mining to determine the incapable recipient's proper or inappropriate status, namely by using the Naïve Bayes algorithm while using the Rapidminer application, aiming to test the dataset's accuracy. In the dataset of incapacitated recipients used in this study, there are 35 records with eight attributes: name, occupation, age, status, income, vehicle, ownership, and roof of the building, while this research aims to predict and produce level values. Accuracy in providing assistance letters of incapacity to the people of 002 sub-district of Meruya Selatan using the naïve Bayes method. The trial results show that the system accuracy rate is 62.86%, a recall of 78.57%, and 52.38% precision.