Analysis of the Naïve Bayes Method for Determining Social Assistance Eligibility Public - Siregar, Adinda Pratiwi; Irmayani, Deci; Sari, Mila Nirmala (Politeknik Ganesha Medan, 2023)
Economic needs are community needs that are used to meet daily needs. Therefore, economic needs are very important for the life of every society. There is a gap in the economic needs of the community, the government created a social assistance program which is assistance provided to the community in the form of cash or non-cash. The help is made for welfare society from inequality, especially economic inequality. So researchers will carry out a data classification of people who are eligible for social assistance. The classification will be carried out using the Naïve Bayes method. The Naïve Bayes method is a simple classification method for calculating the probability of a combination of certain data. The data to be used by researchers is community data as much as 62 community data. research done by using the Naïve Bayes method aims to classify community data that is feasible to forget social assistance. The first stage of this classification is the process of collecting community data and determining community data that will be used as a filtered sample cleaned, furthermore preprocessing data and then designing the Naïve Bayes Algorithm model. The results of data classification using the Naïve Bayes method show that the number of people who are eligible for social assistance is 14 community data and people who are not eligible for social assistance are 48 community data. These results can be a reference for determining the eligibility of the community to receive social assistance.