Comparison of C4.5 method based optimization algorithm to determine eligibility of beneficiaries of direct community assistance (Case study: Kelurahan Cicurug)

The Provisional Direct Assistance to the Community (BLSM) is a program of providing cash assistance to Target Household (RTS), which is a Poor Household (RTM), which is stipulated by the government in addition to the fuel price hike. This study is based on the case that the distribution of BLSM is not the right target and subjective interests. This BLSM is for the poor who can not afford economically, but still many rich people who also receive it specially in Kelurahan Cicurug. Decision Support System (DSS) to determine the community direct assistance beneficiaries in Kelurahan Cicurug with C4.5 method is one of the above theme solutions. Data mining method is chosen because it can generate models and criteria that easily interpreted by the classification of Data Training and Data Testing with Genetic Algorithm (GA) algorithm so that it can be a better form of the method. Damp concluded with method C4.5 with accreditation value 92,92% from training data and 84,21% from data testing, Method C4.5 based on PSO have value 97,35% from training data and 98,68% from data testing, and GA-based C4.5 method has accreditation data of 94,69% from training data and 90,67% from data testing. Can be concluded C4.5 based on PSO is very good.