Implementation of Naive Bayesian Algorithm in Determining Recipients of Government Assistance Programs

Abstract

The government's efforts to improving public welfare with any programs, both central and local government. However, when this assistance program was initiated, sometimes not on targeted because of the difficulty to deciding the beneficiaries based on criteria that have been set. This research aimed to implement the naïve Bayesian algorithm in assessing the prospective beneficiaries of government programs by measuring the level of welfare based on the analysis criteria Naïve Bayesian algorithms. The method used is the Research and Development and using Boehm's spiral models of software development process. In determining of beneficiaries based on the criteria assessment that has been set of the government. By using Naive Bayesian algorithm, conditional probability of the evidence can be determined so that the weight of each class will be obtained which is used as a conclusion.