Classification of Research Proposal Funding Using Naïve Bayes and Decision Tree Methods

In the selection process, determining a university funding research proposal at Tunas Pembangunan University (UTP) still has not fully used information technology to support related institutions, namely UTP Institute for Research and Community Service (LPPM). So that it obstacles requires long time. we need system is able help these institutions make easier determine recipients of proposals are worthy funding. The application data mining series processes explore added value in form knowledge been known manually from set. This parameters, namely, NIDN, academic degree, track record, proposed budget plan (RAB), targeted outcomes. certainly less efficient because if lecturer proposes proposal, he must wait time find out whether results accepted, accepted with improvements, or not. addition, assessment process relevant methods so objective obtained by proposing final feasibility recommendation contained decision letter classification criteria accordance needs necessary. proposal. By applying algorithm Naïve Bayes Method Decision Tree, hoped can simplify accelerate LPPM eligible University.