A combination of backpropagation neural network on fuzzy inference system approach in Indonesia scholarship selection process: Case study: “Bidik misi” scholarship selection

“Bidik Misi” (BM) is a scholarship from the Government of Indonesia with two criteria: economic need and academic performance. Main candidate targets are those from low economic families. Due to the large number of potential recipients who desire to continue their study to the university level despite the limited quota, difficulties occur in selecting candidates. This research aims to provide a new selection model by combining Back-Propagation Neural Network (BPNN) on Fuzzy Inferences System (FIS) for the BM scholarship selection process where BPNN is used as classifier to eliminate non-recommended candidates to reduce the system's workload before applying FIS as candidate selector. By considering spearman's correlation coefficients of the input parameters in creating fuzzy framework for BS scholarship selection, the accuracy of the system is superior to previous works. In the future will be useful in making an automated selection system in order to help the committee by reducing their manual labor.