Penerapan JST Backpropagation Untuk Memprediksi Data Penerimaan Mahasiswa Baru Pada Universitas Simalungun - Choiril Ichsan Damanik; Dedy Haratama; Heru Satria Tambunan (Bulletin of Computer Science Research, 2021)
The growing era of globalization makes people continue their education to a higher level. The greater the interest of prospective students, each year the number of prospective students will increase. The increase has made the university can manage and know the estimated number of prospective students each year. So we need a method to help the university so that the number of prospective students can be predicted quickly and accurately. In predicting the data of prospective new students at Simalungun University the backpropagation method is used, this study is expected to predict the number of new students with smaller error results. The data used was obtained from the Simalungun university administration from 2015 to 2018. Backpropagation is one method that is often used in solving complex problems. Its application researchers conducted the test using the Matlab application. This study uses 5 architectural models: 2-5-1, 2-10-1.2-15-1, 2-25-1, 2-3-5-1, the best accuracy is obtained from architectural models 2-3-5-1 with values accuracy of 86%, epoch 8406 iteration, and MSE namely 0, 0778011336