Finding a solution to improve the quality of SMP in Sawahlunto City based on ANBK using ANN with Backpropagation Algorithm. Adaptation to ANBK needs to be done quickly so that the School Quality Score becomes good from time to time and the main goal of the education unit, namely the development of student competence and character, is achieved. This has only been simulated in 2019 and in 2021 this is the first stage of testing. The National Computer-Based Assessment for SMP level is a quality assessment program for all SMP level schools. From the test results obtained the level of accuracy of pattern recognition in the backpropagation method is 99.17% with a learning rate variation of 0.1 and epoch 100, the learning vector quantization method has an accuracy rate of 96.67% with a variation of learning rate 1 and epoch 20 From the results of the comparison the Backpropagation method is superior in terms of accuracy so that it becomes the right method to use in exploring the potential of new students at STMIK PalComTech. From 120 data tested using variations in test data and training data which are then processed using variations in the learning rate parameters and epochs. Comparisons in this study involve four input variables used which consist of four basic subjects of informatics engineering and information systems (math, basic programming, computer networks and management bases) which then make informatics techniques and information systems as outputs, to get the accuracy level high in this study, the researchers used several variations of parameters which eventually produced the best accuracy of the two methods. The Research aimst to compare backpropagation and Learning Vector Quantization (LVQ) methods in exploring the potential of new students at STMIK PalComTech.
0 kommentar(er)
