Klasifikasi Kekuatan Struktur Beton Menggunakan Convolutional Neural Networks

Abstract

Concrete is one of the most important elements in building a building construction. Concrete is widely used because it has advantages compared to other construction materials. In addition, the development of concrete construction has increased rapidly compared to other constructions, especially in the way of making concrete to the technology and use of materials used. In its development, materials will increase so that experiments in the laboratory make the costs swell. Therefore, a research is proposed which is intended to help researchers as well as to provide a comparison of the use of the model used.

The method used to classify will use the CNN model by producing output that will display the class categories on the variables that have been inputted. The test results on training data resulted in an accuracy of 86.04% and testing on test or validation data was 82.14% on the Adam optimizer and 83.25% on training data and 80.35% on test or validation data on RMSprop. After determining the model to be used, it is continued with the use of K-fold validation.