Prediksi Efisiensi Mesin dengan Kecerdasan Buatan

Abstract

The aim of this research is to determine the engine eficiency by using artificial intelligence. The artificial intelligence used for this study is Artificial Neural Network and Support Vector Machine. In ANN, algorithm that is used is Radial Basis Function and Bacpropogation whereas in SVM algorithm that used is Radial Basis Function kernel. Data used for the study is a test result from Prius 1.5L engine with 144 number of data which 120 of them is used as training and 24 of them is used for testing. The parameter that were used are torque, speed(RPM) and efficiency. The analysis show that the result of the testing approached the actual calculation wtih correlation 0.9664(RBF), 0.9979(Backpropogation) and 0.9836(RBF kernel). Computational time for each algorithm are 9.354s(RBF), 263.44s(Backpropogation) and 2.1994(RBF kernel).

Keywords : Artificial Intelligence, Artificial Neural Network, Support Vector Machine, Efficiency Prediction, Backpropogation, Radial Basis Function