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
Penulis: Mad Yandi, Muhammad
Nizam, Ubaidillah
Kode Jurnal: jptmesindd140494
