TY  - JOUR
T1  - Maritime Weather Predictor Design Based Neural Network and
ANFIS to an Increase in Accuracy in the Java Sea
AU - Dhanistha, Wimala L. AU - Islamiyah, Mufidatul AU - Wardhana, Wisnu 
JO  - Journal of Engineering and Applied Sciences
VL  - 15
IS  - 7
SP  - 1724
EP  - 1727
PY  - 2020
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2020.1724.1727
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2020.1724.1727
KW  - Wave height
KW  -wind speed
KW  -neural network
KW  -ANFIS
KW  -algorithm
AB  - Sea transportation is a mainstay transportation in Indonesia, it is because Indonesia consists of
thousands of islands, so that, to connect between islands, sea transportation is needed. Waves are very closely
related to the sea, waves that are negative that is waves that can endanger shipping. One of the factors causing
sea accidents is natural disasters, namely high waves. To minimize accidents due to high waves, wave
predictions can be made in the hours to come using the neural network algorithm. Neural network was chosen
because of its advantages in processing system input-output data even though the system is nonlinear. The
advantage is that the neural network is chosen as a wave height predictor algorithm. ANFIS is an algorithm for
the development of a combination of neural networks and fuzzy artificial intelligence. The ability of ANFIS
to predict wave heights is no less good with neural networks, it is because ANFIS is a combination of neural
network and fuzzy. It is hoped that by doing this research it can compare which algorithm is better in predicting
wave heights.
ER  -