#TITLE_ALTERNATIVE#

• Main Author: REZKI PERMATASARI (NIM : 10211001), RISA
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/24026
• Institution: Institut Teknologi Bandung

<p align="justify">Groundwater is a natural resource that is vital to support human life everyday. Sufficient groundwater supplies are also needed in coastal areas. However, because of the huge population growth and increasing needs of water for domestic and agricultural, so many people and industries exploit them excessively, then causing a decrease in groundwater quality and quantity especially in vulnerable coastal areas affected by sea water intrusion. Therefore, to maintain the sustainability of the groundwater system in coastal regions needed a better understanding of the dynamics of ground water. One of them is the numerical groundwater modeling. In this case, the Artificial Neural Network is applied as a new approach for the management of groundwater in aquifers coastal areas. Data time series of land located in a coastal can be used to predict the concentration of chloride in groundwater. Artificial Neural Network Model in this study using MATLAB software. The method used is Backpropagation . The resulting excellent modeling depends on a high correlation between the values of the concentration of chloride observed and predicted. The correlation coefficient (r) between the values of the predictions and the observed output of the model ANN is 0.993. ANN model has been implemented as a new approach and an interesting tool to study and predict the salinity of the ground water without physically based hydrological parameters.<p align="justify">