Implementation of LSTM Method on Tidal Prediction in Semarang Region - Ambadar, Panreshma Rizkha; Novitasari, Dian C Rini; Farida, Yuniar; Hafiyusholeh, Moh; Setiawan, Fajar (Journal of Applied Informatics and Computing, 2025)
Semarang is the capital of the Central Java province, located in the north and directly adjacent to the Java Sea. Having an almost flat land condition with a slope of about 0-2%, Semarang City has the opportunity to experience tidal flooding. The occurrence of tides does not have a fixed period. So, it is necessary to predict the height of the tide and the ebb of the seawater. Thus, this research aims to predict tides in the Semarang area using the LSTM method. The data used is tidal data in Semarang waters from 2020 to 2024. The advantage of the LSTM method is its ability to effectively remember time series data or data with long-term dependence. LSTM can store past information using special cells contained in its structure. This research on tidal prediction using the LSTM method with 70% training data trial batch size 32 and epoch 200 obtained the smallest error value, namely the MAE value of 0.0388 and MAPE of 0.0313 which is the best LSTM result.