Comparing Artificial Neural Network and Decision Tree Algorithm to Predict Tides at Tanjung Priok Port

作     者：Arif Musadi Christian Carlos Tertius Jonas Steven Hanis Amalia Saputri Kristien Margi Suryaningrum 

作者机构：Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 

出 版 物：《Procedia Computer Science》 

年 卷 期：2023年第227卷

页      面：406-414页

主　　题：Tidal prediction Artificial Neural networks Decision tree 

摘      要：Tanjung Priok Port is an international port in Indonesia located in Tanjung Priok, North Jakarta. For all activities carried out at Tanjung Priok Port to run smoothly, this research was made which aims to predict the height of tides using the Artificial Neural Network (ANN) and Decision Tree methods with a quantitative approach. Artificial Neural Network (ANN) is a technique inspired by the way the biological nervous system works, namely in brain cells in processing information received by humans. while Decision Tree is also known as a decision tree which is an algorithm for building a decision hierarchy structure. The process of making a Decision Tree starts from the Root Node to the Leaf Node which is done recursively. This research was conducted to predict the height of tides in January 2018 - June 2018. By using both methods that have been computed, the ANN method produces a smaller MSE value than the Decision Tree method. The ANN method produces an MSE value of 0.003727983. While the Decision Tree method produces an MSE value of 0.009870259. If the dataset used has larger amount of data and the architecture of each algorithm is more complex, then the calculation results obtained will be more accurate.