Stevedoring Time Estimation on Smart Port Services Using K-NN Algorithm
- Resource Type
- Conference
- Authors
- Ramadhani, Dimas Khrisna; Novian, Fahmi; Puspitorini, Okkie; Siswandari, Nur Adi; Mahmudah, Haniah; Wijayanti, Ari
- Source
- 2020 6th International Conference on Science in Information Technology (ICSITech) Science in Information Technology (ICSITech), 2020 6th International Conference on. :115-120 Oct, 2020
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Liquids
Loading
Estimation
Prediction algorithms
Marine vehicles
Information technology
Testing
Classification
Long Range
Estimation time
KNN
- Language
Smart Port Service serves the process of ship queuing automatically using a configured system. Inside is an estimated ship docking time (Stevedoring Time). The ship docking time estimation is done to predict the loading and unloading time of the ship at the port. This will later support smart port to create a queue on each dock. To create a stevedoring time estimation system, KNN (K-Nearest Neighbor) is used to classify ships based on specifications from the ship. This ship classification is based on Length of All (LOA) or length of ship, Grosston or tonnage of ships and commodities from ships. Ship specifications will be provided by the Long Range (LoRa) device after LoRa has previously detected the ship to be docking. KNN will make the class based on data from the port of Tanjung Perak. This class is divided into 5 which is the estimated time of docking from the ship. The results after the system was tested resulted in an accuracy of 94.3% in providing estimated docking time from ships. And the most influential parameter in this research is ship commodity. The efficiency of stevedoring process in port could minimize the budget of ship expenses.