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Enhancement of ship basic planning support system of bulk carrier using MLDB
Arifin M.D.
Aip Conference Proceedings
Abstract
Big Data (BD) has being used recently in a number of industries. BD is a vast collection of datasets that are useful for understanding both the present and the future. The volume of business data, or BD, has grown significantly in the maritime industry. This includes ship data, port data, route-related data, and AIS data. in order to effectively use its data and gain insightful knowledge about the actions of the shipping business. Similar to this, rapid development is necessary due to the dynamic nature of global trade. Thus, in order to meet market demands, it is imperative to actualize certain ship characteristics. Given this, the authors looked at how to use big data in marine logistics, which was linked to the Marine Logistics Database (MLDB), to predict ship demand and create a ship basic management support system. The methodology used in this study to produce sufficient data on BD and its relevance to realistic ship design is the main topic. The created database’s reliability data is validated in this investigation. Moreover, the proposed ship allocation model has three models: shipper, owner, and operator, in accordance with a marine logistic database. As a result, the suggested model may be applied to forecast ships that will be in high demand in the future and to reproduce the ship allocation on the intended shipping route. As a result, the necessary ship performance, size, and demand are obtained, all of which are critical for ship basic planning.