Designing Case-Based Reasoning (CBR) System to Support Ship Operations using Case-Method Cycle

Ardhy Wisdarianto, Jonathan Sofian Lusa, Ivan Eka Aditya, Damayanti Elisabeth, Dana Indra Sensuse, Nadya Safitri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Ship operations management in the shipping industry becomes an aspect that needs to be appropriately managed due to the high complexity and related aspects. Integrative knowledge and technical expertise covering various disciplines needed to manage ship operations. The ship operation complexity problem also occurred in one Indonesian Shipping Company where the crew's knowledge in carrying out ship operations, for now, has not been well documented. According to an interview with one of the shipmasters in the company about current ship operation problems, knowledge management becomes an important aspect that needs to be handled properly, especially knowledge capture about handling operational processes and problem in daily ship operation. One of the knowledge management systems that help the organization to allow the acquisition of knowledge using similarity-based reasoning via learning and experience in the problem-solving process is case-based reasoning (CBR). Based on the current organizational problem and the impact of the CBR system, this research aims to design a Case-based Reasoning (CBR) system using Case-Method Cycle to capture the ship crew's knowledge in solving problems that occur when operating the ship. In this research, the Case-Method Cycle is used, which focuses on two essential processes: the case library development process and the data mining process so that CBR development runs effectively. This research used a qualitative approach through document analysis and semi-structured interviews to determine the elicitation process, expert criteria, and the proposed CBR system architecture. The results of this research are the design of a case library with a relational database management system (RDBMS) and the data mining process using cosine similarity for case retrieval.

Original languageEnglish
Title of host publication2022 5th International Conference on Computer and Informatics Engineering, IC2IE 2022
EditorsIndra Hermawan, Asep Taufik Muharram
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages65-73
Number of pages9
ISBN (Electronic)9781665453387
DOIs
Publication statusPublished - 2022
Event5th IEEE International Conference on Computer and Informatics Engineering, IC2IE 2022 - Jakarta, Indonesia
Duration: 13 Sept 202214 Sept 2022

Publication series

Name2022 5th International Conference on Computer and Informatics Engineering, IC2IE 2022

Conference

Conference5th IEEE International Conference on Computer and Informatics Engineering, IC2IE 2022
Country/TerritoryIndonesia
CityJakarta
Period13/09/2214/09/22

Keywords

  • case-based reasoning
  • case-method cycle
  • knowledge capture
  • ship operations
  • shipping
  • support system

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