IoT-based Knowledge Repository Design for Supporting Knowledge Integration within the Marine Information System Study Program

Fitriasari, Novi Sofia; Anzani, Luthfi; Widiyanto, K.; Lukman, Lukman; Apriansyah, M. R.; Setiawan, Muhammad Andi; Asnawiah, L. P.; Shafa, M. G.

doi:10.1088/1742-6596/1811/1/012101

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Knowledge repository is defined differently by different people, depending on their perspective of needs. Knowledge repository is said to be commonly used to store and manage explicit knowledge from knowledge worker (Fitriasari et al, 2021), as it is a computerised system that maintains various digital resources to be accessed by the users electronically (Zamani & Izhar, 2018). On the other hand, knowledge repository is also referred to as a wide range of knowledge domains across various subject areas, not limited to only computing and business processes within a company (Zheng & Dahl, 2010).…”

Section: Knowledge Loss and Recoverymentioning

confidence: 99%

Agent-mediated Knowledge Recovery: The Case of Turnover-induced Knowledge Loss in a Knowledge-intensive Institution

Ismail,

Shaikh Ali

2024

IJARBSS

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The retention of tacit knowledge within organizations, particularly during employee transitions, poses a significant challenge in business settings. This problem is often exacerbated by the underutilization of technology to structure and retain this knowledge. To address this issue, this study proposes an agent-mediated model for knowledge recovery aimed at minimizing knowledge loss by identifying essential information in knowledge repositories and transforming unstructured data into structured format. This study adopts a qualitative case study methodology, employing semi-structured interviews and observational techniques for data collection. Findings, as elucidated through Process-People-Technology (PPT) analysis, highlight the value of understanding routine human tasks in creating rulebased process flows. The proposed CIDM Model (Connect-Identify-Decide-Method) entails of agents, equipped with natural language processing capabilities, which may discern, comprehend, and act on unstructured messages. Additionally, the model enables these agents to identify the roles and responsibilities of message senders and recipients, leading to a more informed decision-making process concerning the use of obtained information. The study highlights the importance of a solution for a more structured, efficient means of retaining organizational knowledge, potentially revolutionizing current management practices.

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Section: Knowledge Loss and Recoverymentioning

confidence: 99%

Agent-mediated Knowledge Recovery: The Case of Turnover-induced Knowledge Loss in a Knowledge-intensive Institution

Ismail,

Shaikh Ali

2024

IJARBSS

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“…CoP consists of students, lecturers, and/or researchers who are interested in the field. Meanwhile, the organizations involved in the formation of big data on marine resources are the Ministry of Marine Affairs and Fisheries and the Indonesian Institute of Sciences (LIPI) [12].…”

Section: People/usersmentioning

confidence: 99%

Marine and Fishery Big Data System Model: A Knowledge Management System Perspective

Fitriasari

Arifin

Armelita

et al. 2023

Advances in Science and Technology

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The need for data on marine resources is increasing, Indonesia as one of the world's maritime countries plays a big role in this. The successful application of big data on marine resources is not only seen from the technology used in it but it is also must related to other system components. A qualitative approach is used in this study to produce a big data model that can be applied to marine resources. This research produces a big data model from the perspective of a Knowledge Management System (KMS) which consists of four elements or layers, namely organization, Big Data Process and Technology Information, and people as users. The integration of these four elements is expected to promote economic transformation and knowledge in the marine and fishery sectors.

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IoT-based Knowledge Repository Design for Supporting Knowledge Integration within the Marine Information System Study Program

Cited by 2 publications

References 12 publications

Agent-mediated Knowledge Recovery: The Case of Turnover-induced Knowledge Loss in a Knowledge-intensive Institution

Agent-mediated Knowledge Recovery: The Case of Turnover-induced Knowledge Loss in a Knowledge-intensive Institution

Marine and Fishery Big Data System Model: A Knowledge Management System Perspective

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