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LEARNING ASSISTANCE ARTIFICIAL INTELLIGENCE (LESSIST AI)

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dc.contributor.advisor
dc.contributor.author Albertus, Jonattan Geraldo
dc.date.accessioned 2024-10-07T06:22:52Z
dc.date.available 2024-10-07T06:22:52Z
dc.date.issued 2023
dc.identifier.uri http://repository.president.ac.id/xmlui/handle/123456789/11837
dc.description.abstract In this thesis, a solution to the issue of stagnancy in the learning process due to the occurrence of choice overload to the learner in the learning resource collection phase is proposed. The proposed solution is a preventive act through a construct of artificial intelligence, called Lessist AI, that is able to handle the high complexity required to take over the responsibility of menial decision making. That delegation leaves the learner to be able to focus on the major decision making at the highest level of operation and also minimizing the probability of that issue occurring while preserving the suitability of the learning resources to the learner. The mentioned construct consists of three key points: the functions, the structures, and the user interface that are all established in this thesis. Moreover, parts of the construct structures, in particular the AI subsystems, are developed with Convoluted Neural Network (CNN) as the conceptual architecture. In that sense, CNN is the imaginary core of the construct. Finally, this work leaves out the implementation and expansion of the capability of Lessist AI as potential future works. en_US
dc.language.iso en_US en_US
dc.publisher President University
dc.relation.ispartofseries Information Technologies;001201700011
dc.subject Learning Assistance en_US
dc.subject Learning Resource Collection en_US
dc.subject Artificial Intelligence en_US
dc.subject AI Construct en_US
dc.subject Choice Overload en_US
dc.title LEARNING ASSISTANCE ARTIFICIAL INTELLIGENCE (LESSIST AI) en_US
dc.type Thesis en_US


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