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 |