Arif, Muhammad Syaiful (2021) An Expert System for the Identification of the Mentally Impaired Using the Fuzzy Sugeno Method. Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.
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Abstract
Mental retardation is a state of mental retardation, this condition is also known as mental retardation. Mentally retarded children are children where mental development does not take place normally, so as a result there is an inability in intellectual field, will, taste, social adjustment and so on. Identification of mental retardation is usually carried out by an expert or expert in the field of child growth and development, but actually parents can also carry out early identification of possibility mental retardation in children by observing children's behavior in everyday life, especially from how to communicate, interact socially with their peers, and the ability to imagine children. For this reason, in this study an expert system was created which can later be used as a solution to assist parents in early identification of possibility of mental retardation in children. In designing the expert system it will go through several stages, started initial stage is analyzing needs, namely by finding and collecting symptom data information and its classification obtained from an expert or an expert. The next stage is to process data information that has been obtained by building and designing a system with the proposed method using Fuzzy Sugeno method. With the development of this expert system and packaged with a good display, it can greatly assist parents in predicting and recognizing whether child is mentally retarded or not. Keywords : expert system, identification, retardation, fuzzy, sugeno
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | expert system, identification, retardation, fuzzy, sugeno |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Fakultas Teknik > Program Studi Teknik Informatika |
Depositing User: | 1461404875 Arif Muhammad |
Date Deposited: | 19 Apr 2022 02:10 |
Last Modified: | 21 Jul 2022 02:51 |
URI: | http://repository.untag-sby.ac.id/id/eprint/15617 |
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