Abstract
Higher institutions admission faces the need for a precise and effective method to evaluate and select the most qualified applicants to be in their institution. This scenario also happened in Mengubah Destini Anak Bangsa (MDAB) programme, which is a new programme that was introduced by UiTM. Currently, MDAB programme have to manually evaluate every candidate’s data against the set of admission requirements before selecting the few successful ones. The manual process contributes many problems such as inaccurate decision resulting from human error, needs a lot of effort and is time consuming. The objectives of the project to assist the MDAB programme to select the most suitable applicants and also suggest suitable programme based on qualification of their SPM result. There are two phases involved in this project. The first phase is, user must input the data which will be processed in the fuzzy inference system. If the candidate qualifies, the system will proceed to the second phase which is programmes suggestion process. The result shows whether the candidate qualify and if so, will be suggested a programme. This project uses Sugeno-Style Fuzzy Inference technique to select the suitable candidates. This system prototype was tested with thirty sample data. From the analysis, this project accuracy is 73%. As the conclusion, this technique is suitable to be applied by MDAB programme.
Metadata
Item Type: | Thesis (Degree) |
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Creators: | Creators Email / ID Num. Nurul Adila, Zulkifli UNSPECIFIED |
Contributors: | Contribution Name Email / ID Num. Thesis advisor Itaza Afiani, Mohtar UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Mathematical statistics. Probabilities > Decision theory > Fuzzy decision making Q Science > QA Mathematics > Online data processing Q Science > QA Mathematics > Fuzzy logic |
Divisions: | Universiti Teknologi MARA, Perak > Tapah Campus > Faculty of Computer and Mathematical Sciences |
Keywords: | Mengubah Destini Anak Bangsa (MDAB) programme, artificial intelligence technique, fuzzy logic |
Date: | 1 April 2011 |
URI: | https://ir.uitm.edu.my/id/eprint/34261 |
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