The Comprehensive Mamdani Inference to Support Scholarship Grantee Decision

- Humaira - Department of Information Technology, Politeknik Negeri Padang, 21562, Indonesia
- Rasyidah - Department of Information Technology, Politeknik Negeri Padang, 21562, Indonesia
- Junaldi - Department of Electrical Engineering, Politeknik Negeri Padang, 21562, Indonesia
Indri Rahmayuni - Department of Information Technology, Politeknik Negeri Padang, 21562, Indonesia

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Fuzzy Mamdani has been mostly used in various disciplines of science. Its ability to map the input-output in the form of a surface becomes an interesting thing. This research took DSS case of a scholarship grantee. Many criteria in taking a decision need to be simplified so that the result obtained remains intuitive. The model completion by conducting two stages consisted of two phases. The first phase consists of four FIS blocks. The second phase consists of one FIS block. The FIS design in the first phase was designed in such a way so that the output obtained has a big score interval. FIS output at the first phase will become FIS input at the second phase. This big value range becomes good input at FIS in the second phase. Each FIS block has different total input. Until the surface formed must be seen from various dimensions to assure trend surface increasing or decreasing softly. This kind of thing is conducted by observing the movement of output dots kept for its soft surface form. The output dots change influenced by the membership function, the regulations used, total fuzzy set, and parameter value of membership function. This research used the Gaussian membership function. The Gaussian membership function is highly suitable for this DSS case. This article also explains the usage of a fuzzy set in each input, the parameter from the membership function, and the input value range. After observing the surface form with an intuitive approach, then this model needs to be evaluated. The evaluation was done to measure the model performance using Confusion Matrix. The result of model performance obtained accuracy in the amount of 85%.


Fuzzy; Mamdani; DSS; scholarship; reasoning.

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