AZIZI, M. RIZKY and Rini, Dian Palupi and Miraswan, Kanda Januar (2023) OPTIMASI FUZZY TSUKAMOTO DALAM MEMPREDIKSI CURAH HUJAN DI KABUPATEN BANYUASIN MENGGUNAKAN ALGORITMA ARTIFICIAL BEE COLONY. Undergraduate thesis, Sriwijaya University.
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Abstract
Fuzzy inference system is one of the methods that can be used to predict the amount of rainfall. One of the common problems faced when implementing this fuzzy inference system is the difficulty in determining the boundary values of membership functions for each appropriate fuzzy set. One solution to overcome this problem is by applying optimization algorithms to help determine the boundary values of the appropriate fuzzy membership functions, such as the Artificial Bee Colony algorithm. The results of this study show that the Artificial Bee Colony algorithm is able to optimize Fuzzy Tsukamoto in predicting rainfall in Banyuasin Regency, resulting in a MAPE value of 26.02%, while rainfall prediction using the Fuzzy Tsukamoto method without optimization yields a larger MAPE value of 76.90%.
Item Type: | Thesis (Undergraduate) |
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Uncontrolled Keywords: | Fuzzy Inference System Tsukamoto, Artificial Bee Colony, Prediksi Curah Hujan |
Subjects: | Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76 Computer software |
Divisions: | 09-Faculty of Computer Science > 55201-Informatics (S1) |
Depositing User: | M. Rizky Azizi |
Date Deposited: | 21 Jun 2023 02:01 |
Last Modified: | 21 Jun 2023 02:01 |
URI: | http://repository.unsri.ac.id/id/eprint/112309 |
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