OPTIMASI FUNGSI KEANGGOTAAN FUZZY TSUKAMOTO DALAM MEMPREDIKSI CURAH HUJAN DI PROVINSI LAMPUNG MENGGUNAKAN ALGORITMA ARTIFICIAL BEE COLONY

HUDORI, NURSILA ALWI and Rini, Dian Palupi (2024) OPTIMASI FUNGSI KEANGGOTAAN FUZZY TSUKAMOTO DALAM MEMPREDIKSI CURAH HUJAN DI PROVINSI LAMPUNG MENGGUNAKAN ALGORITMA ARTIFICIAL BEE COLONY. Undergraduate thesis, Sriwijaya University.

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Abstract

Rainfall is a natural phenomenon that plays an important role in various aspects of human life, such as agriculture, the environment, and water resource management. Accurate rainfall prediction is crucial for effective planning and decision-making. The complexity of rainfall and unpredictable climate changes make rainfall prediction challenging. Therefore, a prediction method capable of capturing and measuring the complexity of these climate changes is required. The Tsukamoto fuzzy method is one such method that can be used; however, predictions with this method often face difficulties in finding suitable membership functions for predicting specific problems, resulting in suboptimal prediction outcomes. To address this issue, a metaheuristic algorithm, the Artificial Bee Colony algorithm, was used to optimize the membership functions in the Tsukamoto fuzzy method. The results of the research showed that the prediction accuracy of the optimized Tsukamoto fuzzy method improved drastically, with MAPE decreasing from 96.25% to 27.60%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Fuzzy Tsukamoto, Curah Hujan, Algoritma Artificial Bee Colony
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75 Electronic computers. Computer science
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Nursila Alwi Hudori
Date Deposited:	27 May 2024 06:10
Last Modified:	27 May 2024 06:10
URI:	http://repository.unsri.ac.id/id/eprint/145609

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