Skripsi

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

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Penilaian

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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%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407003308	T145609	T1456092024	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1456092024

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer., 2024

Collation

xvi, xviii hlm.; tab.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

518.107

Content Type

Text

Media Type

unmediated

Carrier Type

unspecified

Edition

-

Subject(s)

Prodi Teknik Informatika, Fakultas Ilmu Komputer
Fuzzy Tsukamonto

Specific Detail Info

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Statement of Responsibility

UIN YOLA

Other version/related

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