Skripsi

OPTIMASI FUZZY TIME SERIES CHENG MENGGUNAKAN PARTICLE SWARM OPTIMIZATION UNTUK HARGA BRENT OIL

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Penilaian

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The price of Brent oil is the first choice in investor list of commodities and its constant fluctuations lead to instability in the economy. Therefore, it is important to accurately predict oil price trends to increase profits for investors and benefit the wider community. In this study, the Fuzzy Time Series Cheng model will be used to predict the price of Brent oil. This model will be optimized using the Particle Swarm Optimization (PSO) algorithm to get the optimal interval value by maximizing the available parameter functions. The parameter in the optimized PSO is the number of particles. Number of iterations, w (inertia weight), c1 (speed coefficient 1) and c2 (speed coefficient 2). The test results using the Fuzzy Time Series Cheng produced a MAPE of 3.538%, while the Fuzzy Time Series Cheng test which was optimized for PSO obtained the best fitness value with a MAPE value of 2.964% along with the parameter values, namely the value of the number of iterations = 150, the number of particles = 50, the value of inertial weight = 0.3 and the value of c1 = 1.5 and the value of c2 = 1.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307000637	T87350	T873502022	Central Library (REFERENS)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T873502022

Publisher

Indralaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

xiii, 72 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

511.3 07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Logika Matematika
Jurusan Teknik Informatika

Specific Detail Info

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Statement of Responsibility

ANUG

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