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OPTIMASI NILAI KINERJA RADIAL BASIS FUCNTION MENGGUNAKAN ALGORITMA PARTICLE SWARM OPTIMIZATION

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Penilaian

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Forecasting methods are used to see possible future data, so that problem solving can be done as early as possible. This study uses the Radial Basis Function method which is optimized using Particle Swarm Optimization, for data clustering the K-Means Clustering method is used. The radial basis function architecture used in this research is 6 input neurons, 2 hidden neurons, and 1 output neuron. In this study, the measurement accuracy of forecasting used is MAPE (Mean Absolute Percentage Error) and MSE (Mean Square Error). The test uses 208 Computer Hardware Data Set data and 1030 Concrete Compressive Strength Data Set data. From the test results obtained the best accuracy of 21%, it can be said that MAPE accuracy is reasonable because it is between 20% - 50%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
T798772022	T79877	T798772022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T798772022

Publisher

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

Collation

xiv, 53 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

001.420 7

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)

Jurusan Teknik Informatika
Metode Riset

Specific Detail Info

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Statement of Responsibility

SEPTA

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