OPTIMASI NILAI KINERJA RADIAL BASIS FUNCTION MENGGUNAKAN ALGORITMA PARTICLE SWARM OPTIMIZATION

DAKHILULLAH, MUHAMMAD ABDUR ROSYID and Rini, Dian Palupi and Miraswan, Kanda Januar (2022) OPTIMASI NILAI KINERJA RADIAL BASIS FUNCTION MENGGUNAKAN ALGORITMA PARTICLE SWARM OPTIMIZATION. Undergraduate thesis, Sriwijaya University.

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Abstract

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%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Forecasting, radial basis function, particle swarm optimization, MAPE, MSE.
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) > T14 Philosophy. Theory. Classification. Methodology Cf. CB478 Technology and civilization
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Abdur Rosyid Dakhilullah
Date Deposited:	26 Sep 2022 05:29
Last Modified:	26 Sep 2022 05:29
URI:	http://repository.unsri.ac.id/id/eprint/79877

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