ANALISIS POLA TEMPERATUR PEKANBARU DENGAN MENGGUNAKAN FRAKTAL DAN JARINGAN SARAF TIRUAN BERDASARKAN DATA TEMPERATUR BULANAN

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dc.contributor.authorRazzaq, Reynal Nur
dc.contributor.supervisorDefrianto, Defrianto
dc.date.accessioned2023-11-15T07:04:22Z
dc.date.available2023-11-15T07:04:22Z
dc.date.issued2023-07
dc.description.abstractClimate and global warming play a crucial role in the lives of living organisms on Earth. Temperature, varying in each region, is a vital aspect in climate observation. This study analyzed temperature fluctuations in Pekanbaru from 2016 to 2022 using fractal analysis and Backpropagation artificial neural networks. The research findings revealed that temperature prediction with Backpropagation artificial neural networks was quite accurate. However, errors during testing or validation could impact the comparison with the target values. Fractal analysis indicated a persistence tendency in temperature fluctuations in Pekanbaru, with a Hurst exponent of 0.7993 and a fractal dimension of 1.2007. Nevertheless, temperature fluctuations were also influenced by other factors, leading to varying levels of stability over certain periods. Thus, temperature in Pekanbaru can be considered a complex system with diverse fluctuation patterns and varying levels of complexity.en_US
dc.description.sponsorshipFakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Riauen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/11233
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectTemperatureen_US
dc.subjectExponent Hursten_US
dc.subjectFractal Dimensionen_US
dc.subjectArtificial Neural Networken_US
dc.subjectFluctuationen_US
dc.subjectBackpropagationen_US
dc.titleANALISIS POLA TEMPERATUR PEKANBARU DENGAN MENGGUNAKAN FRAKTAL DAN JARINGAN SARAF TIRUAN BERDASARKAN DATA TEMPERATUR BULANANen_US
dc.title.alternativeElfitraen_US
dc.typeArticleen_US

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