IMPLEMENTASI JARINGAN SYARAF TIRUAN BACKPROPAGATION UNTUK PREDIKSI PENYEDIAAN ENERGI LISTRIK (STUDI KASUS PLN RAYON RUMBAI)

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dc.contributor.authorRahmawati, Amelia Wahyu
dc.contributor.supervisorElfizar, Elfizar
dc.date.accessioned2021-08-23T07:06:57Z
dc.date.available2021-08-23T07:06:57Z
dc.date.issued2020-10
dc.description.abstractThis study applies the backpropagation algorithm to determine the supply of electrical energy with six variables, namely the amount of electricity for social users, the amount of electricity for household users, the amount of electricity for business users, the amount of electricity for industrial users, the amount of electricity for government users and the amount of electricity for special services. This study uses 12 data with the division of training data and test data that is 90%: 10%, 80%: 20% and 70%: 30% of 12 data. This study also uses several parameters namely learning rate (α) 0.1 to 0.9, maximum epoch 50 and six hidden neurons. The results of the test show the highest average prediction accuracy of 99,90% at 90%: 10% data sharing, six hidden neurons, learning rate (α) of 0.8 and the number of epoch 65 and testing of Mean Square Error (MSE) of 0.00009.en_US
dc.description.sponsorshipJURUSAN ILMU KOMPUTER FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM UNIVERSITAS RIAUen_US
dc.identifier.otherwahyu sari yeni
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/10107
dc.language.isoenen_US
dc.subjectBackpropagationen_US
dc.subjectElectrical Energyen_US
dc.subjectArtificial Neural Networken_US
dc.subjectMean Square Erroren_US
dc.subjectPredictionen_US
dc.titleIMPLEMENTASI JARINGAN SYARAF TIRUAN BACKPROPAGATION UNTUK PREDIKSI PENYEDIAAN ENERGI LISTRIK (STUDI KASUS PLN RAYON RUMBAI)en_US
dc.typeArticleen_US

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