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M. Subhan Maulidin
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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JARINGAN SYARAF TIRUAN SEBAGAI METODE PERAMALAN BEBAN LISTRIK HARIAN DI PT. PISMATEX PEKALONGAN M. Subhan Maulidin; Luqman Assaffat
MEDIA ELEKTRIKA Vol 7, No 2 (2014): MEDIA ELEKTRIKA
Publisher : PSTE UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (632.322 KB) | DOI: 10.26714/me.7.2.2014.%p

Abstract

ABSTRACT Load electricity forecasting of industry can provide an information support to the Top Management and other stakeholders in terms of estimating and monitoring the power requirements and effort in providing it. With the artificial neural network method as an electrical load forecasting method using the short-term power load forecasting in the industrial sector, is expected load forecasting in this study had an average error is small. Research on the daily electricity load forecasting in PT. Pismatex Pekalongan using neural networks with daily electricity load data per hour for one week study. The Result of this study is MAPE of 7.23%. Keywords: Short-Term Forecasting, Electricity Charges, Neural Network
Co-Authors Luqman Assaffat