Please use this identifier to cite or link to this item: https://repository.unej.ac.id/xmlui/handle/123456789/110499
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dc.contributor.authorMUHTADI, Ahmad-
dc.contributor.authorKALOKO, Bambang Sri-
dc.contributor.authorHARDIANTO, Triwahju-
dc.date.accessioned2022-11-02T02:06:47Z-
dc.date.available2022-11-02T02:06:47Z-
dc.date.issued2022-09-21-
dc.identifier.urihttps://repository.unej.ac.id/xmlui/handle/123456789/110499-
dc.description.abstractBattery Management System (BMS) is a tool used to monitor and manage battery conditions. In battery modeling to engineer batteries, it is necessary to identify the parameters. Accurate modeling and identification of parameters are required to create a reliable BMS system. In this study, battery modeling was carried out using a moving average and ARIMA model because it was able to predict the shape of the data to resemble its original form and was significant. Meanwhile, the identification of parameters is carried out using test data that has been carried out on a dataset of power consumption for 1 year. The results obtained by the ARIMA model which has the best accuracy for predicting BMS, namely the MSE test: 0.076 with a relatively small error deviation value.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Science, Engineering and Technologyen_US
dc.subjectARIMAen_US
dc.subjectMoving Averageen_US
dc.subjectBMSen_US
dc.subjectPhotovoltaicen_US
dc.subjectModelingen_US
dc.titleModeling Battery Monitoring System (Bms) On Photovoltaic Based Moving Average And Autoregressive Integrated Moving Average Model (Arima)en_US
dc.typeArticleen_US
Appears in Collections:LSP-Jurnal Ilmiah Dosen

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