APLIKASI METODE MOVING AVERAGE TERHADAP PERAMALAN BEBAN LISTRIK JARINGAN DISTRIBUSI 20 KV PADA PENYULANG SIMPANG TIGA SATU DI GARDU INDUK KERAMASAN
DOI:
https://doi.org/10.31851/ampere.v4i1.2877Keywords:
load forecasting, cluster data, ARIMAAbstract
The forecast load requirements for electrical energy are an important fist step in planning and developing electricity supply at any time sufficiently, well dan continously. Therefore we need a load forecasting method that is accurate and easy to implement based on available data on the Autoregrsive Integrated Moving Average (ARIMA) method. So the advantages in this ARIMA Method are good for short-term forecasting, flexible and can represent a wide range of time series characters that occur in the short term, there are formal procedures in testing the suitability of the model and forecast interval and predictions have followed the model. Period of data in school by clustering the monthly data, from the results of cluster clustering forecasting the burden of each monthly period in the future can be done
Abstrak-- Prakiraan kebutuhan beban energi listrik merupakan langkah mula yang penting dalam perencanaan dan pengembangan penyediaan tenaga listrik setiap saat secara cukup, baik dan terus menerus. Oleh karena itu diperlukan suatu metode peramalan beban yang akurat dan mudah di implementasikan berdasarkan ketersediaan data yang ada pada metode Autoregrsive Integrated Moving Average (ARIMA). Maka keunggulan dalam Metode ARIMA ini baik untuk peramalan jangka pendek, fleksibel dan dapat mewakili rentang yang lebar dari karakter deret waktu yang terjadi dalam jangka pendek, terdapat prosedur yang formal dalam pengujian kesesuaian model dan interval ramalan dan prediksi sudah mengikuti modelnya. Periode data di kelolah dengan cara mengcluster data perbulan nya, dari hasil pengelompokkan atau cluster peramalan beban setiap periode bulanan kedepannya dapat dilakukan.
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