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Media Statistika

Vol 12, No 2 (2019): Media Statistika

Herni Utami (Departemen Matematika, FMIPA, Universitas Gadjah Mada)
Yunita Wulan Sari (Departemen Matematika, FMIPA, Universitas Gadjah Mada)
Subanar Subanar (Departemen Matematika, FMIPA, Universitas Gadjah Mada)
Abdurakhman Abdurakhman (Departemen Matematika, FMIPA, Universitas Gadjah Mada)
Gunardi Gunardi (Departemen Matematika, FMIPA, Universitas Gadjah Mada)

Publish Date
30 Dec 2019

This paper will study forecasting model for electricity demand in Yogyakarta and forecast it for 2019 until 2024. Usually, electricity demand data contain seasonal. We propose Singular Spectral Analysis-Linear Recurrent Formula (SSA-LRF) method. The SSA process consists of decomposing a time series for signal extraction and then reconstructing a less noisy series which is used for forecasting. The SSA-LRF method will be used to forecast h-step ahead. In this study, we use monthly electricity demand in Yogyakarta for 11 year (2008 to 2018). The forecasting results indicates that the forecast using window length of L=26 have good performance with MAPE of 1.9%.

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