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Cross-correlation Analysis Between Sea Surface Temperature Anomalies and Several Climate Elements in The Indian Ocean Fanny Oktaviani; Miftahuddin; Ichsan Setiawan
Parameter: Journal of Statistics Vol. 1 No. 1 (2021)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (321.653 KB) | DOI: 10.22487/27765660.2021.v1.i1.15354

Abstract

Climate change can create a considerable impact in Indonesia. Aceh province is a province located on the island of Sumatra and it are located around in the Indian Ocean. Aceh Province has a considerable impact of climate change caused by the Sea Surface Temperature Anomalies (SSTA). The SSTA in the Indian Ocean is a parameter that can affect climatic conditions in Indonesia. The SSTA changes can cause an extreme climate change on earth. There are several climate elements affected by SSTA including air temperature, rainfall, wind speed, solar radiation, and relative humidity. One of the methods used to look at SSTA's relationship with some climate elements is the Cross-Correlation method. The climate data used in this study was a daily time series data. The purpose of this study is to find out SSTA's relationship with some climate elements. The results showed that using the Pearson correlation, the highest relationship was SSTA and the air temperature was 0.45. Meanwhile, the lowest relationship was SSTA and the rainfall was -0.05. Similarly, the Cross-Correlation method where the highest relationship was SSTA and the air temperature was 0.469, and the lowest close relationship was SSTA and the rainfall was -0.075.
Peramalam Model ARFIMA-GPH dan Intervensi Multi Input pada Indeks Harga Perdagangan Besar Indonesia Vivi Dina Melani; Miftahuddin; Muhammad Subianto
ESTIMASI: Journal of Statistics and Its Application Vol. 3, No. 2, Juli, 2022, Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.19683

Abstract

IHPBI is an early indicator in consumer price analysis. When inflation has occurred, Indonesia's economic stability begins to be disturbed, so in order to suppress inflation, the government raises interest rates and when the circulation of money begins to decrease. This study to see IHPBI in the next 3 years through forecasting using the ARFIMA method and multi-input intervention. This is done to find out the movement of the IHPBI over the next 3 years and to compare the two methods. The results obtained show that the selected model is ARFIMA(1,0.1579,0), the January 2009 intervention with ARIMA(1,1,1) of order (b=0, s=1, r=1) and November 2013 intervention with ARIMA(1,1,2) order (b=1, s=1, r=0). The IHPBI forecast for the next 3 years is increasing slowly every month