# The analysis of partial autocorrelation function in predicting maximum wind speed
> Tinungki G.M.

URL kanonis: https://discover.unhas.ac.id/publications/pub_scopus_85062486601
Jurnal / Konferensi: Iop Conference Series Earth and Environmental Science
Tahun terbit: 2019
DOI: https://doi.org/10.1088/1755-1315/235/1/012097
ISSN: 17551307
Citations: 16

## Authors
- Tinungki G.M.

## Abstract
The stationary and non-stationary testing of the data set can be done using a plot analysis of the Partial Autocorrelation Function of the data, by viewing the maximum number of the expected value of Partial Autocorrelation.The Autocorrelation Function (ACF) is a function that shows the correlation between the observation of the t-time and the observation at the previous time.The autocorrelation function shows the autocorrelation coefficient, which is the correlation measurement of the observations at different times.Data taken from Statistics Indonesia -known in Indonesia as BPS (Badan Pusat Statistik)-contains the information about the maximum wind speed by month at the Paotere station in 2008 -2017 in Makassar City.By using the data, the maximum wind speed for the next 12 months will be estimated.iefrom January 2017 to December 2018.The results obtained, forecasting is done with 12 leads period ahead with 95% confidence interval.

## Keywords
- Autocorrelation
- Partial autocorrelation function
- Statistics
- Autocorrelation technique
- Wind speed
- Function (biology)
- Mathematics
- Confidence interval
- Data set
- Standard deviation
- Interval (graph theory)
- Meteorology
- Time series
- Physics
- Evolutionary biology
- Biology
- Autoregressive integrated moving average
- Combinatorics

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Sumber: Discover Unhas — RIMS Universitas Hasanuddin.
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