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Jurnal Lebesgue Jurnal Ilmiah Pendidikan Matematika Matematika dan Statistika
Article . 2022 . Peer-reviewed
License: CC BY NC SA
Data sources: Crossref
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PERAMALAN TINGKAT PENGANGGURAN TERBUKA PROVINSI BANTEN DENGAN METODE TRIPLE EXPONENTIAL SMOOTHING

Authors: Rindang Ndaru Puspita;

PERAMALAN TINGKAT PENGANGGURAN TERBUKA PROVINSI BANTEN DENGAN METODE TRIPLE EXPONENTIAL SMOOTHING

Abstract

The Unemployment Rate is the main indicator to measure the unemployment in the labor force. The higher Unemployment Rate will have an impact on the decline in people's welfare. Based the results of SAKERNAS in February 2022, Banten Province's Unemployment Rate is the highest in Indonesia, besides that, since the Covid-19 pandemic, the Banten Province's Unemployment Rate has increased. There needs an effort to reduce the Unemployment Rate so that it can reduce the number of unemployed, one of which is by knowing the predicted value of the Unemployment Rate in the future. From the results of historical data analysis, it is known that the data pattern of the Banten Province's Unemployment Rate is seasonal, so the Triple Exponential Smoothing Method is suitable to be used because it can stabilize seasonal patterns. Forecasting is carried out to determine the Unemployment Rate in Banten Province in the next 7 periods, from Semester 2 of 2022 to Semester 2 of 2025. From the forecasting results, the MAPE value is 8.858859%, which is smaller than 10%, that shows very accurate predictions. Furthermore, the results of this research are expected to be used as consideration in determining strategies to reduce the Banten Province's Unemployment Rate

Keywords

unemployment, QA1-939, forecasting, peramalan, triple exponential smoothing, Mathematics, pengangguran

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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