dc.contributor.author |
Medellu, Juliano Victor Christian |
|
dc.contributor.author |
Edwin Setiawan Nugraha |
|
dc.date.accessioned |
2023-04-18T07:29:41Z |
|
dc.date.available |
2023-04-18T07:29:41Z |
|
dc.date.issued |
2022 |
|
dc.identifier.issn |
(e):2620-3863 |
|
dc.identifier.uri |
http://repository.president.ac.id/xmlui/handle/123456789/11219 |
|
dc.description |
The 6th International Conference on Family Business and Entrepreneurship 2022. |
en_US |
dc.description.abstract |
Indonesia is known for its outstanding agricultural sector and natural wealth. Tea is one of the
plantation sectors that are mostly consumed all over the world and has been one of Indonesia’s
mainstay commodities that has already been listed as one of the 10 export commodities with a big
amount of production. Tea production data have a fluctuating pattern and characteristic. Therefore, it
is really important to know the projection of tea production for planning and management purposes.
The ARIMA (Autoregressive Integrated Moving Average) model is one of the methods that can be used
to predict future productions. The ARIMA (4,1,0) is found to be the most suitable model to be used with
a MAPE of 29.9%. The forecasting process shows the production will have an uptrend pattern for ten
months from March 2018. The Tea production forecast data will be useful for future planning and
production control. |
en_US |
dc.language.iso |
en_US |
en_US |
dc.publisher |
ICFBE |
en_US |
dc.subject |
Time series |
en_US |
dc.subject |
Arima |
en_US |
dc.subject |
Tea Production |
en_US |
dc.subject |
Forecasting |
en_US |
dc.title |
TEA PRODUCTION FORECASTING IN INDONESIA’S LARGE PLANTATION BY USING ARIMA MODELS |
en_US |
dc.type |
Article |
en_US |