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TEA PRODUCTION FORECASTING IN INDONESIA’S LARGE PLANTATION BY USING ARIMA MODELS

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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


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