Noor Ajian Mohd Lair, and Abdul Halim Kudi, and Chua, Bih Lii and Rosalam Sarbatly, (2012) Forecasting of palm oil fruit delivery quantities using the trend adjusted exponential smoothing: A case study. In: 2012 2nd International Conference on Key Engineering Materials, ICKEM 2012, 26-28 February 2012, Singapore.
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Official URL: http://dx.doi.org/10.4028/www.scientific.net/AMR.4...
Palm oil industry has increasingly become the important industry for Malaysia. However, only a limited number of researches have been conducted on improving the palm oil industries. This research attempted to contribute by improving forecast activity along the palm oil industry. Specifically, this research centred on the development of forecast software for a Malaysian based palm oil estate. The developed forecasting software can be used to assist the estate manager in predicting accurately their monthly delivery quantity to the palm oil mill. The forecast technique selected for this research was the trend adjusted exponential smoothing technique. The performance of the trend adjusted exponential smoothing technique based software was then compared to the naïve method. Comparison in the performance indicated that the trend adjusted exponential smoothing produces lower root mean square error, which is equivalent to 14.6% of error produced by the naïve method. This finding emphasises the efficiency of the trend adjusted exponential smoothing in predicting the monthly delivery quantity by the palm oil estate.
|Item Type:||Conference Paper (UNSPECIFIED)|
|Uncontrolled Keywords:||Forecasting, Palm oil estate, Trend adjusted exponential smoothing, Exponential smoothing, Forecasting software, Malaysia, Malaysians, Palm oil, Root mean square errors, Forecasting, Managers, Mean square error, Research, Steel beams and girders, Vegetable oils|
|Subjects:||?? SB354-402 ??|
|Divisions:||SCHOOL > School of Engineering and Information Technology|
|Deposited By:||IR Admin|
|Deposited On:||02 Jan 2013 11:14|
|Last Modified:||08 Sep 2014 12:44|
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