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000			02081ntm a2200265 a 4500
001			vtls000091186
003			KUKTEM
005			20251117113304.0
008			150908t2014 da f abm 000 0 eng d
020			_aTHE0001505(Local)
039		9	_a201905271020 _basmadi _c201711291127 _dsaini _c201509081613 _dasma _y201509081612 _zasma
040			_aUMP
090			_aHD30.27 .N67 2014 r Bc.
100	0		_aNorwadati Najihah Azman
245	1	2	_aA study on demand forecasting in textile industry / _cNorwadati Najihah Azman
260			_aKuantan, Pahang : _bUMP, _c2014
300			_axi, 58 p. : _bill. (some col.) ; _c30 cm. + _e1 CD-ROM
500			_aFaculty of Industrial Management
502			_aProject paper (Bachelor of Industrial Technology Management with Honours) -- Universiti Malaysia Pahang - 2014
504			_aBibliography : p. 55-57
520	3		_aNumerous operation decision are based on the proper forecast of future demand. For this reason, textile industry considered forecasting is crucial process for effectively guiding several activities. The objectives of this research are to identify demand forecasting method applied by the company, to analyses the sales data using several forecasting method and to propose the most suitable forecasting method to the company. The forecasting method involves in this study is Time Series Forecasting Method. The forecasting method was analyzed by using forecast error measurement tools includes Mean Absolute Deviation (MAD), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Tracking Signal to monitor the forecast result of various method. The result of this study showed that the Additive Decomposition (Seasonal) of forecasting method is the most suitable method to apply and proposed to the textile Industry. This method comes out With the accurate result and least forecast errors
650		0	_aBusiness forecasting
856	4	0	_uhttp://ecollib.ump.edu.my/id/eprint/9649 _zAccess in library only
999			_aVIRTUA40 _c6153 _d6159
999			_aVTLSSORT008002000400090010002450260030005000502050405200650085609992