Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/24934
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dc.contributor.authorNoor, A.Z.M. A.Z.M.-
dc.contributor.authorFauadi, M.H.F.M.-
dc.contributor.authorJafar, F.A.,-
dc.contributor.authorRhaffor, K.A.-
dc.contributor.authorUniKL MSI-
dc.date.accessioned2021-05-28T01:58:33Z-
dc.date.available2021-05-28T01:58:33Z-
dc.date.issued2020-
dc.identifier.citationNoor, A.Z.M., Fauadi, M.H.F.M., Jafar, F.A., Rhaffor, K.A. Data prediction of reject unit from manufacturing company using auto regressive integrated moving average (ARIMA) algorithm (2020) International Journal of Emerging Trends in Engineering Research, 8 (9), art. no. 203, pp. 6164-6169. DOI: 10.30534/ijeter/2020/203892020.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/24934-
dc.description.abstractBig data is one of the nine pillars available in the nine pillars of industrial revolution 4.0. Malaysia came up with this incentive under the Ministry of International Trade and Industry whereby called Industry 4WRD. Problem faced by the industry people is not utilize the data obtain well. Rejects unit keeps on piling however, the data was not utilize to determine the trend of reject unit decrease. The objective of this research is to perform data prediction using ARIMA algorithm. The data were acquired, wrangled, explored, model and visualized in order to perform data prediction on reject units. The dataset on reject unit for 10 years respective to each month were obtained. ARIMA algorithm were utilized shows that the p – value decrease from 0.33 to 0.31. From these values, the next stage shows the prediction of reject units significantly decrease in the year 2021.en_US
dc.publisherInternational Journal of Emerging Trends in Engineering Researchen_US
dc.titleData Prediction of Reject Unit from Manufacturing Company Using Auto Regressive Integrated Moving Average (ARIMA) Algorithmen_US
dc.conference.year2020en_US
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