UNIVERSITAS AIRLANGGA



Detail Article

Jurnal Biometrika dan Kependudukan

ISSN 2302707X

Vol. 2 / No. 2 / Published : 2013-12

Order : 4, and page :123 - 130

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Original Article :

Neural network control chart sebagai salah satu alternatif untuk diterapkan pada data non-normal

Author :

  1. Diah Indriani*1
  1. Dosen Fakultas Kesehatan Masyarakat

Abstract :

  Control chart is a tool for stability process measure. Efficient and reliable control chart is control chart which can detect mean and variants shift simultaneous. Process shift will be happened if the process out of control. Commonly control chart is Shewhart Control Chart which can use with normal distribution assumption in data. Neural network approximation is alternative for control chart methods. The superiority of Control Chart Neural Network can apply in normal or non-normal distribution data. This research was studied about neural network approximation in control chart for process shift detection. ARL (Average Run Length) value is tool for identified efectiveness of control chart. This research was generated exponential distribution with 9 shif process. The ARL value can detect the shift under 6 point value. This indicate that Neural Network Control effective for detecting shift ini non-normal data distribution.  

Keyword :

neural network control chart, average run length, non-normal, average run length, non-normal,


References :

Amitava, M,(1993) Fundamental of Quality Control and Improvement New york : Macmillan Publishing Company

Bishop, C.M,(1995) Neural Network for Pattern Recognition. London : Clarendon Press

Chang, S.I, Aw, C.A,(1999) A Neural Fuzzy Control Chart for Detecting and Classifying Process Mean Shift, Journal of Production Research, Volume 34, No. 8: 2265–2278 Abingdon : Taylor and Francis Ltd

Dedeakayogulari, Burnak N,(1999) The Determination of Mean and/or Variance Shif with Artificial Neural Networks, Journal of Production Research, Volume 37, No. 13: 3101–3114 Abingdon : Taylor and Francis Ltd

Guh R.S., Tannock D.T,(1999) Recognition of Control Chart Concurrent Using a Neural Network Approach, Journal of Production Research, Volume. 37, No. 17: 4007–4020 Abingdon : Taylor and Francis Ltd

Ho E.S., Chang S.I,(1999) A Two Neural Network Approach for Process Variance Change Detection and Classification, Journal of Production Research, Volunme 37,



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