PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON

Nida Adelia; Mustafid Mustafid; Dwi Ispriyanti

doi:10.14710/j.gauss.12.1.71-80

DOI: https://doi.org/10.14710/j.gauss.12.1.71-80

PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON

*Nida Adelia - Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia

Mustafid Mustafid - Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia

Dwi Ispriyanti - Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia

How to cite (IEEE): N. Adelia, M. Mustafid, and D. Ispriyanti, "PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON," Jurnal Gaussian, vol. 12, no. 1, pp. 71-80, May. 2023. https://doi.org/10.14710/j.gauss.12.1.71-80

How to cite (APA): Adelia, N., Mustafid, M., & Ispriyanti, D. (2023). PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON. Jurnal Gaussian, 12(1), 71-80. https://doi.org/10.14710/j.gauss.12.1.71-80

How to cite (BCREC): Adelia, N., Mustafid, M., Ispriyanti, D. (2023). PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON. Jurnal Gaussian, 12 (1), 71-80 (doi:10.14710/j.gauss.12.1.71-80)

How to cite (Chicago): Adelia, Nida, Mustafid Mustafid, and Dwi Ispriyanti. "PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON." Jurnal Gaussian 12, no. 1 (2023): 71-80. Accessed : April 3, 2025. https://doi.org/10.14710/j.gauss.12.1.71-80

How to cite (Vancouver): Adelia N, Mustafid M, Ispriyanti D. PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON. Jurnal Gaussian [Online]. 2023 May;12(1):71-80. https://doi.org/10.14710/j.gauss.12.1.71-80.

How to cite (Harvard): Adelia, N., Mustafid, M., and Ispriyanti, D., 2023. PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON. Jurnal Gaussian, [Online] Volume 12(1), pp. 71-80. https://doi.org/10.14710/j.gauss.12.1.71-80 [Accessed : 3 Apr. 2025].

How to cite (MLA8): Adelia, Nida, Mustafid Mustafid, and Dwi Ispriyanti. "PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON." Jurnal Gaussian, vol. 12, no. 1, 04 May. 2023, pp. 71-80 , https://doi.org/10.14710/j.gauss.12.1.71-80. Retrieved : 3 Apr. 2025.

BibTex Citation Data :

@article{J.Gauss35888,
    author = {Nida Adelia and Mustafid Mustafid and Dwi Ispriyanti},
    title = {PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON},
    journal = {Jurnal  Gaussian},
  volume = {12},
    number = {1},
    year = {2023},
    keywords = {Aircraft accidents; Poisson; PEWMA; Control chart; ARL.},
    abstract = {Airplane is a mode of transportation that has an accident risk. Aircraft accidents are recorded to occur almost every year in Indonesia. The Poisson distribution is used to model the number of aircraft accidents that occur each year because they have a fixed time and independent. Statistical quality control is applied as a method to monitor the number of fatal aircraft accidents in Indonesia that are within control limits. One method to carry out quality control is to use a control chart. This study aims to apply the Poisson Exponentially Weighted Moving Average (PEWMA) method to create a control chart with a case study of the number of fatal airplane accidents in Indonesia from 1962 to 2021 with a Poisson distribution. The EWMA control chart is used to monitor the average or process variability and is considered effective in detecting small shifts in the process (the shift is said to be small if the shift is less than 1.5σ). The calculation of Average Run Length (ARL) is performed to test the performance of the PEWMA control chart. Control charts with smaller out-of-control ARLs are considered superior and can detect process shifts more quickly than other control charts. Based on the results of the calculation of the ARL value, it was found that the weight of 0.3 is the optimal weight with the smallest ARL value of 1.138 which is able to describe the state of the data on fatal aircraft accidents in Indonesia. The control chart with the optimal weight shows the data on fatal aircraft accidents in Indonesia that are tolerated equal to one.},
   issn = {2339-2541},   pages = {71--80}  doi = {10.14710/j.gauss.12.1.71-80},
    url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/35888}
}

Refworks Citation Data :

@article{{J.Gauss}{35888}, author = {Adelia, N., Mustafid, M., Ispriyanti, D.}, title = {PENERAPAN METODE POISSON EXPONENTIALLY WEIGHTED MOVING AVERAGE (PEWMA) UNTUK MEMBUAT BAGAN PENGENDALI VARIABEL BERDISTRIBUSI POISSON}, journal = {Jurnal Gaussian}, volume = {12}, number = {1}, year = {2023}, doi = {10.14710/j.gauss.12.1.71-80}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/35888} }

Citation Format:

Abstract

Airplane is a mode of transportation that has an accident risk. Aircraft accidents are recorded to occur almost every year in Indonesia. The Poisson distribution is used to model the number of aircraft accidents that occur each year because they have a fixed time and independent. Statistical quality control is applied as a method to monitor the number of fatal aircraft accidents in Indonesia that are within control limits. One method to carry out quality control is to use a control chart. This study aims to apply the Poisson Exponentially Weighted Moving Average (PEWMA) method to create a control chart with a case study of the number of fatal airplane accidents in Indonesia from 1962 to 2021 with a Poisson distribution. The EWMA control chart is used to monitor the average or process variability and is considered effective in detecting small shifts in the process (the shift is said to be small if the shift is less than 1.5σ). The calculation of Average Run Length (ARL) is performed to test the performance of the PEWMA control chart. Control charts with smaller out-of-control ARLs are considered superior and can detect process shifts more quickly than other control charts. Based on the results of the calculation of the ARL value, it was found that the weight of 0.3 is the optimal weight with the smallest ARL value of 1.138 which is able to describe the state of the data on fatal aircraft accidents in Indonesia. The control chart with the optimal weight shows the data on fatal aircraft accidents in Indonesia that are tolerated equal to one.

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Keywords: Aircraft accidents; Poisson; PEWMA; Control chart; ARL.

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In Vol 12, No 1 (2023): Jurnal Gaussian