### 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

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

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1. Abujiya, M.R., Farouk, A.U., Lee, M.H., Mohamad, I. 2013. On the Sensitivity of Poisson EWMA Control Chart. International Journal of Humanities and Management Science (IJHMS) Vol. 1, No. 1, Hal: 2320-4044
2. Abujiya, M.R., Abbasi, S.A., Riaz, M. 2016. A New EWMA Control Chart for Monitoring Poisson Observation. Quality and Reliability Engineering International Vol. 32, No. 3, Hal: 995-1005
3. Alevizakos, V., Koukouvinos, C. 2019. A Comparative Study on Poisson Control Charts. Quality Technology & Quantitive Management Vol 17, No. 3, Hal: 354-382
4. Borror, C.M., Champ, C.W., Rigdon, S.E. 1998. Poisson EWMA Control Charts. Journal of Quality Technology Vol. 30, Hal: 352-361.ICAO. 2001. Annex 13 Aircraft Accident and Incident Investigation-Ninth Edition. Montreal: International Civil Aviation Organization
5. Montgomery, D.C. 1990. Introduction to Statistical Quality Control. Washington: John Wiley and Sons, Inc
6. Montgomery, D.C. 2009. Introduction to Statistical Quality Control 6th edition. New York: John Wiley and Sons
7. Rachmah, N. F dan Purhadi. 2014. Pemodelan Jumlah Kematian Bayi dan Jumlah Kematian Ibu di Provinsi Jawa Timur dengan Menggunakan Bivariate Poisson Regression. Jurnal Sains dan Seni POM ITS Vol. 3, No. 2
8. Sari, E.R., Herdiana, E.T., Sirajang, N. 2020. Analisis Keakuratan Bagan Kendali Poisson Berdasarkan Ukuran Sampel. Jurnal Matematika, Statistika, dan Komputasi Vol. 16, No. 3, Hal: 325-336

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