Pengendalian Kualitas Udara Di Kota X Tahun 2024 Menggunakan Diagram Kendali Multivariate Exponentially Weighted Moving Variance (MEWMV) Dan Multivariate Exponentially Weighted Moving Average (MEWMA)

Widianti, Hediana Bella (2025) Pengendalian Kualitas Udara Di Kota X Tahun 2024 Menggunakan Diagram Kendali Multivariate Exponentially Weighted Moving Variance (MEWMV) Dan Multivariate Exponentially Weighted Moving Average (MEWMA). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Kota X merupakan kota besar dengan jumlah penduduk mencapai 3,02 juta jiwa pada tahun 2024 dengan laju pertumbuhan penduduknya sebesar 0,29 persen. Pertambahan penduduk yang terjadi setiap tahun meningkatkan aktivitas sektor industri dan transportasi, yang berdampak pada peningkatan jumlah kendaraan bermotor hingga mencapai 3.806.238 unit di tahun 2024, sehingga berkontribusi pada pencemaran udara di kota tersebut. Penyebab utama pencemaran udara di Kota X berasal dari sektor transportasi dan industri, dimana kedua sektor tersebut menghasilkan polutan seperti PM2.5, PM10, dan SO2 yang seringkali melebihi baku mutu kualitas udara ambien, sehingga berpotensi menimbulkan gangguan kesehatan pada masyarakat. Oleh karena itu, evaluasi untuk pengendalian kualitas udara secara statistik dilakukan dengan menggunakan diagram kendali multivariat MEWMV dan MEWMA yang efektif mendeteksi perubahan kecil pada variabilitas dan rata-rata proses. Tiga karakteristik kualitas udara yang diamati adalah PM10, PM2.5, dan SO2. Diagram kendali MEWMV digunakan untuk memantau variabilitas proses dengan pembobot optimum yang terpilih adalah ω = 0,1 dan λ = 0,4 sedangkan diagram MEWMA digunakan untuk memantau rata-rata proses dengan pembobot optimum λ = 0,1. Hasil analisis MEWMV dan MEWMA pada data fase I menunjukkan kondisi belum terkendali secara statistik sehingga diperlukan identifikasi penyebab out of control serta penanganan data yang out of control tersebut. Setelah dilakukan penanganan data yang out of control maka variabilitas dan rata-rata proses pada data fase I telah terkendali secara statistik. Analisis pada fase II yang menunjukkan variabilitas proses kualitas udara di Kota X Tahun 2024 telah terkendali namun secara rata-rata proses belum terkendali secara statistik. Hasil analisis kapabilitas proses baik secara univariat maupun multivariat menunjukkan bahwa proses telah kapabel.
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City X is a large city with a population of 3,02 million in 2024, growing at a rate of 0,9 percent per year. This population growth increases activities in the industrial and transportation sectors, leading to a rise in motor vehicles to 3.806.238 units in 2024. As a result, air pollution in the city has increased. The main sources of air pollution in City X are the transportation and industrial sectors, which emit pollutants such as PM2.5, PM10, and SO2. These pollutants often exceed the ambient air quality standards and may cause health problems for the community. To monitor and control air quality, statistical evaluations were conducted using multivariate control charts called MEWMV and MEWMA. These charts effectively detect small changes in process variability and average levels. The three air quality indicators measured were PM10, PM2.5, and SO2. The MEWMV chart was used to observe process variability with optimal weights set at ω = 0.1 and λ = 0.4. The MEWMA chart was used to monitor the average process level with an optimal weight of λ = 0.1. Results from phase I data showed that the air quality process was not yet statistically controlled, so it was necessary to identify and manage out of control data points. After handling these data, both variability and average levels in phase I became statistically controlled. Phase II analysis indicated that the variability of the air quality process was under control, but the average levels still were not statistically controlled. Results from capability analysis, both univariate and multivariate, showed that the process is capable.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Diagram Kendali MEWMA, Diagram Kendali MEWMV, Kapabilitas Proses, Kualitas Udara, Polutan Udara, Air Pollutants, Air Quality, MEWMA Control Chart, Process Capability
Subjects:	T Technology > TD Environmental technology. Sanitary engineering > TD883.5 Air--Pollution T Technology > TS Manufactures > TS156 Quality Control. QFD. Taguchi methods (Quality control)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Hediana Bella Widianti
Date Deposited:	05 Aug 2025 12:50
Last Modified:	05 Aug 2025 12:50
URI:	http://repository.its.ac.id/id/eprint/127632

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