PREDIKSI KUALITAS POLUSI UDARA PARTICULATE MATTER 2.5 DAN 10 DI DKI JAKARTA MENGGUNAKAN METODE ARIMA

PUTRI, ISNAENI KARUNIA (2024) PREDIKSI KUALITAS POLUSI UDARA PARTICULATE MATTER 2.5 DAN 10 DI DKI JAKARTA MENGGUNAKAN METODE ARIMA. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Air pollution has become an issue that has occurred in big cities throughout the world in recent years, especially in DKI Jakarta due to high air pollution. Longterm exposure to particulate matter can have negative impacts on human health and the environment. Therefore, monitoring and controlling air quality is very important to reduce the risk of adverse impacts from particulate matter. This research aims to predict air quality in DKI Jakarta for the next 366 days using the ARIMA method. Daily DKI Jakarta air pollution data is used to see the level of PM 10 and PM 2.5 pollution. Forecasting is carried out using the ARIMA model to provide forecasting accuracy with an RSME, MAE, MAPE, MSE size of <20%. This measure shows that the model can make predictions for the future period quite well. From the forecasting results, it can be seen that the PM 10 and PM 2.5 pollution levels will increase and decrease at each station for the next several periods. Keywords : ARIMA, Air Quality, Particulate Matter, Pollution, Forecasting Pencemaran udara menjadi salah satu isu yang terjadi di kota-kota besar seluruh dunia dalam beberapa tahun terakhir khususnya pada DKI Jakarta karena tingginya polusi udara. Pemaparan jangka panjang terhadap particulate matter dapat berdampak negatif pada kesehatan manusia dan lingkungan. Oleh karena itu, pemantauan dan pengendalian kualitas udara sangat penting untuk mengurangi risiko dampak buruk dari partikulat matter tersebut. Penelitian ini bertujuan untuk memprediksi kualitas udara di DKI Jakarta selama 366 hari ke depan menggunakan metode ARIMA. Data harian polusi udara DKI Jakarta digunakan untuk melihat bagaimana tingkat pencemaran PM 10 dan PM 2.5. Peramalan dilakukan dengan menggunakan model ARIMA untuk memberikan akurasi peramalan dengan ukuran RSME, MAE, MAPE, MSE bernilai <20%. Ukuran ini menunjukkan bahwa model dapat melakukan prediksi untuk periode mendatang dengan cukup baik. Dari hasil peramalan tersebut, dapat diketahui bahwa tingkat polusi PM 10 dan PM 2.5 akan mengalami naik dan turun dari masing-masing stasiun untuk beberapa periode ke depan. Kata Kunci : ARIMA, Kualitas Udara, Particulate Matter, Polusi, Peramalan

Item Type: Thesis (S1)
Call Number CD: FIK/SI. 24 117
NIM/NIDN Creators: 41820010028
Uncontrolled Keywords: ARIMA, Kualitas Udara, Particulate Matter, Polusi, Peramalan
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000.01-000.09 Standard Subdivisions of Computer Science, Information and General Works/Subdivisi Standar Dari Ilmu Komputer, Informasi, dan Karya Umum
600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 628 Sanitary Engineering and Environmental Protection Engineering/Rekayasa Sanitasi dan Teknik Perlindungan Lingkungan, Teknik Lingkungan
600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 628 Sanitary Engineering and Environmental Protection Engineering/Rekayasa Sanitasi dan Teknik Perlindungan Lingkungan, Teknik Lingkungan > 628.5 Pollution Control and Industrial Sanitation Engineering/Pengawasan Polusi dan Teknik Sanitasi Industri
Divisions: Fakultas Ilmu Komputer > Sistem Informasi
Depositing User: khalimah
Date Deposited: 31 Jul 2024 03:13
Last Modified: 31 Jul 2024 03:13
URI: http://repository.mercubuana.ac.id/id/eprint/89928

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