Peramalan Kasus Virus Covid-19 Menggunakan Metode Arimax Untuk Memprediksi Level Ppkm Di Dki Jakarta Dan Surabaya.

Muhayat, Hanifan (2022) Peramalan Kasus Virus Covid-19 Menggunakan Metode Arimax Untuk Memprediksi Level Ppkm Di Dki Jakarta Dan Surabaya. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pandemi Covid-19 telah memberikan dampak yang signifikan terhadap berbagai sektor kehidupan di Indonesia, termasuk kesehatan, ekonomi, dan sosial. Pemerintah Indonesia telah menerapkan berbagai kebijakan untuk menekan laju penyebaran virus, salah satunya adalah Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM). Penentuan level PPKM yang tepat sangat krusial agar penanganan pandemi dapat berjalan efektif tanpa mengabaikan aspek ekonomi. Penelitian ini bertujuan untuk melakukan peramalan kasus harian Covid-19 dengan menggunakan metode ARIMAX (Autoregressive Integrated Moving Average with Exogenous Variables) dengan variabel eksogen berupa data mobilitas masyarakat. Metode ini dipilih karena kemampuannya dalam mengakomodasi variabel eksternal yang mempengaruhi data deret waktu. Data yang digunakan adalah data kasus harian Covid-19 dan data mobilitas masyarakat di DKI Jakarta dan Surabaya. Hasil penelitian menunjukkan bahwa model ARIMAX yang dibangun mampu melakukan peramalan dengan akurasi yang baik dan dapat digunakan untuk memprediksi level PPKM di masa depan berdasarkan tren kasus harian.
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The Covid-19 pandemic has had a significant impact on various sectors of life in Indonesia, including health, economy, and social. The Indonesian government has implemented various policies to suppress the spread of the virus, one of which is the Implementation of Community Activity Restrictions (PPKM). Determining the appropriate PPKM level is crucial so that pandemic management can be effective without ignoring economic aspects. This study aims to forecast daily Covid-19 cases using the ARIMAX (Autoregressive Integrated Moving Average with Exogenous Variables) method with exogenous variables in the form of community mobility data. This method was chosen because of its ability to accommodate external variables that affect time series data. The data used are daily Covid-19 cases and community mobility data in DKI Jakarta and Surabaya. The results show that the developed ARIMAX model is able to perform forecasting with good accuracy and can be used to predict future PPKM levels based on daily case trends.

Item Type:	Thesis (Other)
Additional Information:	RSSI 519.535 Muh p-1 2022
Uncontrolled Keywords:	ARIMAX. Covid-19. ARIMAX. Covid-19.
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD30.213 Management information systems. Dashboards. Enterprise resource planning.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	04 Jun 2026 06:42
Last Modified:	04 Jun 2026 06:42
URI:	http://repository.its.ac.id/id/eprint/133567

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