Pemodelan faktor-faktor cuaca dan mobilitas masyarakat dengan kasus positif covid-19 di Indonesia = Modeling daily covid-19 cases in Indonesia by weather factors and community mobility

Cindy, Cindy (2022) Pemodelan faktor-faktor cuaca dan mobilitas masyarakat dengan kasus positif covid-19 di Indonesia = Modeling daily covid-19 cases in Indonesia by weather factors and community mobility. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

COVID-19 (coronavirus disease 2019) merupakan sebuah penyakit yang ditemukan pada Desember 2019 dan dideklarasikan sebagai pandemi global pada Maret 2020. Penyakit ini menular melalui transmisi antara manusia yang terjadi dalam jarak dekat. World Health Organization belum memiliki bukti yang cukup kuat untuk mengatakan bahwa cuaca dan iklim berpengaruh besar pada transmisi COVID-19. Oleh karena itu, tujuan penelitian ini adalah mengetahui pengaruh dari faktor-faktor cuaca dan mobilitas masyarakat terhadap kasus terkonfirmasi harian di seluruh provinsi Indonesia dengan menggunakan uji korelasi. Selain itu, penelitian ini juga bertujuan untuk mendapatkan persamaan linear antara variabel-variabel tersebut dengan menggunakan counting GLM, yaitu model Poisson dan model negative binomial. Terdapat dua model untuk setiap provinsi di mana sebuah model dibentuk tanpa menggunakan metode clustering dan model lainnya dibentuk dengan metode clustering. Algoritma k-means clustering akan dibentuk untuk mengelompokkan provinsi-provinsi di Indonesia berdasarkan faktor-faktor cuaca. Performa kedua model akan dibandingkan dengan melihat nilai MAE (Mean Absolute Error), MASE (Mean Absolute Squared Error), dan RMSE (Root Mean Squared Error) masing-masing model. Hasil penelitian memperlihatkan bahwa mayoritas faktor-faktor cuaca berkorelasi negatif dan mayoritas variabel-variabel mobilitas masyarakat berkorelasi positif dengan penambahan kasus harian. Kemudian, terdapat 5 cluster yang terbentuk berdasarkan faktor-faktor cuaca, dengan 2 cluster berisi masing-masing satu provinsi. Hasil penelitian menunjukkan bahwa terdapat 31 provinsi lebih baik menggunakan model yang dibentuk tanpa metode clustering dan 3 provinsi lebih baik menggunakan model yang dibentuk dengan metode clustering. / COVID-19 (Coronavirus Disease 2019) is a disease found in December 2019 and was declared as a global pandemic in March 2020. This disease is spread between people who are in close contact with each other. The World Health Organization does not have enough evidence to say that weather and climate have a big effect on COVID-19 transmissions. Therefore, the purpose of this study is to know the effect of weather factors and community mobility towards daily confirmed cases in all provinces of Indonesia using correlation test. Other than that, this study also aims to get a linear equation between these variables using counting GLM, namely the Poisson model and negative binomial model. There are two models for each province where a model is formed without using the clustering method and the other one is formed with the use of clustering method. K-means clustering algorithm will be used to cluster each province in Indonesia based on the weather factors. Performance of the two models will be compared by the MAE (Mean Absolute Error), MASE (Mean Absolute Squared Error), and RMSE (Root Mean Squared Error) values. Research result shows that the majority of weather factors are negatively correlated with daily confirmed cases, whereas most of the community mobility variables are positively correlated. There are 5 clusters formed based on weather factors, with 2 clusters containing only one province each. Daily cases of 31 provinces are better modeled without the clustering method and 3 others are better modeled with the clustering method applied.

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Cindy, CindyNIM01112180008cindyteo889@gmail.com
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorMargaretha, HelenaNIDN0312057504helena.margaretha@uph.edu
Thesis advisorSaputra, Dewi TanasiaUNSPECIFIEDdewi.saputra@lecturer.uph.edu
Uncontrolled Keywords: Penyakit COVID-19; Faktor-faktor cuaca; Mobilitas masyarakat; Uji korelasi; K-means clustering; Model poisson; Model negative binomial
Subjects: Q Science > QA Mathematics
Divisions: University Subject > Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Depositing User: Users 6025 not found.
Date Deposited: 23 Feb 2022 11:06
Last Modified: 11 Apr 2022 03:16
URI: http://repository.uph.edu/id/eprint/46674

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