Perancangan Model COVID-19 di Indonesia dengan Metode Generalized Polynomial Modelling = Covid-19 modelling in indonesia with generalized polynomial modelling method

Feryanto, Sandy (2021) Perancangan Model COVID-19 di Indonesia dengan Metode Generalized Polynomial Modelling = Covid-19 modelling in indonesia with generalized polynomial modelling method. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

COVID-19 is a new variant of respiratory disease that were caused by a new virus named Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). In this research, the data of COVID-19 in Indonesia will be modeled with GPoM (Generalized Polynomial Modelling) to produces system of differential equations of polynomial form to detect couplings between input variables. The purpose of this research is to model Indonesia’s COVID-19 data with GPoM and to obtain the best model to be used for data forecasting. There are 3 input variables used in this research which is Daily Confirmed Cases, Daily Recovered Cases, and Daily Deaths. The modelling will be done by multiple different scenarios which also gives different results. The best model will be chosen by comparing each models MSE (Mean Square Error) and choose the smallest value for each scenarios. In this research, the data used are Indonesia’s COVID-19 data which is taken on a daily basis from March 2, 2020 to March 1 2021. In this research, the best model has been obtained to be used to do forecasting with the MSE value for Daily Confirmed Cases is 3,529,280.56, the MSE value for Daily Recovered Cases is 2,290,980.56, and the MSE value for Daily Deaths is 2,846.47. The forecasting results shows that every cases is increasing / COVID-19 merupakan varian baru penyakit pada saluran pernafasan yang disebabkan oleh virus baru Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). Dalam penelitian ini, data kasus COVID-19 di Indonesia akan dimodelkan dengan menggunakan GPoM (Generalized Polynomial Modelling) yang menghasilkan suatu sistem persamaan diferensial berbentuk polinomial yang bertujuan untuk melihat hubungan antara variabel yang menjadi input. Tujuan dari penelitian ini adalah memodelkan data COVID-19 di Indonesia dengan GPoM dan memilih model terbaik yang bisa digunakan untuk melakukan forecasting data. Dalam penelitian ini terdapat tiga variabel yang dijadikan input yaitu Kasus Terkonfirmasi Harian, Kasus Sembuh Harian, dan Kasus Meninggal Harian. Pemodelan dilakukan dengan beberapa skenario berbeda yang memberikan hasil yang berbeda pula. Model terbaik dipilih berdasarkan perbandingan dari nilai MSE (Mean Square Error) antar model yang mempunyai nilai terkecil untuk masing-masing skenario. Pada penelitian ini, data yang digunakan adalah data kasus COVID-19 di Indonesia yang diambil harian dari 2 Maret 2020 hingga 1 Maret 2021. Pada penelitian ini diperoleh model terbaik yang dapat digunakan untuk forecasting dengan nilai MSE dari Kasus Terkonfirmasi Harian adalah 3,529,280.56, nilai MSE dari Kasus Sembuh Harian adalah 2,290,980.56, dan nilai MSE dari Kasus Meninggal Harian adalah 2,846.47. Hasil forecasting menunjukkan seluruh kasus mengalami kenaikan.

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