Penerapan Algoritma Model Regresi pada Angka New Active Cases Covid-19 di Indonesia.
DOI:
https://doi.org/10.26418/jari.v1i1.59941Keywords:
COVID-19, New Active Cases, Multiple Linear Regression, Neural Network, Model RegresiAbstract
Virus COVID-19 sudah menjadi wabah yang menyebar hampir keseluruh dunia dalam dua tahun terakhir. Kasus aktif COVID-19 dapat menjadi salah satu penyebab penularan virus ini. Hal ini dikarenan, kasus aktif merupakan sebutan bagi sekelompok orang yang dinyatakan positif COVID-19 dan masih dalam masa perawatan. Dalam penerapannya, penggunaan algoritma model regresi untuk memprediksi angka new active cases COVID-19 dapat dilakukan, berdasarkan feature yang berkolerasi baik dengan label. Tujuan dari penelitian ini adalah untuk menganalisa penerapan algoritma model regresi prediksi angka new active cases yang dibangun menggunakan algoritma Multiple Linear Regression dan Neural Network, dengan menambahkan proses optimasi hyperparameter terhadap hyperparameter dari masing-masing algoritma. Berdasarkan hasil pengujian akurasi terhadap kedua model, menunjukkan bahwa error yang dihasilkan oleh kedua model ini dianggap masih cukup besar, namun nilai R2-nya dianggap dapat menjelaskan hubungan antara variabel bebas dengan label yang kuat, serta model dapat mengikuti pola trend dari data aktualnya. Model yang memiliki akurasi terbaik, yaitu model yang dibangun menggunakan algoritma Neural Network yang menghasilkan nilai RMSE = 925.452, Absolute Error = 669.729 dan R2 = 0.866.
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