Analisis Ketercapaian Vaksinasi Terhadap Penyebaran COVID-19 Menggunakan Machine Learning
DOI:
https://doi.org/10.22441/incomtech.v12i3.15370Kata Kunci:
Vaksinasi, AdaBoostRegressor, Machine Learning, COVID-19Abstrak
Pada akhir tahun 2019 tepatnya bulan Desember Organisasi Kesehatan Dunia (WHO) mengatakan virus baru bernama virus COVID-19 ditemukan di Wuhan, Cina dengan cepat mempengaruhi masyarakat setempat. WHO sebagai organisasi kesehatan dunia menyetujui vaksinasi COVID-19 dan tersedia untuk seluruh masyarakat di dunia guna meningkatkan kekebalan tubuh manusia supaya tidak mudah terinfeksi oleh COVID-19. Untuk mengetahui ketercapaian vaksinasi diperlukan alat yang dapat bekerja secara otomatis dari pola data tanpa pemrograman eksplisit menggunakan Machine Learning (ML). Adapun data cakupan vaksinasi yang diprediksi adalah pada provinsi Jakarta dengan sumber melalui website satgas COVID-19 dengan parameter yang akan di uji adalah sasaran, belum vaksin, dosis 1, dosis 2, total vaksin diberikan kepada masyarakat. Pemodelan ML yang diusulkan adalah AdaBoost Regressor. Kinerja regressor ditentukan berdasarkan akar rata – rata keasalahan (RMSE) dan kesalahan mutlak (MAE). Nilai Akurasi yang didapatkan adalah 98% dengan nilai korelasi 99%. Berdasarkan berita dari kementrian kesehatan Indonesia dikatakan tercapainya vaksinasi jika sudah mencapai lebih kurang 80% untuk total vaksinasi yang sudah diberikan yaitu baik vaksinasi dosis 1 dan dosis 2. Total dosis vaksinasi yang sudah disebarkan pada masyarakat di provinsi DKI Jakarta dengan Kabupaten Adm. Kep. Seribu sebagai kota/kabupaten yang tertinggi untuk memberikan vaksinasi dosis 1 dan dosis 2 yang sudah mencapai 140% total dosis yang diberikan.
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