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All Journal Prosiding Seminar Nasional Official Statistics
Lalu Muhamad Winadi Darundiye
Politeknik Statistika STIS
Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

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Perbandingan Hot-deck, SVM, dan Random Forest dalam Mengidentifikasi Industri Mikro dan Kecil Terdampak Covid-19 Tahun 2020 Iman Jihad Fadillah; Lalu Moh. Arsal Fadila; Lalu Muhamad Winadi Darundiye
Seminar Nasional Official Statistics Vol 2022 No 1 (2022): Seminar Nasional Official Statistics 2022
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (350.248 KB) | DOI: 10.34123/semnasoffstat.v2022i1.1235

Abstract

The spread of Covid-19 has been declared a pandemic since March 2020. The pandemic coupled with policies by the government resulted in a decline in the economic sector, especially in micro and small industries (IMK). Identifying IMK affected by the Covid-19 pandemic is an important step. There are two types of identification methods that are commonly used, namely statistical-based methods and machine learning-based methods. Each method has different measurement results. Therefore, an appropriate method is needed to identify IMKs affected by the Covid-19 pandemic. This study aims to compare the hot-deck, SVM and random forest methods, in order to obtain the best method to identify IMK affected by Covid-19. The results obtained are that the random forest method is the best method in identifying IMK affected by Covid-19.
Co-Authors Iman Jihad Fadillah Lalu Moh. Arsal Fadila