Tingkat Pengangguran Terbuka Periode Sebelum hingga Sesudah Pandemi Covid-19 dengan Pendekatan Non-Parametrik
DOI:
https://doi.org/10.31537/estimator.v2i1.1829Keywords:
Covid-19, Uji Friedman, pendekatan non parametrik, tingkat pengangguran terbukaAbstract
The unemployment rate is one of the factors related to a country's economy. During the COVID-19 pandemic, there was a decline in economic growth in Indonesia which also had a negative impact on the labor market. The decreased mobility of people causes reduced economic activity and ultimately the number of poverty increases. This research compares the percentage of unemployment rates in Indonesia in the period before, during, and after the COVID-19 pandemic using a non-parametric approach because the data of unemployment rates in 2020 and 2021 are not normally distributed. The non-parametric tests used in this research are the Friedman test and the Nemenyi post-hoc test. Based on research conducted, it was found that there was a statistically significant difference (?=5%) between the percentage of unemployment rates during the COVID-19 pandemic and the period before and after the COVID-19 pandemic. Meanwhile, the difference between before and after COVID-19 occurred was not statistically significant (?=5%). However, the average unemployment rate in 2023 is the smallest that compared to previous years. This shows that the economy in Indonesia is slowly starting to improve after the COVID-19 pandemic.
References
Kementerian Koordinator Bidang Perekonomian, Laporan Kajian: Dampak Pandemi Covid-19 Terhadap Ketenagakerjaan di Indonesia. Jakarta Pusat: Kemenko Perekonomian, 2021.
Badan Pusat Statistik. (2021) Pertumbuhan Ekonomi Indonesia Triwulan IV-2020. [Online], https://www.bps.go.id/id/pressrelease/2021/02/05/1811/ekonomi-indonesia-2020-turun-sebesar-2-07-persen%E2%80%93c-to-c-.html, tanggal akses: 28 Mei 2024.
A. S Darmawan dan M. N Mifrahi, “Analisis Tingkat pengangguran Terbuka di Indonesia Periode Sebelum dan Saat Pandemi Covid-19,” Jurnal Kebijakan Ekonomi dan Keuangan., vol. 1, hal 111-119, 2022.
A. Hardjanto, T. Novianti, D. V. Panjaitan, S. R. W. Nugraheni, dan S. Mulatsih, "Pandemi COVID-19 dan Pengangguran di Kabupaten Tangerang", Jurnal Manajemen dan Organisasi (JMO), vol. 13, hal. 313-323, Desember, 2022.
Badan Pusat Statistik. (2023a) Profil Kemiskinan di Indonesia, Maret 2023. [Online], https://www.bps.go.id/id/pressrelease/2023/07/17/2016/profil-kemiskinan-di-indonesia-maret-2023.html, tanggal akses: 8 Juni 2024.
Badan Pusat Statistik. (2023b) Keadaan Ketenagakerjaan Indonesia Februari 2023. [Online], https://www.bps.go.id/id/pressrelease/2023/05/05/2001/februari-2023-tingkat-pengangguran-terbuka--tpt--sebesar-5-45-persen-dan-rata-rata-upah-buruh-sebesar-2-94-juta-rupiah-per-bulan.html, tanggal akses: 8 Juni 2024.
R. Maliqi dan K. Falgenti, "Komparasi Klaster Pengangguran Terbuka di Indonesia Sebelum dan Saat Pandemi Covid-19 Menggunakan K-Mean Clustering," Factor Exacta, vol. 16, hal. 23-30, 2023.
D. G. Pereira, A. Afonso, F. M. Medeiros, “Overview of Friedman’s Test and Post-hoc Analysis,” Communications in Statistics - Simulation and Computation, vol. 44, hal. 2636–2653, 2015.
Pusat Statistik, “Keadaan Angkatan Kerja di Indonesia: Agustus 2019,” Jakarta: BPS RI, 2019
M. Al Jundi, “Analisis Faktor yang Mempengaruhi Tingkat Kemiskinan Provinsi-Provinsi di Indonesia,” Universitas Diponegoro, 2014.
Marhawati, dkk., Statistika Terapan. Sukoharjo: Tahta Media Group, 2022.
S. S. Asih, A. Tripena, A. Wardayani, "Studi Perbandingan Uji Nonparametrik K-Sampel Independen," Ulil Albab: Jurnal Ilmiah Multidisiplin, vol (2), hal. 3503-3514, 2023.
M. Friedman, “The use of ranks to avoid the assumption of normality implicit in the analysis of variance,” Journal of the American Statistical Association, 32, hal. 675- 701. 1937.
E. A. H. Elamir, “A Graphical Approach for Friedman Test: Moments Approach,” arXiv preprint arXiv:2202.09131, hal. 1-18, 2022.
E. N. Na'imah dan S. A. Rohmaniah, "Analisis Data Produksi Ikan Konsumsi Menggunakan Uji Friedman," Jurnal UJMC, Vol (6), hal. 25-32, 2020.
R. Kusumawati, dkk., "Workshop Analisis Perbandingan k Populasi dengan Pendekatan Nonparametrik untuk Penelitian Ilmu Sosial dan Pendidikan," J. Pengabdian Masyarakat MIPA dan Pendidikan MIPA, vol. 6(2), hal. 84-91, 2022.
N. M. Razali dan Y. B. Wah, "Power Comparision of Shapiro-Wilk, KolmogorovSmirnov, Lilliefors, and Anderson-Darling tests," Journal of Statistical modeling and Analytics, vol (2), hal. 21–33, 2011.
