KOMPARASI KLASTER PENGANGGURAN TERBUKA DI INDONESIA SEBELUM DAN SAAT PANDEMI COVID-19 MENGGUNAKAN K-MEAN CLUSTERING

Raihan Maliqi(1), Kursehi Falgenti(2*)

(1) Univrsitas Nusa Mandiri
(2) (Scopus ID 57189267771) Universitas Nusa Mandiri Jakarta
(*) Corresponding Author

Abstract


Open unemployment is a productive workforce of secondary education and higher education graduates who have not worked at all. The Indonesian Statistics Bureau (BPS) routinely publishes provincial open unemployment (TPT) data per semester. Many studies have analyzed TPT data by exploring new knowledge using data mining methods with cluster analysis techniques. Researchers have investigated the TPT data cluster under normal conditions before the COVID-19 pandemic. This study aims to find new knowledge from TPT data by comparing the TPT data cluster analysis results before the pandemic (2018-2019) with TPT data during the pandemic (2020-2021). Data mining techniques used are cluster analysis and the k-mean algorithm. The cluster analysis results are regional clusters with low and high unemployment rates before and during COVID-19. In addition, another finding is the movement from high to down clusters. Other interesting results are Covid-19 has the most impact on high unemployment in Aceh, North Sumatra, West Sumatra, Riau Islands, DKI Jakarta, West Java, Banten, East Kalimantan, North Sulawesi, Maluku, and West Papua. Anticipatory steps of the high open unemployment rates in 11 provinces, local government could design the program or policy that could support the BLT policy by the central government.

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References


W. A. Amrullah, N. Istiyani, and F. Muslihatinningsih, “Analisis Determinan Tingkat Pengangguran Terbuka di Pulau Jawa Tahun 2007-2016,” e-Journal Ekon. Bisnis dan Akunt., vol. 6, no. 1, p. 43, 2019, doi: 10.19184/ejeba.v6i1.11074.

M. Wardiansyah, Yulmardi, and Z. Bahri, “Analisis Faktor-Faktor Yang Mempengaruhi Tingkat pengangguran (Studi kasus provinsi-provinsi Se-Sumatra),” e-Jurnal Ekon. Sumberd. dan Lingkung. Vol., vol. 5, no. 1, pp. 13–18, 2016.

H. Susanto and S. Sudiyatno, “Data mining untuk memprediksi prestasi siswa berdasarkan sosial ekonomi, motivasi, kedisiplinan dan prestasi masa lalu,” J. Pendidik. Vokasi, vol. 4, no. 2, pp. 222–231, 2014, doi: 10.21831/jpv.v4i2.2547.

T. W. Liao and E. Triantaphyllou, Data Mining of Enterprise Data: Recent Advances in Algorithms and Applications. World Scientific Publishing Co. Pte. Ltd., 2007.

G. Gustientiedina, M. H. Adiya, and Y. Desnelita, “Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan,” J. Nas. Teknol. dan Sist. Inf., vol. 5, no. 1, pp. 17–24, 2019, doi: 10.25077/teknosi.v5i1.2019.17-24.

R. Garcia-Dias, S. Vieira, W. H. Lopez Pinaya, and A. Mechelli, “Clustering analysis,” in Machine Learning: Methods and Applications to Brain Disorders, 2019, pp. 227–247.

T. H. Sardar and Z. Ansari, “An analysis of MapReduce efficiency in document clustering using parallel K-means algorithm,” Futur. Comput. Informatics J., vol. 3, no. 2, pp. 200–209, 2018, doi: 10.1016/j.fcij.2018.03.003.

F. Sembiring, S. B. Rizqi, M. A. Aziz, and D. Firmansyah, “Analisis Pemetaan Tingkat Pengangguran Di Pulau Jawa Dan Bali Dengan Metode K-Means,” vol. 4, no. 1, 2019.

F. A. Tanjung, A. P. Windarto, and M. Fauzan, “Penerapan Metode K-Means Pada Pengelompokkan Pengangguran Di Indonesia,” Jurasik (Jurnal Ris. Sist. Inf. dan Tek. Inform., vol. 6, no. 1, p. 61, 2021, doi: 10.30645/jurasik.v6i1.271.

A.- Akramunnisa and F. Fajriani, “K-Means Clustering Analysis pada PersebaranTingkat Pengangguran Kabupaten/Kota di Sulawesi Selatan,” J. Varian, vol. 3, no. 2, pp. 103–112, 2020, doi: 10.30812/varian.v3i2.652.

D. Safira, M. Mustakim, E. D. Lestari, M. Iffa, and S. Annisa, “Pengelompokan Jumlah Penduduk Sumatera Barat Berdasarkan Angkatan Kerja Menggunakan Algoritma K-Means,” J. Ilm. Rekayasa dan Manaj. Sist. Inf., vol. 6, no. 1, p. 26, 2020, doi: 10.24014/rmsi.v6i1.8682.

W. Kawohl, “COVID-19, unemployment, and suicide,” The Lancet Psychiatry, vol. 7, no. 5. pp. 389–390, 2020, doi: 10.1016/S2215-0366(20)30141-3.

S. M. Smith, “Unemployment rises in 2020, as the country battles the COVID-19 pandemic,” Mon. Labor Rev., vol. 2021, pp. 1–45, 2021, [Online]. Available: https://api.elsevier.com/content/abstract/scopus_id/85111248433.

H. S. Munawar, “Effects of COVID?19 on the Australian economy: Insights into the mobility and unemployment rates in education and tourism sectors,” Sustain., vol. 13, no. 20, 2021, doi: 10.3390/su132011300.

P. H. Nguyen, “Assessing the Unemployment Problem Using A Grey MCDM Model under COVID-19 Impacts: A Case Analysis from Vietnam,” J. Asian Financ. Econ. Bus., vol. 7, no. 12, pp. 53–62, 2020, doi: 10.13106/JAFEB.2020.VOL7.NO12.053.

F. Almeida, “The effects of COVID-19 on job security and unemployment in Portugal,” Int. J. Sociol. Soc. Policy, vol. 40, no. 9, pp. 995–1003, 2020, doi: 10.1108/IJSSP-07-2020-0291.

R. T. Angita, R. Rinofah, and P. P. Sari, “Dampak Covid - 19 Terhadap Tingkat Pengangguran Di Indonesia,” J. Manag. Accounting, Econ. Bus., vol. 02, no. 01, pp. 486–491, 2021.

BPS, “Keadaan Ketenagakerjaan Indonesia Agustus 2021,” Ber. Resmi Stat. No. 84/11/Th. XXIV., vol. 2, 2021.

P. N. Harahap, “Implementasi Data Mining Dalam Memprediksi Transaksi Penjualan Menggunakan Algoritma Apriori (Studi Kasus PT. Arma Anugerah Abadi Cabang Sei Rampah),” Matics, vol. 11, no. 2, pp. 46–50, 2019.

E. D. Sikumbang, “Penerapan data mining penjualan sepatu menggunakan metode algoritma apriori,” J. Tek. Komput. AMIK BSI, vol. 4, no. 1, pp. 156–161, 2018.

BPS, “Tingkat Pengangguran Terbuka Menurut Provinsi,” 2022. [Online]. Available: https://www.bps.go.id/indicator/6/543/1/tingkat-pengangguran-terbuka-menurut-provinsi.html.




DOI: http://dx.doi.org/10.30998/faktorexacta.v16i1.15108

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