Amalia, Diza (2021) Pemetaan Potensi UMK Kabupaten/Kota Di Jawa Timur Berdasarkan Jumlah UMK Dan Jumlah Tenaga Kerja UMK Menurut Lapangan Usaha Dengan Metode K-Means Dan K-Medoids Clustering. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pemetaan potensi UMK di Jawa Timur dapat dilakukan dengan melakukan analisis clustering terhadap jumlah UMK dan jumlah tenaga kerja UMK berdasarkan sektor lapangan usaha. Jumlah UMK dan jumlah tenaga kerja UMK terdeteksi memiliki outlier secara multivariat. Ada perbedaan median yang signifikan antara jumlah UMK di Jawa Timur pada tahun 2012 dibandingkan dengan 2016. Clustering yang dilakukan menggunakan variabel perwakilan hasil analisis faktor baik pada jumlah UMK maupun jumlah tenaga kerja UMK memiliki nilai silhouette yang lebih tinggi daripada menggunakan semua variabel dan nilai silhouette yang dihasilkan oleh metode K-Medoids cenderung lebih tinggi daripada oleh K-Means. Secara umum, nilai silhouette hasil clustering data studi kasus tanpa outlier lebih tinggi daripada data yang memiliki outlier. Clustering terbaik pada jumlah UMK adalah dengan K-Medoids dan variabel sektor industri pengolahan, sektor real estat dan sektor kesenian, hiburan, dan rekreasi, cluster yang terbentuk sebanyak 4, dan terdapat perbedaan median jumlah UMK yang signifikan antar cluster pada sektor industri pengolahan dan sektor kesenian, hiburan, dan rekreasi. Clustering terbaik dari jumlah tenaga kerja UMK yaitu dengan K-Medoids dan variabel sektor industri pengolahan, sektor pengangkutan dan pergudangan, sektor aktvitas keuangan dan asuransi, dan sektor real estat, hasilnya cluster yang terbentuk sebanyak 2, dan ada perbedaan median jumlah tenaga kerja UMK yang signifikan antar cluster pada sektor industri pengolahan, sektor pengangkutan dan pergudangan, dan sektor aktivitas keuangan dan asuransi.
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Mapping the potential of MSEs in East Java can be done by conducting a clustering analysis of the number of MSEs and the number of MSEs labor based on the business filed. The number of MSEs and the number of MSEs labor were detected to have multivariate outliers. There is a significant median difference between the number of MSEs in East Java in 2012 compared to 2016. Clustering analysis using representative variables as a result of factor analysis both on the number of MSEs and the number of MSEs labor had a higher silhouette value than clustering using all variables and silhouette value produced by K-Medoids tends to be higher than by K-Means. Generally, clustering using data without outliers produced higher silhouette score than using data with outliers. The best clustering on the number of MSEs is with K-medoids and the used variables are manufacturing industry sector, the real estate sector and the arts, entertainment, and recreation sectors, there are 4 clusters formed, and there is a significant median difference in number of MSEs between clusters in the manufacturing industry sector and the arts, entertainment, and recreation sectors. The best clustering of the number of MSEs labor is with K-Medoids and used variables are manufacturing industry sector, the transportation and warehousing sector, the financial and insurance activity sector, and the real estate sector, there are 2 clusters formed, and there is a significant median difference in number of MSEs labor between clusters in the manufacturing industry sector, the transportation and warehousing sector, and the financial and insurance activity sector.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Cluster Data Outlier, Jumlah UMK, Jumlah Tenaga Kerja UMK, K-Means, K-Medoids, Data Outlier Cluster, Number of MSEs, Number of MSEs Labor |
| Subjects: | H Social Sciences > HA Statistics Q Science > QA Mathematics > QA278.55 Cluster analysis |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Diza Amalia |
| Date Deposited: | 02 Sep 2021 01:45 |
| Last Modified: | 31 Oct 2024 09:33 |
| URI: | http://repository.its.ac.id/id/eprint/91291 |
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