Putri, Kariina Rizka (2019) Pengelompokan Kabupaten/Kota di Provinsi Jawa Barat Berdasarkan Indikator Tingkat Pengangguran Terbuka Menggunakan Fuzzy C-Means Cluster. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Masalah pengangguran masih menjadi salah satu titik berat dalam pembangunan di Jawa Barat. Tingkat Pengangguran Terbuka (TPT) merupakan salah satu indikasi dalam mengukur kesejahteraan masyarakat di suatu wilayah. Angka TPT Jawa Barat pada tahun 2017 mengalami penurunan, namun angka tersebut belum memenuhi target capaian kinerja pemerintah Provinsi Jawa Barat. Menurut Rencana Pembangunan Jangka Menengah Daerah (RPJMD) Provinsi Jawa Barat tahun 2013-2018. Berdasarkan hal tersebut maka penelitian ini bertujuan mengelompokkan Kabupaten/Kota berdasarkan indikator TPT di Provinsi Jawa Barat agar dapat diberikan solusi penurunan TPT secara merata akan lebih terarah. Metode yang digunakan yaitu fuzzy c-means cluster dimana analisis yang dilakukan dengan membandingkan metode fuzzy c-means cluster tanpa analisis faktor serta metode fuzzy c-means cluster dengan analisis faktor. Hasil penelitian menunjukkan bahwa metode terbaik yang digunakan yaitu FCM dengan analisis faktor dimana menghasilkan cluster optimum sebanyak 4 dengan fungsi keanggotaan linier naik. Perlu adanya perbaikan atau penanganan khusus pada Cluster 1 dimana memiliki 9 Kabupaten/Kota atau sekitar 33% dari Provinsi Jawa Barat yang masih digolongkan tingkat pengangguran tinggi.
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The problem of unemployment is still one of the main focus of development in West Java. The open unemployment rate (TPT) is one of indication in measuring the welfare of the people in a region. The West Java TPT rate in 2017 has decreased, but this number has not met the target of the performance of the government of West Java Province. According to the Regional Medium-Term Development Plan (RPJMD) of West Java Province 2013-2018. Based on this matter, this study aims to classify regencies / cities based on TPT indicators in West Java Province so that solutions can be given to reduce TPT evenly and will be more directed. The method used is fuzzy c-means cluster where the analysis is done by comparing fuzzy c-means cluster method without factor analysis and fuzzy c-means cluster method with factor analysis. The results showed that the best method used was FCM with factor analysis which resulted in optimum clusters of 4 with up linear membership functions. There needs to be special improvement or handling in Cluster 1 where there are 9 regencies / cities or around 33% of West Java provinces which are still classified as high unemployment rates.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSSt 519.535 Put k-1 2019 |
| Uncontrolled Keywords: | Analisis Faktor, Fuzzy C-Means Cluster, Tingkat Pengangguran Terbuka. |
| Subjects: | H Social Sciences > HA Statistics H Social Sciences > HA Statistics > HA29 Theory and method of social science statistics H Social Sciences > HA Statistics > HA31.35 Analysis of variance H Social Sciences > HN Social history and conditions. Social problems. Social reform |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Kariina Rizka Putri |
| Date Deposited: | 14 Mar 2024 07:24 |
| Last Modified: | 14 Mar 2024 07:24 |
| URI: | http://repository.its.ac.id/id/eprint/64237 |
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