Pengelompokan Kabupaten/Kota di Provinsi Jawa Barat Berdasarkan Indikator Pembangunan Ekonomi Menggunakan Fuzzy C-Means

Khoirunnisa, Nasywa (2024) Pengelompokan Kabupaten/Kota di Provinsi Jawa Barat Berdasarkan Indikator Pembangunan Ekonomi Menggunakan Fuzzy C-Means. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pembangunan ekonomi daerah dapat menggambarkan pertumbuhan ekonomi, kesejahteraan masyarakat serta taraf hidup masyarakat pada wilayah tersebut. Keberhasilan pembangunan ekonomi daerah dapat diukur menggunakan indikator pembangunan ekonomi yang terbagi menjadi tiga indikator, yaitu indikator moneter, indikator nonmoneter, serta indikator campuran. Pertumbuhan ekonomi Provinsi Jawa Barat tahun 2022 menunjukkan kinerja positif dan tumbuh naik sebesar 5,45% dibandingkan nasional. Namun masih terdapat ketimpangan pendapatan yang dapat memengaruhi ekonomi di Provinsi Jawa Barat. Ketimpangan pendapatan di Provinsi Jawa Barat masih cukup tinggi berdasarkan nilai gini rasio. Secara nasional, nilai gini rasio Indonesia pada tahun 2022 sebesar 0,381, sedangkan Provinsi Jawa Barat memiliki nilai gini rasio diatas nasional, yaitu 0,412. Berdasarkan hal tersebut, pembangunan ekonomi Provinsi Jawa Barat belum dapat dikatakan begitu baik, karena secara teori terjadinya pertumbuhan ekonomi diiringi dengan berkurangnya ketimpangan pendapatan. Namun kenyataannya pada tahun 2022 pertumbuhan ekonomi Provinsi Jawa Barat meningkat, begitupun dengan meningkatnya ketimpangan pendapatan. Dengan adanya ketimpangan tersebut dapat menimbulkan permasalahan dalam hubungan antar daerah, maka dilakukan pengelompokan kabupaten/kota di Provinsi Jawa Barat berdasarkan indikator pembangunan ekonomi menggunakan Fuzzy C-Means yang berguna menjadi salah satu upaya memacu pembangunan ekonomi di Provinsi Jawa Barat dengan mengoptimalkan indikator pembangunan ekonomi di masing-masing kabupaten/kota Provinsi Jawa Barat. Hasil analisis didapatkan kesimpulan bahwa pengelompokkan menggunakan fungsi keanggotaan linear naik dengan jumlah kelompok sebanyak 7 kelompok merupakan metode terbaik dalam melakukan pengelompokan pembangunan ekonomi di Provinsi Jawa Barat tahun 2022.

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The regional economic development can illustrate economic growth, community welfare, and the standard of living in that region. The success of regional economic development can be measured using economic development indicators, which are divided into three categories: monetary indicators, non-monetary indicators, and mixed indicators. The economic growth of West Java Province in 2022 showed a positive performance, increasing by 5.45% compared to the national level. However, there is still income inequality that can affect the economy in West Java Province. Income inequality in West Java Province remains relatively high based on the Gini ratio value. Nationally, Indonesia's Gini ratio in 2022 was 0.381, while West Java Province had a Gini ratio above the national level, at 0.412. Based on this, the economic development of West Java Province cannot be considered very good, because theoretically, economic growth should be accompanied by reduced income inequality. However, in reality, in 2022, the economic growth of West Java Province increased, as did income inequality. This inequality can lead to problems in inter-regional relationships, thus, a clustering of districts/cities in West Java Province based on economic development indicators was carried out using Fuzzy C-Means. This approach is useful as an effort to stimulate economic development in West Java Province by optimizing the economic development indicators in each district/city within the province. The analysis results concluded that the clustering using a linear increasing membership function with a total of 7 clusters was the best method for clustering economic development in West Java Province in 2022.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Fuzzy C-Means, Indikator Pembangunan Ekonomi, Pembangunan Ekonomi Daerah, Economic Development Indicators, Fuzzy C-Means, Regional Economic Development
Subjects:	H Social Sciences > HB Economic Theory Q Science > QA Mathematics > QA248_Fuzzy Sets Q Science > QA Mathematics > QA278 Cluster Analysis. Multivariate analysis. Correspondence analysis (Statistics)
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User:	Nasywa Khoirunnisa
Date Deposited:	08 Aug 2024 07:22
Last Modified:	08 Aug 2024 07:22
URI:	http://repository.its.ac.id/id/eprint/114911

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