PENGELOMPOKAN PROVINSI DI INDONESIA \ BERDASARKAN INDIKATOR PEMBANGUNAN PENDIDIKAN MENGGUNAKAN METODE SUBTRACTIVE FUZZY C-MEANS
DOI:
https://doi.org/10.25077/jmua.11.3.181-189.2022Abstract
Pendidikan menjadi salah satu tujuan utama dalam rencana pembangunan di Indonesia. Pembangunan pendidikan diukur dengan indikator-indikator terkait pendidikan. Ketercapaian pembangunan pendidikan setiap provinsi di Indonesia berbeda sehingga dengan cara mengelompokkan provinsi- provinsi tersebut berdasarkan kemiripan indikator yang tercapai dapat memudahkan pemerintah memberikan program peningkatan pembangunan pendidikan. Indikator pembangunan pendidikan yang digunakan dalam pengelompokan adalah sarana dan prasarana pendidikan, sanitasi sekolah, partisipasi sekolah, dan angka putus sekolah. Metode yang digunakan adalah metode Subtractive Fuzzy C-Means. Pengolahan data mengambil jari-jari yang beragam yaitu 1.00, 1.10, 1.20, 1.30, dan 1.50. Hasil indeks validitas klaster menunjukkan jari-jari 1.50 yang membentuk 2 klaster merupakan jumlah klaster terbaik. Jumlah keanggotaan klaster pertama sebanyak 20 provinsi. Provinsi-provinsi yang menjadi keanggotaannya tersebar di seluruh indonesia bagian barat kecuali Aceh. Kemudian sebahagian provinsi di Indonesia bagian tengah yaitu Pulau Kalimantan kecuali Kalimantan Tengah, Gorontalo pada Pulau Sulawesi dan Bali. Sedangkan jumlah provinsi yang masuk keanggotaan klaster kedua sebanyak 14 provinsi. Keanggotaannya tersebar pada provinsi-provinsi selain yang menjadi anggota klaster pertama. Berdasarkan karakteristik klaster, klaster kedua merupakan klaster terbaik dibanding klaster pertama.
KataKunci : Pembangunan Pendidikan, Pengelompokan, Subtractive Fuzzy C-Means
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References
Azizah, N., D.Yuniarti., R.Goejantoro. 2018. Penerapan metode Fuzzy Subtractive Clustering (studi kasus: pengelompokan kecamatan di Provinsi Kalimantan Timur berdasarkan luas daerah dan jumlah penduduk tahun 2015. Jurnal Ekponensial. Vol 9:2: 197-206.
Johnson,R.A., Wichern,D.E. 2007. Applied Multivariate Statistical Analysis. Prentice Hall, New Jersey.
Klir,G.J., Folger T.A. 1988. Fuzzy Set, Uncertainty and Information. Prentice Hall, New Jersey.
Kurniawan, R., B.N Haqiqi. 2015. Pengelompokan menggunakan metode Subtractive Fuzzy C-Means (SFCM), studi kasus : demam berdarah di Jawa Timur. Jurnal Statistika. Vol 3:2: 22-30.
Kusumadewi, S., Purnomo, H. 2004. Logika Fuzzy Untuk pendukung keputusan Jilid 2. Graha Ilmu, Jakarta.
Pal,N.R dan Bezdek.J.C. 1995. On Cluster Validity for the fuzzy c-means model. IEEE Transactions On Fuzzy Systems. Vol 3:3: 370-379.
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