Analysis of School Grouping Against Educational Teachers in NTB Using K-Prototypes Method
DOI:
https://doi.org/10.51519/journalisi.v4i4.378Keywords:
Clustering K-Prototypes, School Grouping, Educational TeachersAbstract
The shortage of teaching staff is still a problem in education in Indonesia, resulting in the number of teachers and students being unbalanced. It is very significant based on data from the Analysis of the Distribution of Teachers in Region 3T, which shows that the national ratio of teachers per school is 18.41, and many still have a ratio of teachers per school lower than the national. Therefore, it is necessary to group the data in one of the 3T regions, especially in the Province of West Nusa Tenggara (NTB). The data used for this study were 4997 schools from 8 districts and two cities. The results of this study were conducted to determine whether the grouping ratio of the number of teachers and students is ideal or not ideal. The data used are categorical and numeric data types, so the clustering analysis method used is K-Prototypes. Each cluster produces a different range of teachers and students. Cluster 1, which obtained the High category almost followed the ideal, while Cluster 2 and the Cluster 3 were still far from ideal. This needs to be considered to increase the number of teaching staff in the Education Office in each district.
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References
M. Minsih, R. Rusnilawati, and I. Mujahid, “Kepemimpinan Kepala Sekolah Dalam Membangun Sekolah Berkualitas Di Sekolah Dasar,” Profesi Pendidikan Dasar, vol. 1, no. 1, pp. 29–40, Jul. 2019, doi: 10.23917/ppd.v1i1.8467.
Presiden Republik Indonesia, “Undang-Undang Republik Indonesia Nomor 20 Tahun 2003 Tentang Sistem Pendidikan Nasional.”
P. Data dan Statistik Pendidikan dan Kebudayaan, “Sistem Verifikasi dan Validasi Proses Pembelajaran,” https://vervalsp.data.kemdikbud.go.id/vervalpp/formula.php
P. Pembangunan, D. Tertinggal, P. Menetapkan, P. Presiden, and P. Daerah, “Dengan Rahmat Tuhan Yang Maha Esa Presiden Republik Indonesia, bahwa untuk melaksanakan ketentuan Pasal 6 ayat (3) Peraturan Pemerintah Nomor 78 Tahun 2OL4 tentang.”
Tim Penyusun Direktorat Sekolah Dasar, Direktorat Sekolah Dasar Pendidikan Bagi Anak di Daerah 3T SERI 4, vol. Cetakan 1, 2021. 2021.
K. Pendidikan dan Kebudayaan and P. Data dan Statistik Pendidikan dan Kebudayaan, “Analisis Sebaran Guru Dikdasmen Di Wilayah 3 T,” 2016.
M. Nishom and D. S. Wibowo, “Implementasi Metode K-Means berbasis Chi-Square pada Sistem Pendukung Keputusan untuk Identifikasi Disparitas Kebutuhan Guru,” Jurnal Sistem Informasi Bisnis, vol. 8, no. 2, p. 187, Nov. 2018, doi: 10.21456/vol8iss2pp187-194.
H. Prasetyo, B. Pusat, S. Provinsi, and J. Tengah, “Pengelompokan Wilayah Menurut Potensi Fasilitas Kesehatan Dan Kejadian Covid-19 Menggunakan Algoritma Fuzzy K-Prototypes,” 2021.
P. P. Putra, I. Bagus, K. Widiartha, and A. Zubaidi, “Rancang Bangun Sistem Informasi Geografis Capaian Pendidikan Formal Sebagai Alat Pendukung Kebijakan Dinas Pendidikan dan Kebudayaan Provinsi NTB.”
P. D. dan P. M. D. Jenderal Pendidikan Anak Usia Dini, “Data Pokok Pendidikan,” https://dapo.kemdikbud.go.id/sp, May 2022.
B. G. Sudarsono, M. I. Leo, A. Santoso, and F. Hendrawan, “Analisis Data Mining Data Netflix Menggunakan Aplikasi Rapid Miner,” JBASE - Journal of Business and Audit Information Systems, vol. 4, no. 1, Apr. 2021, doi: 10.30813/jbase.v4i1.2729.
P.-N. Tan, M. Steinbach, and V. Kumar, “Introduction to Data Mining Instructor’s Solution Manual.”
Z. Huang, “Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values,” 1998.
A. S. Sulthoni, R. Andreswari, and F. Hamami, “segmentasi pelanggan pt. Telekomunikasi seluler indonesia menggunakan clustering algoritma k-prototypes dan metode elbow sebagai perumusan strategi marketing customer segmentation pt. Telekomunikasi seluler indonesia uses clustering k-prototypes algorithm and elbow method for formulating marketing strategy.”
S. Sulastri, L. Usman, and U. D. Syafitri, “K-prototypes Algorithm for Clustering Schools Based on The Student Admission Data in IPB University,” Indonesian Journal of Statistics and Its Applications, vol. 5, no. 2, pp. 228–242, Jun. 2021, doi: 10.29244/ijsa.v5i2p228-242.
N. Putu, E. Merliana, and A. J. Santoso, Analisa Penentuan Jumlah Cluster Terbaik Pada Metode K-Means Clustering.
Y. Aprilia, P. Kartikasari, Y. A. Pranoto, and D. Rudhistiar, “Penerapan Metode K-Modes Untuk Proses Penentuan Penerima Bantuan Langsung Tunai (BLT),” 2021.
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