PENERAPAN ALGORITMA K-MEANS PADA SMA PROVINSI DKI JAKARTA UNTUK MENENTUKAN SEKOLAH TERBAIK BERDASARKAN NILAI UN

Authors

  • Muhammad Hasan Universitas Ibrahimy Author
  • Zaehol Fatah Universitas Ibrahimy Author

DOI:

https://doi.org/10.69714/bncwkr16

Keywords:

K-Means Algorithm, Best Schools, National Examination Scores, Classification, Clustering, Education, DKI Jakarta

Abstract

Education is an important aspect in human resource development in Indonesia. One indicator to measure the quality of education is the National Examination (UN) score. However, parents or students often have difficulty choosing the best school in DKI Jakarta Province because of the many choices available. This research aims to apply the K-Means algorithm to group high school schools in DKI Jakarta Province based on National Examination scores. By using the clustering method, it is hoped that groups of schools with the best achievements can be found, making it easier to select schools based on these criteria. In this research, the data used are high school National Examination scores in DKI Jakarta obtained from the Ministry of Education and Culture. The results of this research show that the K-Means algorithm can be effectively used to group schools based on National Examination scores, thereby providing a clearer picture for the public in determining quality schools.

References

N. sukmadinata Syaodih, “ILMU & APLIKASI PENDIDIKAN,” 2007, [Online]. Available: https://www.google.co.id/books/edition/Ilmu_dan_aplikasi_pendidikan/B8cfnF69lOEC?hl=id&gbpv=1&dq=pendidikan&pg=PA98&printsec=frontcover

A. M. Dama yanti S.Si ; Mira Juangsih,S. Si. Asep sukandar, Spd; Lingga kartini, “RINGKASAN MATERI & LATIHAN SOAL-SOAL UN SMP 2011,” 2010, [Online]. Available: https://www.google.co.id/books/edition/Ringkasan_Materi_Latihan_Soal_soal_UN_SM/4V5xBAAAQBAJ?hl=id&gbpv=1&dq=mengetahui+bagusnya+sekolah+dari+nilai+un&pg=PR3&printsec=frontcover

M.-Y.-A. M.-N. Ahmad-Dkk, “DATA MINING & Aplikasinya,” 2021, [Online]. Available: https://books.google.co.id/books?id=53FXEAAAQBAJ&newbks=0&printsec=frontcover&dq=data+mining&hl=id&source=newbks_fb&redir_esc=y#v=onepage&q=data mining&f=false

M. F. Edy Irawansyah, ADVANCED CLUSTERING Teori dan Aplikasi, 1st ed. 2015. [Online]. Available: https://www.google.co.id/books/edition/Advanced_Clustering/8y80BgAAQBAJ?hl=id&gbpv=1&dq=algoritma+k-means+clustering+adalah&printsec=frontcover

P. M. A. K-means, S. Nurani, Y. Syahra, and A. Calam, “Penerapan Data Mining Dalam Clustering Pencapaian Target,” vol. 2, pp. 355–363, 2023.

M. S. Deny Jollyta, Prihandoko, Alyauma Hajjah, Elin Haerani, ALGORITMA KLASIFIKASI UNTUK PEMULA. DEEPUBLISH DIGITAL, 2023. [Online]. Available: https://books.google.co.id/books?id=y84TEQAAQBAJ&newbks=0&printsec=frontcover&pg=PA138&dq=Rapidminer+bahasa+indonesia&hl=id&source=newbks_fb&redir_esc=y#v=onepage&q&f=true

ensiklopedia bebas Wikipedia bahasa Indonesia, “Ujian Nasional,” Wikipedia bahasa Indonesia, ensiklopedia bebas, 2024.

M. Faid, “Perbandingan Kinerja Tool Data Mining Weka dan Rapidminer Dalam Algoritma Klasifikasi,” vol. 8, 2019, doi: 10.34148/teknika.v8i1.95.

A. perdana windarto Kiki Fatmawati, “DATA MINING PENERAPAN RAPIDMINER DENGAN K-MEANS CLUSTER PADA DAERAH TERJANGKIT DEMAM BERDAARAH DENGUE (DBD) BERDASARKAN PROVINSI,” vol. 3, 2018.

Y. R. Sari et al., “PENERAPAN ALGORITMA K- MEANS UNTUK CLUSTERING DATA KEMISKINAN PROVINSI BANTEN MENGGUNAKAN RAPIDMINER,” vol. 5, no. 2, pp. 192–198, 2020.

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Published

2025-02-01

How to Cite

PENERAPAN ALGORITMA K-MEANS PADA SMA PROVINSI DKI JAKARTA UNTUK MENENTUKAN SEKOLAH TERBAIK BERDASARKAN NILAI UN (Muhammad Hasan & Zaehol Fatah , Trans.). (2025). Jurnal Ilmiah Multidisiplin Ilmu, 2(1), 89-95. https://doi.org/10.69714/bncwkr16