Pemetaan dan Klasterisasi Sekolah Muhammadiyah di Kabupaten PPU Berdasarkan Fasilitas, Pendidik dan Tenaga Pendidik Menggunakan Metode K-Means Clustering
DOI:
https://doi.org/10.35891/explorit.v14i2.3425Keywords:
Mapping, Clustering, MuhammadiyahAbstract
Educational facilities are a part of achieving learning in schools. Facilities that are generally located in schools are classrooms, libraries and toilets which are intended for teachers/educators and students. With the facilities, teachers, and teaching staff are very important to support teaching and learning activities. To make it easier for the government and Muhammadiyah schools to cluster certain schools into several clusters, making it easier to assist and procure school needs within the North Penajam Paser Regency government. Clustering is done by using the K-Means algorithm. The application of the K-Means Algorithm by determining the Cluster value is 3. The results show that each Cluster has its own number of members. Cluster 0 consists of 5 schools, Cluster 1 consists of 8 schools, and Cluster 2 consists of 1 school. Then the results of the increase sequentially obtained Cluster 0, Cluster 2, and finally Cluster 1. Furthermore, in testing the performance of the K-Means algorithm by dividing 3 clusters, the Davies Bouldin Index value of 0.446 was obtained. From the results of data analysis and processing, there are 8 schools in the low cluster, so this study recommends the need for assistance and provision of school needs for the low cluster by the education office of the North Penajam Paser Regency.
Downloads
References
Setiawan, F.Setiawan (2021) Muhammadiyah mencerdaskan bangsa. Yogyakarta, UAS PRESS.
Badan Pusat Statistik (2021). BPS: 270,20 juta Penduduk Indonesia Hasil SP2020. Badan Pusat Statistik. https://www.bps.go.id/news/2021/01/21/405/bps--270-20-juta-penduduk-indonesia-hasil-sp2020.html
HM, M. A. (2020). Peran Guru dalam Pengembangan Pembelajaran. el-Idarah: Jurnal Manajemen Pendidikan Islam, 5(1), 44-59.
Agushinta, D., & Murniyati, M. (2022). Penerapan Algoritma K-Means Clustering Pada Data Keluhan Pelanggan PT. PLN (Persero). Journal of Information System, Applied, Management, Accounting and Research, 6(2), 327- 340.
Rahmawati, L., Widya Sihwi, S., & Suryani, E. (2016). Analisa Clustering Menggunakan Metode K-Means Dan Hierarchical Clustering (Studi Kasus : Dokumen Skripsi Jurusan Kimia, Fmipa, Universitas Sebelas Maret). Jurnal Teknologi & Informasi IT Smart, 3(2), 66. https://doi.org/10.20961/its.v3i2.654
Suyanto, 2017, Data Mining Untuk Klasifikasi dan Klasterisasi Data. Bandung: Informatika.
Fatmawati, K., & Windarto, A. P. (2018). Data Mining: Penerapan Rapidminer Dengan K-Means Cluster Pada Daerah Terjangkit Demam Berdarah Dengue (Dbd) Berdasarkan Provinsi. Computer Engineering, Science And System Journal, 3(2), 173.
Nurahman, N., Purwanto, A., & Mulyanto, S. (2022). Klasterisasi Sekolah Menggunakan Algoritma K-Means berdasarkan Fasilitas, Pendidik, dan Tenaga Pendidik. MATRIK : Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 21(2), 337–350. https://doi.org/10.30812/matrik.v21i2.1411
Sibuea, F. L., & Sapta, A. (2017). Pemetaan Siswa Berprestasi Menggunakan Metode K-Means Clustering. Jurnal Teknologi Dan Sistem Informasi, 1, 10.
M. L. Sibuea and A. Safta, “Pemetaan Siswa Berprestasi Menggunakan Metode K- Means Clustring,†JURTEKSI (Jurnal Teknologi dan Sistem Informasi), vol. 4, no. 1, 2017.
Hakim, L., & Prayoga, R. H. (2017). PENGENALAN IRIS MATA METODE TIGA KELAS DENGAN ADAPTIVE K-MEANS CLUSTERING. Explore IT! : Jurnal Keilmuan Dan Aplikasi Teknik Informatika, 9(2). https://doi.org/10.35891/explorit.v9i2.791
Rhind, D. (1988). A GIS research agenda. 2.
Budiyanto, E. (2016). Sistem informasi geografis dengan Quantum GIS.
S. Oktarian, S. Defit, and Sumijan, “Klasterisasi Penentuan Minat Siswa dalam Pemilihan Sekolah Menggunakan Metode Algoritma K-Means Clustering,†Jurnal Informasi dan Teknologi, vol. 2, no. 3, pp. 68–73, 2020.
Hamzah, R., Marpaung, S., & Prayogo, T. (2017). Metode Penentuan Titik Koordinat Zona Potensi Penangkapan Ikan Pelagis Berdasarkan Hasil Deteksi Termal Front Suhu Permukaan Laut. Jurnal Penginderaan Jauh Dan Pengolahan Data Citra Digital, 13(2). https://doi.org/10.30536/j.pjpdcd.2016.v13.a2364
Dimas, D., Nurjayadi, N., & Haryono, D. (2019). Penerapan Augmented Reality Pada Informasi Data Peta Kawasan Hutan Lindung Menggunakan Metode Marker. SATIN - Sains Dan Teknologi Informasi, 4(2), 100.
Rahmawati, L., Widya Sihwi, S., & Suryani, E. (2016). Analisa Clustering Menggunakan Metode K-Means Dan Hierarchical Clustering (Studi Kasus : Dokumen Skripsi Jurusan Kimia, Fmipa, Universitas Sebelas Maret). Jurnal Teknologi & Informasi IT Smart, 3(2), 66. https://doi.org/10.20961/its.v3i2.654
Downloads
Published
Issue
Section
License

Jelajahi IT! dilisensikan di bawah Lisensi Internasional Creative Commons Attribution 4.0 .






