Penerapan Algoritma Fuzzy C-Means untuk Analisis Tingkat Pendidikan Sekolah Dasar di Karanganyar
Keywords:
Clustering, Fuzzy C-Means, Elementary School, RapidminerAbstract
The use of the Fuzzy C-Means (FCM) algorithm is an interesting topic in the analysis of elementary school education. Karanganyar is an area that has many elementary schools and we need a method that can classify data with high accuracy to understand elementary school data effectively. Therefore, this study aims to apply the FCM algorithm in data mining to analyze elementary schools in Karanganyar. The research began by collecting data on elementary schools in Karanganyar which included attributes such as the number of study groups and students. The FCM method is then used to process the data. The data clustering technique is enabled by this algorithm. Experimental findings indicate that the application of FCM algorithm in data mining to analyze an elementary school in Karanganyar produces information grouping. In rapidminer's calculations, 6 clusters were obtained, namely cluster 0 consisting of 45 elementary schools with the lowest educational level category, cluster 1 consisting of 3 elementary schools with the highest educational level category, cluster 2 consisting of 73 elementary schools with the lowest educational level category, cluster 3 consisting of 14 elementary schools with the higher education level category, cluster 4 consisting of 39 elementary schools with various levels of education categories, cluster 5 consisting of 27 elementary schools with the medium education level category. The DBI value acquired by the FCM method is -0.471, and since this number is near to 0, it can be argued that the cluster that the algorithm generated is excellent. This can help the government and the educational system. in formulating sensible development plans and policies. Karanganyar's educational system.
References
Kurniawan, S., Siregar, A. M., & Novita, H. Y. (2023). Penerapan Algoritma K-Means dan Fuzzy C-Means Dalam Mengelompokan Prestasi Siswa Berdasarkan Nilai Akademik. IV(1).
Wuni, S., Mutoi Siregar Universitas Buana Perjuangan Karawang Karawang, A., & Sulistya Kusumaningrum Universitas Buana Perjuangan Karawang Karawang, D. (2020). K-Means Clustering untuk Mengelompokan Tingkat Putus Sekolah Jenjang SMP di Indonesia. 1(1).
Primasari, I. F. N. D., Marini, A., & Sumantri, M. S. (2021). Analisis Kebijakan Dan Pengelolaan Pendidikan Terkait Standar Penilaian Di Sekolah Dasar. Jurnal Basicedu, 5(3), 1479–1491. https://doi.org/10.31004/basicedu.v5i3.956
Dewi, M. P., Marsyidin, S., & Sabandi, A. (2020). Analisis Kebijakan dan Pengelolaan Pendidikan Dasar terkait Standar Kompetensi Lulusan di Sekolah Dasar. EDUKATIF : JURNAL ILMU PENDIDIKAN, 2(2), 144–152. https://doi.org/10.31004/edukatif.v2i2.117
Dasriani, N. G. A., Mayadi, M., & Anggrawan, A. (2022). Klasterisasi Lokasi Promosi PMB Dengan Fuzzy C-means Masa Pandemi Covid 19. MATRIK : Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 21(2), 327–336. https://doi.org/10.30812/matrik.v21i2.1832
Hands-on data science with SQL server 2017. (n.d.). Packt. https://www.packtpub.com/product/hands-on-data-science-with-sql-server-2017/9781788996341
Zaidah, A. R., Septiarani, C. I., Nisa, S., Yusuf, A., & Wahyudi, N. (2021). KOMPARASI ALGORITMA K-MEANS, K-MEDOID, AGGLOMEARTIVE CLUSTERING TERHADAP GENRE SPOTIFY. 7(1). https://ejournal.fikom-unasman.ac.id
Rini Astuti, Achmad Nugroho, Yudhistira Arie Wijaya, & Santi Purwanti. (2022). ANALISIS DATA MINING MENGGUNAKAN ALGORITMA FUZZY C-MEANSPADA DATA TRANSAKSI PENGGUNAAN ARMADA DI PERUSAHAAN TRAVEL. Media Informatika, Vol.21.
Astuti, R., Rahaningsih, N., Hayati, U., Rohmat, C. L., & Suarna, N. (2023). Implementation of Fuzzy C-Means Algorithm with Optimized Parameter Grid for Clustering Electronic Product Sales. East Asian Journal of Multidisciplinary Research, 2(4), 1647–1660. https://doi.org/10.55927/eajmr.v2i4.3929
Arifien, F. (2020). PENGGUNAAN MODEL KLUSTERISASI DENGAN METODE K-MEANS UNTUK MENDETEKSI AKTIVITAS PENGGUNA WEB MENGGUNAKAN RAPIDMINER BERDASARKAN USER-AGENT-BASED STUDI KASUS PADA APLIKASI-APLIKASI PADA STMIK JAKARTA STI&K. Seminar Nasional Teknologi Informasi Dan Komunikasi STI&K (SeNTIK), 4(1).
