Clustering Data Calon Siswa Baru Menggunakan Metode K-Means di Pusat Pengembangan Anak Fajar Baru Cengkareng
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Abstract
Clustering is the process of partitioning a set of data objects into subsets known as clusters. K-means is an unsupervised learning algorithm, K-Means also has a function to group data into data clusters. The K-Means algorithm method was chosen because it has a fairly high accuracy of object size, so this algorithm is relatively more scalable and more efficient for processing large numbers of objects. In the world of education, in general, every new school year there will be something called registration of new prospective students, at the Fajar Baru Child Development Center, many prospective students are accepted from 3 years to 5 years old, therefore the authors hope that by using clustering data can easily group data so that it can make it easier to find the necessary data. By using the K-means algorithm method and using the RapidMiner application, it found 80% efficient results in grouping data.
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References
Nasir, J., 2020. Penerapan Data Mining Clustering Dalam Mengelompokan Buku Dengan Metode K-Means. Jurnal Simetris, 11(2), pp.1-13.
Purnamaningsih, C., 2013. Pemanfaatan Metode K-Means Clustering dalam Penentuan Penjurusan Siswa SMA. UPT Perpustakaan Universitas Sebelas Maret.
Damanik, Y.F.S.Y., Sumarno, S., Gunawan, I., Hartama, D. and Kirana, I.O., 2021. Penerapan Data Mining Untuk Pengelompokan Penyebaran Covid-19 Di Sumatera Utara Menggunakan Algoritma K-Means. Jurnal Ilmu Komputer Dan Informatika, 1(2). DOI: https://doi.org/10.54082/jiki.13.
Damanik, N. and Sigiro, M., 2021. Penerapan data mining menggunakan algoritma K-Means clustering pada penerimaan mahasiswa baru sebagai metode promosi. J. Tek. Inform. Komput. Univers, 4(2), p.158.
Rohmah, A., Sembiring, F. and Erfina, A., 2021, September. Implementasi Algoritma K-Means Clustering Analysis Untuk Menentukan Hambatan Pembelajaran Daring (Studi Kasus: Smk Yaspim Gegerbitung). In Prosiding Seminar Nasional Sistem Informasi dan Manajemen Informatika Universitas Nusa Putra (Vol. 1, No. 01, pp. 290-298).
Febrivani, E. and Winanjaya, R., 2021. Penerapan Data Mining Asosiasi Pada Persediaan Obat. Jurnal Ilmu Komputer Dan Sistem Informasi (JIKOMSI), 4(1), pp.23-35. DOI: https://doi.org/10.9767/jikomsi.v4i1.141.
Suryadi, S., 2018. Penerapan Metode Clustering K-Means Untuk Pengelompokan Kelulusan Mahasiswa Berbasis Kompetensi. INFORMATIKA, 6(1), pp.52-72. DOI: https://doi.org/10.36987/informatika.v6i1.738.
Nabila, Z., Isnain, A.R., Permata, P. and Abidin, Z., 2021. Analisis data mining untuk clustering kasus covid-19 di Provinsi Lampung dengan algoritma k-means. Jurnal Teknologi Dan Sistem Informasi, 2(2), pp.100-108. DOI: https://doi.org/10.33365/jtsi.v2i2.868.
Prastiwi, H., Pricilia, J. and Rasywir, E., 2022. Implementasi Data Mining Untuk Menentuksn Persediaan Stok Barang Di Mini Market Menggunakan Metode K-Means Clustering. Jurnal Informatika Dan Rekayasa Komputer (JAKAKOM), 2(1), pp.141-148. DOI: https://doi.org/10.33998/jakakom.2022.2.1.34.
Aulia, S., 2020. Klasterisasi Pola Penjualan Pestisida Menggunakan Metode K-Means Clustering (Studi Kasus Di Toko Juanda Tani Kecamatan Hutabayu Raja). Djtechno: Jurnal Teknologi Informasi, 1(1), pp.1-5. DOI: https://doi.org/10.46576/djtechno.v1i1.964.
Sembiring, C.S.D.B., Hanum, L. and Tamba, S.P., 2022. Penerapan Data Mining Menggunakan Algoritma K-Means Untuk Menentukan Judul Skripsi Dan Jurnal Penelitian (Studi Kasus Ftik Unpri). Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM PRIMA), 5(2), pp.80-85. DOI: https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2393.
Handoko, S., Fauziah, F. and Handayani, E.T.E., 2020. Implementasi Data Mining Untuk Menentukan Tingkat Penjualan Paket Data Telkomsel Menggunakan Metode K-Means Clustering. Jurnal Ilmiah Teknologi dan Rekayasa, 25(1), pp.76-88. DOI: http://dx.doi.org/10.35760/tr.2020.v25i1.2677.
Asmana, A., Wijaya, Y.A. and Martanto, M., 2022. Clustering Data Calon Siswa Baru Menggunakan Metode K-Means Di Sekolah Menengah Kejuruan Wahidin Kota Cirebon. JATI (Jurnal Mahasiswa Teknik Informatika), 6(2), pp.552-559. DOI: https://doi.org/10.36040/jati.v6i2.5236.
Ningrat, D.R., Di Asih, I.M. and Wuryandari, T., 2016. Analisis cluster dengan algoritma K-Means dan Fuzzy C-Means clustering untuk pengelompokan data obligasi korporasi. Jurnal Gaussian, 5(4), pp.641-650. DOI: https://doi.org/10.14710/j.gauss.5.4.641-650.
Priyatman, H., Sajid, F. and Haldivany, D., 2019. Klasterisasi Menggunakan Algoritma K-Means Clustering untuk Memprediksi Waktu Kelulusan Mahasiswa. Jurnal Edukasi Dan Penelitian Informatika (JEPIN), 5(1), p.62.
Intel., 2023. Meningkatkan Intelijen Bisnis dengan Analisis Dalam Memori. URL: https://www.intel.co.id/content/www/id/id/artificial-intelligence/in-memory-analytics.html. Diakses Tanggal 18 Juni 2023.
Yulianti, Y., Utami, D.Y., Hikmah, N. and Hasan, F.N., 2019. Penerapan Data Mining Menggunakan Algoritma K-Means Untuk Mengetahui Minat Customer Di Toko Hijab. Jurnal Pilar Nusa Mandiri, 15(2), pp.241-246. DOI: https://doi.org/10.33480/pilar.v15i2.650.
Chiang, H.D., Xu, T.S., Lv, X.L. and Dong, N., 2022. Hierarchical Trust-Tech-Enhanced K-Means Methods and Their Applications to Power Grids. IEEE Open Access Journal of Power and Energy, 9, pp.560-572. DOI: https://doi.org/10.1109/OAJPE.2022.3230385.
Purnama, J.J. and Rahayu, S., 2022. Klasifikasi konsumsi energi industri baja menggunakan teknik data mining. Jurnal Teknoinfo, 16(2), pp.395-407. DOI: https://doi.org/10.33365/jti.v16i2.1984.
Tamba, S.P., 2022. Penerapan Data Mining Algoritma Apriori Dalam Menentukan Stok Bahan Baku Pada Restoran Nelayan Menggunakan Metode Association Rule. Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM PRIMA), 5(2), pp.97-102. DOI: https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2407.