Analisis Pola Kinerja Anak dalam Tes Membaca untuk Mengidentifikasi Anak yang Membutuhkan Pendampingan Dini Menggunakan Algoritma K-Means Clustering di PAUD Seroja
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Sep 20, 2024
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This research aims to analyze children's performance patterns in reading tests in order to identify children who need early assistance at PAUD (Early Childhood Education) Seroja. Early identification is very important to provide timely assistance to children who have reading difficulties, so as to improve their reading abilities from an early age. In this research, the K-Means Clustering algorithm was used to group children based on their reading test results. The data used in this research consisted of reading test results taken from a number of children at PAUD Seroja. K-Means Clustering algorithm is applied to Cluster children into groups based on their performance. The results of this grouping are then analyzed to identify significant performance patterns and to identify children who need early assistance.
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Sarimole, F. M., & Septiansyah, M. A. (2024). Analisis Pola Kinerja Anak dalam Tes Membaca untuk Mengidentifikasi Anak yang Membutuhkan Pendampingan Dini Menggunakan Algoritma K-Means Clustering di PAUD Seroja. Jurnal Indonesia : Manajemen Informatika Dan Komunikasi, 5(3), 3054-3064. https://doi.org/10.35870/jimik.v5i3.1010
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References
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Anggraeni, D., Rizaldi, R., & Putra, G. M. (2021). Penerapan K-Means Clustering Untuk Pengelompokan Kelas Pada Taman Kanak-Kanak. Building of Informatics, Technology and Science (BITS), 3(3), 400-404. DOI: https://doi.org/10.47065/bits.v3i3.1125.
Bhatnagar, S., & Saxena, P. S. (2018). ANALYSIS OF FACULTY PERFORMANCE EVALUATION USING CLASSIFICATION. International Journal of Advanced Research in Computer Science, 9(1).
Hossain, M. Z., Akhtar, M. N., Ahmad, R. B., & Rahman, M. (2019). A dynamic K-means clustering for data mining. Indonesian Journal of Electrical engineering and computer science, 13(2), 521-526.
Messakh, G. C. (2023). COMPARISON K-MEANS AND FUZZY C-MEANS IN REGENCIES/CITIES GROUPING BASED ON EDUCATIONAL INDICATORS. Jurnal Varian, 7(1).
Nugraha, G. S., & Hairani, H. (2018). Aplikasi pemetaan kualitas pendidikan di Indonesia menggunakan metode k-means. MATRIK: Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, 17(2), 13-23. DOI: https://doi.org/10.30812/matrik.v17i2.84.
Pradnyana, G. A., & Permana, A. A. J. (2018). Sistem Pembagian Kelas Kuliah Mahasiswa Dengan Metode K-Means Dan K-Nearest Neighbors Untuk Meningkatkan Kualitas Pembelajaran. Jurnal Ilmiah Teknologi Informasi, 16(1), 59-68. DOI: http://dx.doi.org/10.12962/j24068535.v16i1.a696.
Priyatman, H., Sajid, F., & Haldivany, D. (2019). Klasterisasi Menggunakan Algoritma K-Means Clustering untuk Memprediksi Waktu Kelulusan Mahasiswa. Jurnal Edukasi Dan Penelitian Informatika (JEPIN), 5(1), 62.
Qoiriah, A., Harimurti, R., & Nurhidayat, A. I. (2020, November). Application of k-means algorithm for clustering student’s computer programming performance in automatic programming assessment tool. In International Joint Conference on Science and Engineering (IJCSE 2020) (pp. 421-425). Atlantis Press. DOI: https://doi.org/10.2991/aer.k.201124.075.
Rauthan, A., Singh, A. S., & Singh, N. (2021, December). Impact on higher education in pandemic: analysis k-means clustering using urban & rural areas. In 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) (pp. 1974-1980). IEEE. DOI: https://doi.org/10.1109/ICAC3N53548.2021.9725709.
Rizki, M. Y., Maysaroh, S., & Windarto, A. P. (2021). Implementasi K-Means Clushtering dalam Mengelompokkan Minat Membaca Penduduk Menurut Wilayah. Just IT: Jurnal Sistem Informasi, Teknologi Informasi dan Komputer, 11(2), 41-49. DOI: https://doi.org/10.24853/justit.11.2.41-49.
Setyaningtyas, S., Nugroho, B. I., & Arif, Z. (2022). TINJAUAN PUSTAKA SISTEMATIS PADA DATA MINING: STUDI KASUS ALGORITMA K-MEANS CLUSTERING. J Teknoif Teknik Informatika, 10, 52-61.
Situmorang, A., Arifin, A., Rusilpan, I., & Juliane, C. (2022). Analisa dan Penerapan Metode Algoritma K-Means Clustering Untuk Mengidentifikasi Rekomendasi Kategori Baru Pada List Movie IMDb. JURNAL MEDIA INFORMATIKA BUDIDARMA, 6(4), 2171-2179. DOI: http://dx.doi.org/10.30865/mib.v6i4.4729.
Stephen, K. W. (2016). Data Mining Model for Predicting Student Enrolment in STEM Courses in Higher Education Institutions.
Zahroh, L. F. A., Rahaningsih, N., & Dana, R. D. (2024). KLASTERISASI DATA KEGEMARAN MEMBACA MENGGUNAKAN ALGORITMA K-MEANS DI SMA AL-ISLAM CIREBON. JATI (Jurnal Mahasiswa Teknik Informatika), 8(3), 2692-2698. DOI: https://doi.org/10.36040/jati.v8i3.9543.