Estimasi Nilai Akhir Mata Pelajaran Komputer dan Jaringan Dasar Menggunakan Algoritma Linear Regression Berganda
DOI:
https://doi.org/10.22441/format.2023.v12.i2.001Keywords:
Mining, Estimate, Linear RegressionAbstract
Abstract - Vocational High School or SMK is a secondary level of education taken after completing from junior high school/equivalent. SMK plays a significant part in the preparation of human resources. The final grades of the students are difficult for teachers to predict. This estimated final grade is necessary for the teacher to evaluate the quality of the instruction given. In order to ascertain the association between the variable daily average values and competency scores on the final grades in Computer and Basic Networks subjects, a data mining strategy was utilized in conjunction with the estimate method utilizing the multiple linear regression algorithm. The data used is value data for one semester with a total of 134. In order to increase the quality of learning in the event that the grade does not satisfy the completeness requirements, it is anticipated that the Multiple Linear Regression algorithm will be able to estimate the final grades that are likely to be achieved. To determine the scope of the fault discovered, the RMSE (Root Mean Squared Error) is utilized.
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P. Bidang Komputer Sains dan Pendidikan Informatika, D. Akademi Perekam dan Informasi Kesehatan Iris Padang Jl Gajah Mada No, and S. Barat, “Jurnal Edik Informatika Data Mining : Klasifikasi Menggunakan Algoritma C4.5 Yuli Mardi”.
A. P. Windarto, U. Indriani, M. R. Raharjo, and L. S. Dewi, “Bagian 1: Kombinasi Metode Klastering dan Klasifikasi (Kasus Pandemi Covid-19 di Indonesia),” JURNAL MEDIA INFORMATIKA BUDIDARMA, vol. 4, no. 3, p. 855, Jul. 2020, doi: 10.30865/mib.v4i3.2312.
F. O. Lusiana, I. Fatma, and A. P. Windarto, “Estimasi Laju Pertumbuhan Penduduk Menggunakan Metode Regresi Linier Berganda Pada BPS Simalungun,” 2021. [Online]. Available: https://hostjournals.com/
I. D. P. Nasional, “Kamus Besar Bahasa Indonesia: Pusat Bahasa,” 2008.
R. Gunawan, N. B. Nugroho, and R. Arbianto, “Penerapan Data Mining Untuk Estimasi Laju Pertumbuhan Produk Domestik Regional Bruto (PDRB) Perkapita Atas Dasar Harga Berlaku Menurut Lapangan Usaha Pada Kota Medan Menggunakan Metode Regresi Linier Barganda,” Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD, vol. 1, no. 2, pp. 106–113, 2018.
A. Fikri, “Penerapan Data Mining Untuk Mengetahui Tingkat Kekuatan Beton Yang Dihasilkan Dengan Metode Estimasi Menggunakan Linear Regression,” Universitas Dian Nuswantoro, Semarang, 2013.
A. Amrin, “Data Mining Dengan Regresi Linier Berganda Untuk Peramalan Tingkat Inflasi,” Techno Nusa Mandiri: Journal of Computing and Information Technology, vol. 13, no. 1, pp. 74–79, 2016.
D. H. Kamagi and S. Hansun, “Implementasi Data Mining dengan Algoritma C4. 5 untuk Memprediksi Tingkat Kelulusan Mahasiswa,” Ultimatics: Jurnal Teknik Informatika, vol. 6, no. 1, pp. 15–20, 2014.
M. Tranmer, J. Murphy, M. Elliot, and M. Pampaka, “Multiple Linear Regression (2 nd Edition),” 2020. [Online]. Available: https://hummedia.manchester.ac.uk/institutes/cmist/a
E. I. A. Warih and Y. Rahayu, “Penerapan Data Mining Untuk Menentukan Estimasi Produktivitas Tanaman Tebu Dengan Menggunakan Algoritma Linier Regresi Berganda Di Kabupaten Rembang,” Teknik Informatika, Fakultas Ilmu Komputer, Universitas Dian Nuswantoro, Semarang, 2015.
A. Z. Siregar, “Implementasi Metode Regresi Linier Berganda Dalam Estimasi Tingkat Pendaftaran Mahasiswa Baru,” Kesatria: Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen), vol. 2, no. 3, pp. 133–137, 2021.
L. Wiranda, M. Sadikin, J. T. Informatika, and F. I. Komputer, “Penerapan Long Short Term Memory Pada Data Time Series Untuk Memprediksi Penjualan Produk PT,” Metiska Farma. Jurusan Teknik Informatika, Fakultas Ilmu Komputer, 2019.
F. Febrianti, M. Hafiyusholeh, and A. H. Asyhar, “Perbandingan Pengklusteran data iris menggunakan metode k-means dan fuzzy c-means,” Jurnal Matematika" MANTIK, vol. 2, no. 1, pp. 7–13, 2016.
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