Klasifikasi Kemampuan Ekonomi Calon Siswa Baru dengan Metode K-Nearest Neighbor pada SMA Negeri 1 Musi Rawas

Romi Aprillia Soleha(1*), Harma Oktafia Lingga Wijaya(2), Nelly Khairani Daulay(3),

(1) Universitas Bina Insan Lubuklinggau, Indonesia
(2) Universitas Bina Insan Lubuklinggau, Indonesia
(3) Universitas Bina Insan Lubuklinggau, Indonesia
(*) Corresponding Author

Abstract


The need for an analysis of the classification at SMA Negeri 1 Musi Rawas was the reason for conducting research on the clasification of the economic abilities of new student, determining classification in large numbers was impossible to do manually because it required quite a long time. For that we need a method that can solve classification problems automatically with a computer. in classifying an application in the form of orange is used and in analyzing using the K-Nearest Neighbor method because it has the working principle of fiding the shortest distance between the data to be evaluated with the nearest K in the training data. This study aims to apply the orange application using the K-Nearest Neighbor method and find out what the level of accuracy is with the K-Nearest Neighbor method. From this study the training data is 150 and testing 1 with a K value of 50 gets an accuracy value of 92%.

Full Text:

PDF

References


R. Lestarini, “Pengaruh status sosial ekonomi orang tua terhadap prestasi belajar ips siswa kelas vii di smp handayani sungguminasa skripsi,” no. September, 2019.

E. Yulianti, Y. A. Nurdin, F. T. Industri, and B. S. Miskin, “Sistem Pendukung Keputusan Penerimaan Bantuan Siswa Miskin ( Bsm ) Berbasis Online Dengan Metode Knn ( K-Nearest Neighbor ) ( Studi Kasus : Smpn 1 Koto Xi Tarusan ),” vol. 6, no. 1, pp. 12–17, 2018, doi: 10.21063/JTIF.2018.V6.1.12-17.

J. Homepage, S. R. Cholil, T. Handayani, R. Prathivi, and T. Ardianita, “IJCIT (Indonesian Journal on Computer and Information Technology) Implementasi Algoritma Klasifikasi K-Nearest Neighbor (KNN) Untuk Klasifikasi Seleksi Penerima Beasiswa,” IJCIT (Indonesian J. Comput. Inf. Technol., vol. 6, no. 2, pp. 118–127, 2021.

D. Prasetyawan and R. Gatra, “Algoritma K-Nearest Neighbor untuk Memprediksi Prestasi Mahasiswa Berdasarkan Latar Belakang Pendidikan dan Ekonomi,” vol. 7, no. 1, pp. 56–67, 2022.

W. P. Hidayanti, “Penerapan Algoritma K-Nearest Neighbor Untuk Klasifikasi Efektivitas Penjualan Vape ( Rokok El ektrik ) pada ‘ Lombok Vape On ’,” vol. 3, no. 2, 2020.

D. A. N. Pca, “Klasifikasi tingkat kematangan buah kopi berdasarkan deteksi warna menggunakan metode knn dan pca,” vol. 8, no. 2, pp. 88–95, 2021.

B. L. Yudha, L. Muflikhah, and R. C. Wihandika, “Klasifikasi Risiko Hipertensi Menggunakan Metode Neighbor Weighted K- Nearest Neighbor ( NWKNN ),” vol. 2, no. 2, pp. 897–904, 2018.

“Pengertian Ekonomi,” https://id.m.wikipedia.org. .

“Software Orange,” https://id.m.wikipedia.org. .

D. Rahmawati et al., “Bantuan Sosial Dengan Mengimplementasikan Algoritma K-Nearest Neighbor ( Studi Kasus : Rw 13 Kelurahan Palmerah Jakarta Barat ),” 2020.

S. Saepudin, M. Muslih, P. Studi, S. Informasi, and U. N. Putra, “Pemilihan Jurusan Dengan Metode K-Nearest Neighbor Untuk Calon Siswa Baru,” vol. 5, no. 2, 2019.

E. Sugiarto, A. Fahmi, and N. Hendriyanto, “Penerapan Neighbors Klasifikasi Aset Wakaf Produktif ( KNN ) untuk,” vol. 19, no. 2, 2022.

M. T. Informatika, “Penerapan Algoritma K-Nearest Neighbour Dalam Menentukan Pembinaan Koperasi Kabupaten Kotawaringin Timur,” no. April, pp. 232–241, 2019.

S. N. R, P. Harsani, and A. Qur, “Penerapan K-Nearest Neighbor ( KNN ) untuk Klasifikasi Anggrek Berdasarkan Karakter Morfologi Daun dan Bunga,” vol. 15, no. 1, pp. 118–125, 2018.

D. Kurniawan and A. Saputra, “Penerapan K-Nearest Neighbour dalam Penerimaan Peserta Didik dengan Sistem Zonasi,” J. Sist. Inf. Bisnis, vol. 9, no. 2, p. 212, 2019, doi: 10.21456/vol9iss2pp212-219.

F. Kurnia, J. Kurniawan, I. Fahmi, and S. Monalisa, “Klasifikasi Keluarga Miskin Menggunakan Metode K- Nearest Neighbor Berbasis Euclidean Distance,” no. November, pp. 230–239, 2019.

A. Khairi, “Untuk Klasifikasi Masyarakat Pra Sejahtera Desa Sapikerep Kecamatan Sukapura ,” vol. 2, no. 3, pp. 319–323, 2021.

R. L. Hasanah, M. Hasan, and W. E. Pangesti, “Klasifikasi Penerima Dana Bantuan Desa Menggunakan Metode Knn ( K-Nearest Neighbor ),” vol. 16, no. 1, pp. 1–6, 2019.




DOI: http://dx.doi.org/10.30645/jurasik.v8i1.542

DOI (PDF): http://dx.doi.org/10.30645/jurasik.v8i1.542.g520

Refbacks

  • There are currently no refbacks.



JURASIK (Jurnal Riset Sistem Informasi dan Teknik Informatika)
Published Papers Indexed/Abstracted By:

Jumlah Kunjungan : View My Stats