SISTEM PENERIMAAN SISWA BARU DI SMKN 3 PATI BERDASAR JALUR PRESTASI MENGGUNAKAN ALGORITMA KLASTERING K-MEANS BERBASIS WEB

Authors

  • Yassin Achmad Nur Aziz Universitas Stikubank Semarang
  • Eri Zuliarso Universits Stikubank Semarang

DOI:

https://doi.org/10.33884/jif.v10i02.5555

Keywords:

System, Application, New Student Admission, K-Means

Abstract

The new student admission system that uses the K-Means algorithm data grouping is the simplest clustering pattern compared to other algorithms. This algorithm is one of the data mining. K-Means groups them into several clusters that have similarities and separates each cluster based on the differences between each cluster.The research of the K-Means Clustering algorithm aims to minimize the functions set during the Clustering process.The implementation of the K-Means Clustering algorithm into the clustering information system provides the results of an effective data grouping classification and the process of each literacy rotation of the Centroid distance, the determination of the Cluster point is formed, student data as a reference object saves more time on clustering the superior class. The application of this web-based clustering information system results in more flexible information that can be accessed at any time by users who are given access rights to utilize the data. The application of the K-Means Clustering Algorithm to get the results of the Superior Class clarification requires an information system implementation to form 3 clusters for each class, namely M1, M2 and M3. M1 as a high score with a criterion value of 85 to 100, M2 as a medium value with a criterion value of 75 to 80 and M3 as a low value with a criterion value of 10 to 70.

References

S. Defiyanti, M. Jajuli, T. Informatika, F. Ilmu, K. Universitas, and S. Karawang, “IMPLEMENTASI ALGORITMA K-MEANS DALAM,” vol. I, no. 2, pp. 62–68, 2015.

F. Rini and N. Kahar, “PENERAPAN ALGORITMA K-MEANS PADA PENGELOMPOKAN DATA SISWA BARU BERDASARKAN JURUSAN DI SMK NEGERI 1 KOTA JAMBI BERBASIS WEB ”.,” pp. 28–29, 2016.

I. Pusvitaningrum, “Analisis Data Argumen Tentang Penerapan Kebijakan Sistem Zonasi Pada Pendaftaran Sekolah Dengan Menggunakan K-Means Clustering,” J. Buana Inform., vol. 11, no. 2, p. 1, 2020, doi: 10.24002/jbi.v11i2.3575.

P. Studi, T. Informatika, F. Teknologi, I. Dan, and U. T. Yogyakarta, “IMPLEMENTASI METODE K-MEANS PADA PENERIMAAN SISWA,” 2018.

A. Sulistiyawati and E. Supriyanto, “Implementasi Algoritma K-means Clustring dalam Penetuan Siswa Kelas Unggulan,” vol. 15, no. 2, pp. 25–36, 2020.

C. Satria and A. Anggrawan, “Aplikasi K-Means Berbasis Web untuk Klasifikasi Kelas Unggulan Web-based Application of K-Means for classification of Excellence,” vol. 21, no. 1, pp. 111–124, 2021, doi: 10.30812/matrik.v21i1.1473.

F. Nasari, S. Darma, and S. Informasi, “PENERAPAN K-MEANS CLUSTERING PADA DATA PENERIMAAN MAHASISWA BARU,” pp. 6–8, 2015.

R. K. S. C. Putri, “IMPLEMENTASI DEEP LEARNING MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK UNTUK KLASIFIKASI,” 2018.

A. Fauzi and S. Informasi, “Data Mining dengan Teknik Clustering Menggunakan Algoritma K-Means pada Data Transaksi Superstore,” no. September, pp. 15–19, 2017.

T. Pramiyati, “PERAN DATA PRIMER PADA PEMBENTUKAN SKEMA KONSEPTUAL YANG FAKTUAL ( STUDI KASUS : SKEMA KONSEPTUAL BASISDATA SIMBUMIL ),” vol. 8, no. 2, pp. 679–686, 2017.

N. Martono, “Analisis isi dan analisis data sekunder”.

U. Xyz and M. Algoritma, “UNIVERSITAS XYZ MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING,” 2019.

A. A. Sofyan, L. F. Gustomi, and S. Fitrianto, “Perancangan Sistem Informasi Perencanaan dan Pengendalian Bahan Baku Pada PT . Hema Medhajaya,” vol. 6, no. 1, 2016.

Simanjuntak, P., & Elisa, E. (2019). Data Mining Untuk Menentukan Pemilihan Celular Card Di Kota Batam. Journal Information System Development (ISD), 4(2).

S. Pada and P. D. Devi, “PERENCANAAN SISTEM INFORMASI BERBASIS WEB UNTUK SISTEM PERSEDIAAN DAN SISTEM PEMESANAN PRODUK JADI KONVEKSI,” vol. 3, no. 2, pp. 2788–2794, 2016.

Simanjuntak, P., Pangaribuan, H., & Syastra, M. T. (2021). Data Mining Rekomendasi Pemakaian Skincare. MEANS (Media Informasi Analisa dan Sistem), 6(1), 80-83.

S. Adi and D. M. Kristin, “STRUKTURISASI ENTITY RELATIONSHIP DIAGRAM DAN DATA FLOW DIAGRAM BERBASIS BUSINESS EVENT-DRIVEN,” vol. 5, no. 9, pp. 26–34.

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Published

2022-09-15

How to Cite

Nur Aziz, Y. A., & Zuliarso , E. (2022). SISTEM PENERIMAAN SISWA BARU DI SMKN 3 PATI BERDASAR JALUR PRESTASI MENGGUNAKAN ALGORITMA KLASTERING K-MEANS BERBASIS WEB. JURNAL ILMIAH INFORMATIKA, 10(02), 86–95. https://doi.org/10.33884/jif.v10i02.5555