Analysis Of The Use Of X-Means Method In Grouping Interest And Talent Data Students

http://doi.org/10.22216/jit.2020.v14i2.5414


Purwa Hasan Putra(1*), Muhammad Syahputra Novelan(2)

(1) Universitas Pembangunan Panca Budi
(2) Universitas Panca Budi
(*) Corresponding Author

Abstract


The X-Means algorithm is an algorithm used for grouping data. The x means algorithm is the development of k-means. X-means clustering is used to solve one of the main weaknesses of K-means clustering, namely the need for prior knowledge about the number of clusters (K). In this method, the true value of K is estimated in an unsupervised way and only based on the data set itself. The research results using the X-Means algorithm with Davies-Bouldin Index evaluation Determination of the number of Centroid clusters is done by modifying the X-Means method. In grouping this data, clustering is performed on each student data of the collected variables. Each student's gift and interest will be matched with the college and department of what each student is interested in

Keywords


X-Means, Decision Support System

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References


[1] Eka Sabna, Muhardi. 2016. “Penerapan Data Mining Untuk Memprediksi Prestasi
Akademik Mahasiswa Berdasarkan Dosen, Motivasi, Kedisiplinan, Ekonomi, dan Hasil
Belajar.†Jurnal CoreIT 41-44.

[2] Fakhroddin Noorbehbahani., Sadeq Mansoori. (2018). A New Semi-supervised Method for Network Traffic Classification Based on X-means Clustering and Label Propagation. 8th International Conference on Computer and Knowledge Engineering (ICCKE 2018), October 25-26 2018, Ferdowsi University of Mashhad. pp. 120-125

[3] Latifa Greeche., Maha Jazouli., Najia Es-Sbai., Aicha Majda., & Arsalane Zarghili. (2017). IEEE. pp. 1-4

[4] Mahdi Shahbaba, Soosan Beheshti. (2012). Improving X-Means Clustering With MNDL. he 11th International Conference on Information Sciences, Signal Processing and their Applications: Special Sessions pp.1298-1302.

[5] Nakyoung Kim., Hyojin Park., Jun Kyun Choi., & Jinhong Yang. (2017). Time Gap Accounted Video Scene Segmentation with Modified Mean-shift X-means Clustering. IEEE 6th Global Conference on Consumer Electronics (GCCE 2017) pp. 1-2

[6] Poteras, C. M., Mihaescu, M .C., & Mocanu, M. (2014). An Optimized Version of the K-Means Clustering. Proceedings of the 2014 Federated Conference on Computer Science and Information Systems pp. 695–699.


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