Optimizing the Division of Study Class Groups Using the Partitioning Around Medoids (PAM) Method
Optimization is a step to solve a problem to get more profitable results. Profitable based on the point of view used or the desired needs. The optimization value can be profitable in the maximum position or profitable in the minimum position. A problem can be solved in different ways, to produce the best solution. The best conditions can be viewed from many things, including tolerance, methods, and problems. Many theories have been developed to solve optimization problems. This optimization problem is often discussed because it is very close to human life. In this case, optimization can be interpreted as the process of achieving the most optimal results by adjusting input, selecting equipment, mathematical processes, and testing. Thereby in this paper, the Partitioning Around Medoids (PAM) method has succeeded in optimizing class grouping by calculating the closest distance between the achievement and intelligence of each student.
Article MetricsAbstract View: 77 times | PDF View: 11 times
P. G. VanderHart, “Why Do Some Schools Group by Ability?. Some Evidence from the NAEP,” Am. J. Econ. Sociol., vol. 65, no. 2, pp. 435–462, Apr. 2006.
T. Wiedemann, “Virtual textbook for modeling and simulation,” Winter Simul. Conf. Proc., vol. 2, pp. 1660–1665, 2000.
R. Agrawal, B. Golshan, and E. Terzi, “Grouping students in educational settings,” in Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD ’14, 2014, pp. 1017–1026.
K. Holmberg, “Formation of student groups with the help of optimisation,” J. Oper. Res. Soc., vol. 70, no. 9, pp. 1538–1553, 2019.
S. A. A. Freitas, R. C. Silva, E. D. Canedo, and T. F. R. Lucena, “A tool for students’ grouping in classroom,” Proc. - Front. Educ. Conf. FIE, vol. 2016-Novem, no. December, 2016.
R. Santos, B. N. Luz, V. F. Martins, D. R. C. Dias, M. de Paiva Guimarães, and M. D. P. Guimaraes, “Teaching-Learning Environment Tool to Promote Individualized Student Assistance,” in Conference: International Conference on Computational Science and Its Applications, 2015, vol. 9156, no. June, pp. 143–155.
J. B. Nisbet, N. J. Entwistle, B. McQuillin, and I. M. Robinson, “Staff and student perceptions of the teaching-learning environment: A case study,” Int. J. Electr. Eng. Educ., vol. 42, no. 1, pp. 30–40, 2005.
A. Prahara, D. P. Ismi, and A. Azhari, “Parallelization of Partitioning Around Medoids (PAM) in K-Medoids Clustering on GPU,” Knowl. Eng. Data Sci., vol. 3, no. 1, pp. 40–49, Aug. 2020.
R. D. Cahyaningrum, A. Bustamam, and T. Siswantining, “Implementation of spectral clustering with partitioning around medoids (PAM) algorithm on microarray data of carcinoma,” AIP Conf. Proc., vol. 1825, no. November 2019, 2017.
G. Shiyamalagowri, P. Ganapathy, V. Zaalishvili, and D. Melkov, “Partitioning around medoids approach application for computation of regional flood and landslide quantiles,” E3S Web Conf., vol. 157, p. 02001, Mar. 2020.
M. Bipul Hossen and M. Rabiul Auwul, “Comparative Study of K-Means, Partitioning Around Medoids, Agglomerative Hierarchical, and DIANA Clustering Algorithms by Using Cancer Datasets,” Biomed. Stat. Informatics, vol. 5, no. 1, p. 20, 2020.
F. R. Naibaho, “Optimalisasi Keputusan Untuk Memperoleh Keuntungan Maksimal Dalam Penentuan Kelayakan Operasional Kendaraan Dengan Menggunakan Metode Dynamic Programming Pada PT. Tor Ganda,” 2015.
Y. Zhao, X. Liu, and H. Zhang, “The K-Medoids Clustering Algorithm with Membrane Computing,” TELKOMNIKA Indones. J. Electr. Eng., vol. 11, no. 4, pp. 2050–2057, 2013.
F. R. Naibaho, “FUZZY LOGIC METODE TSUKAMOTO UNTUK PREDIKSI PRODUKSI CPO DENGAN PERMINTAAN BERSIFAT STOKASTIK PADA PT. TOR GANDA,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 3, no. 1, Nov. 2019.
A. Zandi and E. Roghanian, “Extension of Fuzzy ELECTRE based on VIKOR method,” Comput. Ind. Eng., vol. 66, no. 2, pp. 258–263, Oct. 2013.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Optimizing the Division of Study Class Groups Using the Partitioning Around Medoids (PAM) Method
- There are currently no refbacks.
Copyright (c) 2021 JURNAL MEDIA INFORMATIKA BUDIDARMA
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
JURNAL MEDIA INFORMATIKA BUDIDARMA
STMIK Budi Darma
Sekretariat : Jln. Sisingamangaraja No. 338 Telp 061-7875998
email : firstname.lastname@example.org
This work is licensed under a Creative Commons Attribution 4.0 International License.