The Implementation of Biplot and Cluster Analysis to Construct Sustainable Education Policies Toward Technology Literate Society in Indonesia
Keywords:
Biplot, cluster, digital, Indonesia, technologyAbstract
The digital era encourages society, especially the younger generation, to have the ability in developing technology and adapt in the era full of change and uncertainty. To establish a technology literate society in Indonesia, it is necessary to enhance the quality of education. This research aims to analyse the correlation between the competence in using technology, literacy rates, and the education completion level in establishing a technology literate society. Through biplot analysis, it was found that the education completion level, literacy rate, and the percentage of people who are able to use technology has a high positive correlation. Therefore, provinces where society has the capability to develop technology are provinces that have high literacy rates and educational completion level. In addition, using cluster analysis with the average linkage method, provinces in Indonesia are grouped into four clusters based on the erudition regarding technology, where the first cluster consists of five provinces, second cluster with 22 provinces, third cluster with six provinces, and forth cluster with a province, namely Papua. Through biplot and cluster analysis, the government can construct sustainable policies that are right on target based on the problems faced by each province.
References
Badan Pusat Statistik. (2021). Retrieved December 29, 2022, from https://www.bps.go.id/
Cohen-addad, V., Kanade, V., Mallmann-trenn, F., & Mathieu, C. (2019). Hierarchical Clustering: Objective Functions and Algorithms. Journal of the ACM, 66(4), 26:1-26:42. https://doi.org/10.1145/3321386
Dutta, A. K., Elhoseny, M., Dahiya, V., & Shankar, K. (2020). An efficient hierarchical clustering protocol for multihop Internet of vehicles communication. Transactions on Emerging Telecommunications Technologies, 31(5), e3690. https://doi.org/10.1002/ett.3690
Govender, P., & Sivakumar, V. (2020). Application of k-means and hierarchical clustering techniques for analysis of air pollution: A review (1980–2019). Atmospheric Pollution Research, 11(1), 40–56. https://doi.org/10.1016/j.apr.2019.09.009
Granato, D., Santos, J. S., Escher, G. B., Ferreira, B. L., & Maggio, R. M. (2018). Use of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for multivariate association between bioactive compounds and functional properties in foods: A critical perspective. Trends in Food Science & Technology, 72, 83–90. https://doi.org/10.1016/j.tifs.2017.12.006
Hashim, H. (2018). Application of Technology in the Digital Era Education. Research in Counseling and Education, 02(01). http://ppsfip.ppj.unp.ac.id/index.php/ijrice/article/view/2/81
Oliveira, T. R. A. de, Gravina, G. de A., Oliveira, G. H. F. de, Araújo, K. C., Araújo, L. C. de, Daher, R. F., Vivas, M., Gravina, L. M., & Cruz, D. P. da. (2018). The GT biplot analysis of green bean traits. Ciência Rural, 48. https://doi.org/10.1590/0103-8478cr20170757
Roux, M. (2018). A Comparative Study of Divisive and Agglomerative Hierarchical Clustering Algorithms. Journal of Classification, 35(2), 345–366. https://doi.org/10.1007/s00357-018-9259-9
Sandi, R. T. (2020). Perkembangan Society 1.0 Hingga Society 5.0. School of Information Systems. https://sis.binus.ac.id/2020/06/09/ perkembangan-society-1-0-hingga-society-5-0/
Shakeel, P. M., Baskar, S., Dhulipala, V. R. S., & Jaber, M. M. (2018). Cloud based framework for diagnosis of diabetes mellitus using K-means clustering. Health Information Science and Systems, 6(1), 16. https://doi.org/10.1007/s13755-018-0054-0
Zeng, K., Ning, M., Wang, Y., & Guo, Y. (2020). Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification. 13657–13665. https://openaccess.thecvf.com/content_CVPR_2020/html/Zeng_Hierarchical_Clustering_With_Hard-Batch_Triplet_Loss_for_Person_Re-Identification_CVPR_2020_paper.html
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Pressylia Aluisina Putri Widyangga

This work is licensed under a Creative Commons Attribution 4.0 International License.