Application of K-Means Clustering Algorithm to Obtain Recommendations for Strategies to Increase the Number of Students in the Information Systems Study Program at ITB Ahmad Dahlan Jakarta
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Application, Clustering, Information
Abstract
The rapid development of technology today has almost touched all sectors of life such as the economy, health and education. The technology currently used produces a lot of data every day, one of which is in the field of education. Data mining is a group of methods used to investigate and reveal complex relationships in very large data sets. Data here means information organized in a tabular format, as is often used in relational database management. This research uses data from the academic section of ITB Ahmad Dahlan, namely data on students of the Information Systems study program from 2019 to 2022. The attributes that will be used for this research are student gender, student employment status and student achievement index. Recommendations for promotional strategies to increase the number of new students are to conduct visits to high schools or vocational schools. Not only that, the new student admission team can also promote to companies or offices.
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Abbasi, S., Keshavarzi, B., Moore, F., Turner, A., Kelly, F. J., Dominguez, A. O., & Jaafarzadeh, N. (2019). Distribution and potential health impacts of microplastics and microrubbers in air and street dusts from Asaluyeh County, Iran. Environmental Pollution, 244, 153–164. https://doi.org/10.1016/j.envpol.2018.10.039
Agus Triansyah, F., Hejin, W., & Stefania, S. (2023). Factors Affecting Employee Performance: A Systematic Review. Journal Markcount Finance, 1(2), 118–127. https://doi.org/10.55849/jmf.v1i2.102
Albrecht, E., & Chin, K. J. (2020). Advances in regional anaesthesia and acute pain management: A narrative review. Anaesthesia, 75(S1). https://doi.org/10.1111/anae.14868
Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004
Archibald, M. M., Ambagtsheer, R. C., Casey, M. G., & Lawless, M. (2019). Using Zoom Videoconferencing for Qualitative Data Collection: Perceptions and Experiences of Researchers and Participants. International Journal of Qualitative Methods, 18, 160940691987459. https://doi.org/10.1177/1609406919874596
Belanche, D., Casaló, L. V., Flavián, C., & Schepers, J. (2020). Service robot implementation: A theoretical framework and research agenda. The Service Industries Journal, 40(3–4), 203–225. https://doi.org/10.1080/02642069.2019.1672666
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019). Internet of things and supply chain management: A literature review. International Journal of Production Research, 57(15–16), 4719–4742. https://doi.org/10.1080/00207543.2017.1402140
Chaabouni, N., Mosbah, M., Zemmari, A., Sauvignac, C., & Faruki, P. (2019). Network Intrusion Detection for IoT Security Based on Learning Techniques. IEEE Communications Surveys & Tutorials, 21(3), 2671–2701. https://doi.org/10.1109/COMST.2019.2896380
Coman, C., ?îru, L. G., Mese?an-Schmitz, L., Stanciu, C., & Bularca, M. C. (2020). Online Teaching and Learning in Higher Education during the Coronavirus Pandemic: Students’ Perspective. Sustainability, 12(24), 10367. https://doi.org/10.3390/su122410367
Dong, X., Yu, Z., Cao, W., Shi, Y., & Ma, Q. (2020). A survey on ensemble learning. Frontiers of Computer Science, 14(2), 241–258. https://doi.org/10.1007/s11704-019-8208-z
Giordani, M., Polese, M., Roy, A., Castor, D., & Zorzi, M. (2019). A Tutorial on Beam Management for 3GPP NR at mmWave Frequencies. IEEE Communications Surveys & Tutorials, 21(1), 173–196. https://doi.org/10.1109/COMST.2018.2869411
Hüllermeier, E., & Waegeman, W. (2021). Aleatoric and epistemic uncertainty in machine learning: An introduction to concepts and methods. Machine Learning, 110(3), 457–506. https://doi.org/10.1007/s10994-021-05946-3
Jain, N., Brock, J. L., Malik, A. T., Phillips, F. M., & Khan, S. N. (2019). Prediction of Complications, Readmission, and Revision Surgery Based on Duration of Preoperative Opioid Use: Analysis of Major Joint Replacement and Lumbar Fusion. Journal of Bone and Joint Surgery, 101(5), 384–391. https://doi.org/10.2106/JBJS.18.00502
Kang, Z., Wen, L., Chen, W., & Xu, Z. (2019). Low-rank kernel learning for graph-based clustering. Knowledge-Based Systems, 163, 510–517. https://doi.org/10.1016/j.knosys.2018.09.009
Modi, V., & Dunbrack, R. L. (2019). Defining a new nomenclature for the structures of active and inactive kinases. Proceedings of the National Academy of Sciences, 116(14), 6818–6827. https://doi.org/10.1073/pnas.1814279116
Oztemel, E., & Gursev, S. (2020). Literature review of Industry 4.0 and related technologies. Journal of Intelligent Manufacturing, 31(1), 127–182. https://doi.org/10.1007/s10845-018-1433-8
Peng, X., & Liu, L. (2019). Information measures for q ?rung orthopair fuzzy sets. International Journal of Intelligent Systems, 34(8), 1795–1834. https://doi.org/10.1002/int.22115
Reed, G. M., First, M. B., Kogan, C. S., Hyman, S. E., Gureje, O., Gaebel, W., Maj, M., Stein, D. J., Maercker, A., Tyrer, P., Claudino, A., Garralda, E., Salvador?Carulla, L., Ray, R., Saunders, J. B., Dua, T., Poznyak, V., Medina?Mora, M. E., Pike, K. M., … Saxena, S. (2019). Innovations and changes in the ICD?11 classification of mental, behavioural and neurodevelopmental disorders. World Psychiatry, 18(1), 3–19. https://doi.org/10.1002/wps.20611
Rodriguez, M. Z., Comin, C. H., Casanova, D., Bruno, O. M., Amancio, D. R., Costa, L. D. F., & Rodrigues, F. A. (2019). Clustering algorithms: A comparative approach. PLOS ONE, 14(1), e0210236. https://doi.org/10.1371/journal.pone.0210236
Safiri, S., Kolahi, A.-A., Smith, E., Hill, C., Bettampadi, D., Mansournia, M. A., Hoy, D., Ashrafi-Asgarabad, A., Sepidarkish, M., Almasi-Hashiani, A., Collins, G., Kaufman, J., Qorbani, M., Moradi-Lakeh, M., Woolf, A. D., Guillemin, F., March, L., & Cross, M. (2020). Global, regional and national burden of osteoarthritis 1990-2017: A systematic analysis of the Global Burden of Disease Study 2017. Annals of the Rheumatic Diseases, 79(6), 819–828. https://doi.org/10.1136/annrheumdis-2019-216515
Shahapure, K. R., & Nicholas, C. (2020). Cluster Quality Analysis Using Silhouette Score. 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 747–748. https://doi.org/10.1109/DSAA49011.2020.00096
Tang, C., Zhu, X., Liu, X., Li, M., Wang, P., Zhang, C., & Wang, L. (2019). Learning a Joint Affinity Graph for Multiview Subspace Clustering. IEEE Transactions on Multimedia, 21(7), 1724–1736. https://doi.org/10.1109/TMM.2018.2889560
Thangaramya, K., Kulothungan, K., Logambigai, R., Selvi, M., Ganapathy, S., & Kannan, A. (2019). Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT. Computer Networks, 151, 211–223. https://doi.org/10.1016/j.comnet.2019.01.024
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. C. (2020). Immediate Psychological Responses and Associated Factors during the Initial Stage of the 2019 Coronavirus Disease (COVID-19) Epidemic among the General Population in China. International Journal of Environmental Research and Public Health, 17(5), 1729. https://doi.org/10.3390/ijerph17051729
Wang, Y., Chen, Q., Hong, T., & Kang, C. (2019). Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges. IEEE Transactions on Smart Grid, 10(3), 3125–3148. https://doi.org/10.1109/TSG.2018.2818167
Wortham, J. M., Lee, J. T., Althomsons, S., Latash, J., Davidson, A., Guerra, K., Murray, K., McGibbon, E., Pichardo, C., Toro, B., Li, L., Paladini, M., Eddy, M. L., Reilly, K. H., McHugh, L., Thomas, D., Tsai, S., Ojo, M., Rolland, S., … Reagan-Steiner, S. (2020). Characteristics of Persons Who Died with COVID-19—United States, February 12–May 18, 2020. MMWR. Morbidity and Mortality Weekly Report, 69(28), 923–929. https://doi.org/10.15585/mmwr.mm6928e1
Zhan, K., Nie, F., Wang, J., & Yang, Y. (2019). Multiview Consensus Graph Clustering. IEEE Transactions on Image Processing, 28(3), 1261–1270. https://doi.org/10.1109/TIP.2018.2877335
Zhang, R., Chen, Z., Chen, S., Zheng, J., Büyüköztürk, O., & Sun, H. (2019). Deep long short-term memory networks for nonlinear structural seismic response prediction. Computers & Structures, 220, 55–68. https://doi.org/10.1016/j.compstruc.2019.05.006
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Copyright (c) 2023 Diana Yusuf, Xie Guilin, Deng Jiao
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