Klasifikasi Loyalitas Pengguna Sistem E-Learning Menggunakan Net Promoter Score dan Machine Learning
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P. Martínez dan I. Rodríguez, “CSR and customer loyalty : The roles of trust , customer identification with the company and satisfaction,” Int. J. Hosp. Manag., vol. 35, hal. 89–99, 2013, doi: 10.1016/j.ijhm.2013.05.009.
I. H. N. Aprilia, P. I. Santoso, dan R. Ferdiana, “Pengujian Usability Website Menggunakan System Usability Scale Website Usability Testing using System Usability Scale,” J. IPTEK-KOM, vol. 17, no. 1, hal. 31–38, 2015.
D. Supriyadi, S. T. Safitri, dan D. Y. Kristiyanto, “Higher Education e-Learning Usability Analysis Using System Usability Scale,” Int. J. Inf. Syst. Technol., vol. 4, no. 36, hal. 436–446, 2020.
ISO, “INTERNATIONAL STANDARD 9241-11:2018 Usability : Definitions and concepts,” 2018.
R. A. Grier, A. Bangor, P. Kortum, dan S. C. Peres, “The system usability scale: Beyond standard usability testing,” Proc. Hum. Factors Ergon. Soc., hal. 187–191, 2013, doi: 10.1177/1541931213571042.
J. R. Lewis, “Measuring Perceived Usability: The CSUQ, SUS, and UMUX,” Int. J. Hum. Comput. Interact., vol. 34, no. 12, hal. 1148–1156, 2018, doi: 10.1080/10447318.2017.1418805.
J. Sauro dan J. R. Lewis, “When designing usability questionnaires, does it hurt to be positive?,” Conf. Hum. Factors Comput. Syst. - Proc., no. May 2011, hal. 2215–2223, 2011, doi: 10.1145/1978942.1979266.
J. Sauro, “Does Better Usability Increase Customer Loyalty?,” Measuring U, 2010. [Daring]. Tersedia pada: http://www.measuringu.com/usability-loyalty.php. [Diakses: 01-Nov-2020].
P. C. Verhoef, “Understanding the Effect of Efforts on Customer Retention and,” J. Mark., vol. 67, no. October, hal. 30–45, 2003.
D. Vélez, A. Ayuso, C. Perales-gonzález, dan J. T. Rodríguez, “Knowledge-Based Systems Churn and Net Promoter Score forecasting for business decision-making through a new stepwise regression methodology,” Knowledge-Based Syst., vol. 196, hal. 105762, 2020, doi: 10.1016/j.knosys.2020.105762.
L. Ma dan B. Sun, “Machine learning and AI in marketing – Connecting computing power to human insights,” Int. J. Res. Mark., no. xxxx, 2020, doi: 10.1016/j.ijresmar.2020.04.005.
T. K. Balaji, C. Sekhara, R. Annavarapu, dan A. Bablani, “Machine learning algorithms for social media analysis : A survey,” Comput. Sci. Rev., vol. 40, hal. 100395, 2021, doi: 10.1016/j.cosrev.2021.100395.
R. Nayak, S. A. Jiwani, dan B. Rajitha, “Materials Today : Proceedings Spam email detection using machine learning algorithm,” Mater. Today Proc., no. xxxx, 2021, doi: 10.1016/j.matpr.2021.03.147.
D. Berrar, “Bayes ’ Theorem and Naive Bayes Classi fi er,” Encyclopedia of Bioinformatics and Computational Biology, vol. 1. Elsevier Inc., 2018, doi: 10.1016/B978-0-12-809633-8.20473-1.
E. M. M. Van Der Heide, R. F. Veerkamp, M. L. Van Pelt, C. Kamphuis, I. Athanasiadis, dan B. J. Ducro, “Comparing regression , naive Bayes , and random forest methods in the prediction of individual survival to second lactation in Holstein cattle,” J. Dairy Sci., vol. 102, no. 10, hal. 9409–9421, 2019, doi: 10.3168/jds.2019-16295.
A. Tella, A. Balogun, N. Adebisi, dan S. Abdullah, “Spatial Assessment of PM10 hotspots using Random Forest, K-Nearest Neighbor and Naive Bayes,” Atmos. Pollut. Res., hal. 101202, 2021, doi: 10.1016/j.apr.2021.101202.
J. Brooke, “SUS - A quick and dirty usability scale. Usability evaluation in industry,” vol. 189, no. 194, hal. 4–7, 1996, doi: 10.4236/9781618961020_0002.
P. Korneta, “Net promoter score, growth, and profitability of transportation companies,” Int. J. Manag. Econ., vol. 54, no. 2, hal. 136–148, 2018, doi: 10.2478/ijme-2018-0013.
M. Kubat, An Introduction to Machine Learning, 2nd Ed. Springer, 2017.
F. Maepa, R. S. Smith, dan A. Tessema, “Support vector machine and artificial neural network modelling of orogenic gold prospectivity mapping in the Swayze greenstone belt , Ontario , Canada,” Ore Geol. Rev., vol. 130, no. June 2020, hal. 103968, 2021, doi: 10.1016/j.oregeorev.2020.103968.
D. Supriyadi dan S. T. Safitri, “The Application of C4 . 5 Algorithm to Classify the User Satisfaction of Online Learning System,” Int. J. Inf. Syst. Technol., vol. 3, no. 36, hal. 323–331, 2020.
G. S. Kumar, “Decision Trees: A step-by-step approach to building DTs,” Towards data science, 2020. [Daring]. Tersedia pada: https://towardsdatascience.com/decision-trees-a-step-by-step-approach-to-building-dts-58f8a3e82596. [Diakses: 15-Sep-2021].
M. M. S dan A. Yasar, “Intelligent Systems and Applications in Engineering Performance Analysis of ANN and Naive Bayes Classification Algorithm for Data Classification,” Int. J. Intell. Syst. Appl. Eng., vol. 7, no. 2, hal. 88–91, 2019, doi: 10.1039/b000000x.
O. Harrison, “Machine Learning Basics with the K-Nearest Neighbors Algorithm,” Towards data science, 2018. [Daring]. Tersedia pada: https://towardsdatascience.com/machine-learning-basics-with-the-k-nearest-neighbors-algorithm-6a6e71d01761. [Diakses: 15-Sep-2021].
V. L. Miguéis, A. Freitas, P. J. V. Garcia, dan A. Silva, “Early segmentation of students according to their academic performance: A predictive modelling approach,” Decis. Support Syst., vol. 115, no. September, hal. 36–51, 2018, doi: 10.1016/j.dss.2018.09.001.
S. Shalev-shwartz, C. Science, S. Ben-david, dan C. Science, Understanding Machine Learning From Theory to Algorithms. New York, USA: Cambridge University Press, 2014.
DOI: http://dx.doi.org/10.26418/jp.v8i1.49300
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