LOYALTY ASSESSMENT OF COMPANY COSTUMER WITH CLASSIFICATION METHOD

##plugins.themes.academic_pro.article.main##

Fricles Ariwisanto Sianturi
Jonson Manurung
R.Fanry Siahaan

Abstract

Companies in general want the customers they have to be able to sustain forever. To make this happen is not something that is easy in the current climate of intense business competition, considering that there are rapid changes that can occur at any time, such as changes in customers, competitors and changes in broad conditions that are always dynamic. This requires policy makers to develop a strategy capable of achieving sales growth targets, increasing the company's market share. For this reason, an analysis of customer loyalty is needed.


For this reason, an analysis is needed to understand and assess customer loyalty using a classification design method. With classification, information can be produced more quickly and the information presented is analytical in nature so that it is easy to use for decision making.

##plugins.themes.academic_pro.article.details##

How to Cite
Ariwisanto Sianturi, F., Manurung, J., & Siahaan, R. (2020). LOYALTY ASSESSMENT OF COMPANY COSTUMER WITH CLASSIFICATION METHOD. INFOKUM, 9(1,Desember), 21-30. Retrieved from http://infor.seaninstitute.org/index.php/infokum/article/view/70

References

[1] E. Elisa, "Analysis and Application of the C4.5 Algorithm in Data Mining to Identify Factors Causing PT.Arupadhatu Adisesanti Construction Accidents," J. Online Inform., vol. 2, no. 1, p. 36, 2017, doi: 10.15575 / join.v2i1.71.
[2] S. Normasari, S. Kumadji, and A. Kusumawati, "The Influence of Service Quality on Customer Satisfaction, Company Image and Customer Loyalty," J. Adm. Business, 2013.
[3] M. Fahmi and FA Sianturi, "ANALYSIS OF APRIORIC ALGORITHM ON CONSUMER ORDERING AT CAFÉ THE L. COFFE COFFEE, "SAINTEK (Journal of Science and Technology., vol. 1, no. 1, pp. 52–57, 2019.
[4] A. Mukminin and D. Riana, "Comparison of C4 Algorithms. 5, Naïve Bayes And Neural Network For Soil Classification, "J. Inform., 2017.
[5] FA Sianturi, "Decision Tree Analysis in Student Data Processing," MEANS (Media Inf. Anal. And Sist., vol. 3, no. 2, pp. 166–172, 2018, [Online]. Available: http://ejournal.ust.ac.id/index.php/Jurnal_Means/.
[6] J. Simarmata et al., "Multimedia of number recognition for early childhood using image object," Int. J. Eng. Technol., Vol. 7, no. 3.2 Special Issue 2, pp. 796–798, 2018, doi: 10.14419 / ijet.v7i3.2.18760.
[7] YI Kurniawan, "Comparison of Naive Bayes Algorithm and C.45 in Data Classification Mining, ”J. Technol. Inf. and Computer Science., 2018, doi: 10.25126 / jtiik.201854803.
[8] FA Sianturi, B. Sinaga, PM Hasugian, T. Informatics, and S. Utara, "Fuzzy Multiple Attribute Decisison Macking Using Oreste Method to Determine Promotion Location," J. Inform. Pelita Nusant., vol. 3, no. 1, pp. 63–68, 2018, [Online]. Available: http://e-jurnal.pelitanusantara.ac.id/index.php/JIPN/article/view/289.
[9] DS Kusumo, MA Bijaksana, and D. Darmantoro, "DATA MINING WITH APRIORIC ALGORITHM IN ORACLE RDBMS," TECHNOLOGY - J. Researcher. and Pengemb. Telecomun. Control, Computer, Electr. and Electrons., 2016, doi: 10.25124 / tektrika.v8i1.215.
[10] EP Cynthia and E. Ismanto, "The C.45 Algorithm Decision Tree Method in Classifying Data on Sales of Fast Food Store Business," Jurasik (Jurnal Ris. Sist. Inf. And Tek. Inform., vol. 3, no. July, p. 1, 2018, doi: 10.30645 / jurasik.v3i0.60.
[11] IH Witten, E. Frank, MA Hall, and CJ Pal, Data Mining: Practical Machine Learning Tools and Techniques. 2016.

Most read articles by the same author(s)