ANALISIS PERPIDAHAN PENGGUNAAN MEREK SIMCARD DENGAN PENDEKATAN RANTAI MARKOV

Abstract

The aim of this research is to know the displacement made by consumers of GSM cards and predictions of market share when reaching equilibrium conditions for each of the displacements made by consumers of GSM cards. This research uses Markov chain method. Markov chain method produces probabilistic information that can be used to assist for making decision. In Markov’s analysis, the equilibrium conditions are conditions in which the variables in the system ultimately bring the transition probabilities in stable or unchanged conditions. Data from this research is divided into two categories namely data about brand switching of GSM cards and data about the transfer of GSM cards brand usage. Data brand switching of GSM cards obtained from users who use one GSM cards, while the data transfer use of GSM cards obtained from user more than one GSM cards. The results of this research indicate that GSM card displacement equilibrium conditions was achieved in the 9th period, whereas the results of switching the use of GSM card shows that equilibrium conditions for phone and SMS users is in the 15th period, and equilibrium conditions for internet user is reached in 5th period.

Downloads

Download data is not yet available.

Author Biographies

NURMA ALIYUWANINGSIH, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

I WAYAN SUMARJAYA, Udayana University

Program Studi Matematika, Fakultas MIPA – UniversitasUdayana

I GUSTI AYU MADE SRINADI, Udayana University

Program Studi Matematika, Fakultas MIPA – UniversitasUdayana

Published
2018-02-03
How to Cite
ALIYUWANINGSIH, NURMA; SUMARJAYA, I WAYAN; SRINADI, I GUSTI AYU MADE. ANALISIS PERPIDAHAN PENGGUNAAN MEREK SIMCARD DENGAN PENDEKATAN RANTAI MARKOV. E-Jurnal Matematika, [S.l.], v. 7, n. 1, p. 56-63, feb. 2018. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/37607>. Date accessed: 12 aug. 2022. doi: https://doi.org/10.24843/MTK.2018.v07.i01.p185.
Section
Articles

Most read articles by the same author(s)

1 2 3 > >>