ANALYTICAL HIERARCHY PROCESS AND MARKOV CHAIN IN SHARED KNOWLEDGE THROUGH SOCIAL MEDIA

Authors

  • Nor Intan Saniah Sulaiman School of Quantitative Sciences, UUM College of Arts and Sciences, UUM, Sintok, Kedah, Malaysia
  • Saadiah Ghazali School of Quantitative Sciences, UUM College of Arts and Sciences, UUM, Sintok, Kedah, Malaysia
  • Nerda Zura Zabidi School of Quantitative Sciences, UUM College of Arts and Sciences, UUM, Sintok, Kedah, Malaysia
  • Mohd Faizal Omar School of Quantitative Sciences, UUM College of Arts and Sciences, UUM, Sintok, Kedah, Malaysia
  • Rose Alinda Alias Faculty of Computing, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v77.6119

Keywords:

Knowledge sharing, social media, analytic hierarchy process, Markov Chain

Abstract

Many studies have been performed to measure successful knowledge sharing in general. However, limited study has been done to assess successful knowledge sharing through social media. Hence, in this paper intend to discuss our approach to assess   knowledge sharing among personal social media user. In order to achieve our objective, we proposed to integrate Analytic Hierarchy Process (AHP) and Markov Chain (MC) technique to investigate the pattern of the shared knowledge through social media. Markov Chain will be used to model the knowledge sharing success through expert opinion and stochastic process. We anticipate the outcome of the assessment in a form of a final matrix showing the probability of successful knowledge sharing through social media. The elements in each row of the Markov Chain transition matrix will be calculated using Analytic Hierarchy Process.  The assessment tool produce from our research is expected to benefit policy maker or internet user in order to enhance their knowledge sharing strategy in social media application.

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Published

2015-11-05

How to Cite

ANALYTICAL HIERARCHY PROCESS AND MARKOV CHAIN IN SHARED KNOWLEDGE THROUGH SOCIAL MEDIA. (2015). Jurnal Teknologi (Sciences & Engineering), 77(5). https://doi.org/10.11113/jt.v77.6119