TAILIEUCHUNG - Application of fuzzy logic to improve the Likert scale to measure latent variables

The research studied the process of improving the Likert scale based on fuzzy logic to measure latent variables and to compare the quality of the data as measured by the improved Likert scale with data measured by the Likert scale. Qualitative study and survey study were used as the research methodology. | Kasetsart Journal of Social Sciences 38 2017 337e344 Contents lists available at ScienceDirect Kasetsart Journal of Social Sciences journal homepage http locate kjss Application of fuzzy logic to improve the Likert scale to measure latent variables Paothai Vonglao Faculty of Science Ubon Ratchathani Rajabhat University Ubon Ratchathani 34000 Thailand a r t i c l e i n f o a b s t r a c t Article history The research studied the process of improving the Likert scale based on fuzzy logic to Received 16 February 2016 measure latent variables and to compare the quality of the data as measured by the Received in revised form 21 December 2016 improved Likert scale with data measured by the Likert scale. Qualitative study and survey Accepted 30 January 2017 study were used as the research methodology. Data analysis included content analysis and Available online 26 August 2017 statistics comprising the arithmetic mean standard deviation standard error consensus index and the KolmogoroveSmirnov test. It was found that the Likert scale could be Keywords improved by using Mamdadi fuzzy inference which included four important steps fuzzy logic 1 fuzzification 2 fuzzy rule evaluation 3 aggregation and 4 defuzzification. A latent variable comparison of the two different approaches showed that the data measured using the Likert scale improved Likert scale was more suitable to be analyzed with the arithmetic mean and standard deviation than the data measured using the Likert scale. More importantly the distribution of data measured by the improved Likert scale was normal with a lower standard error making it appropriate for data analysis for statistical inference. 2017 Kasetsart University. Publishing services by Elsevier . This is an open access article under the CC BY-NC-ND license http licenses by-nc-nd . Introduction interval scale as they are acquired through psychological scaling. The latent variables are measured by the com- .

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