Assessment of Non-Verbal Communication Online Job Recruitment Using Gray Level Co-Occurrence Matrix and Fuzzy C-Means Algorithm

Abstract

Communication contains two dimensions, verbal and non-verbal. Non-verbal communication behavior was evaluated using the feature extract calculation of the Gray Level Co-Occurrence Matrix (GLCM). Extraction formula consists of feature, contrast, energy, entropy and homogeneity at rotation 00, 450, 900 and 1350. The results of the GLCM extraction calculation are then classified using the Fuzzy C-Means algorithm. Fuzzy C-Means (FCM) is used in pattern recognition. Data identification on the FCM is determined based on the degree of membership which has a value between 0 and 1. This study processes the applicant's offline video data. Identify expressions that indicate doubt, confusion and optimism. The assessment of the 10 videos was taken with the dominant optimistic expression extraction loop, it was obtained that the 7th video had the highest percentage of optimistic facial expressions.