Data Similarity Filtering of Wartegg Personality Test Result using Cosine-Similarity

Abstract

Wartegg test is a widely adopted personality evaluation instrument known for its drawing completion technique.  Employee personality data, for instance, can be sorted by the closest similarity with the expected characters. Whereas, Wartegg test plays a significant role in data similarity filtering. Despite the potential contribution of personal characters identification technique, practical guidance is rarely found in the literature. This paper demonstrates the usage of cosine-similarity method for data similarity filtering on Wartegg personality test. The method used in this study is a case study, in which will be selected several Wartegg test subjects. By using the value of each character aspect derived from the Wartegg test, the cosine-similarity value will be calculated against the expected/ideal aspect character. Based on this value, the Wartegg test subjects will be filtered based on similarity to the expected/ideal character aspects. A technical procedure to perform the method is also presented in this paper. In order to find out the effectiveness, sample data scores of each character aspect from five test subjects, and also the ideal scores of the expected characters are given. By using FWAT, a graphical representation of the test subjects' characters to the ideal characters is generated. Then, this graph was compared to the results obtained from the cosine-similarity method. Drawn from the results, the cosine-similarity is effectively applied for Wartegg test data similarity filtering.