Author(s): Duenpen Panurug, Montean Rattanasiriwongwut
The objective of this research was to analyze the classification of texts related to job qualifications. A text analysis algorithm (Text Classification Analysis) was applied. This research gathered the qualifications of job positions from the database of JOBBKK Company (as of March 9, 2020), which is the most popular recruitment agency in Thailand. Data on the job qualifications of 10,000 samples were used to classify workgroups by means of the 10-Fold Cross Validation test, which uses five algorithms: Decision Tree, naive Bayes, Learning base (Support Vector Machine), Random Decision Forest (Random Forest), and K-Nearest Neighbor. Performance measures were precision, recall, and each algorithm's F-measure value. The analysis results show that the Support Vector Machine (SVM) algorithm has a text recognition efficiency with a highest accuracy of 92.73%.