Prediction of 6 Personality Characters (HEXACO) from Social Media using Random Forest Classifier and Particle Swarm Optimization
| Autor: | Iksan Ramadhan |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Jurnal Komputasi. 10 |
| ISSN: | 2541-0350 2541-0296 |
| DOI: | 10.23960/komputasi.v10i2.3171 |
| Popis: | The importance of personality assessment is required in determining whether an individual can support a job, or which position is suitable and in accordance with his personality. The personality model that is often used is the Myer Brigs Type Indicator, but the model is considered inappropriate for use because the model is too dichotomous in defining one's personality. Unlike the HEXACO personality model, the model provides a numerical assessment of each personality trait. In determining an individual's personality, it can be done by utilizing one's writing using the classification algorithm model. In the test, the data collected previously was classified according to its target to get the results in the form of personality classifications. Testing is done using the PSO algorithm so that the results obtained have a high level of accuracy, equal to 0.9 (90%). The use of PSO algorithm can help to get high accuracy results in the prediction process because the search for parameter values in the prediction model is done automatically. |
| Databáze: | OpenAIRE |
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