Abstract
An individual must do work to meet his daily needs. According to revisesociology.com, which analyzed data from the Annual Survey for Hours and Earnings (ASHE) in the UK from 1997 to 2014, a worker would spend 92,120 h in a lifetime if assuming a full adult working life from ages 18–67. So that a person’s life will be spent much work. Furthermore, an article by Upskilled Australia mentions that many factors affect a person’s job satisfaction; it could be his job, benefits, or team camaraderie. However, a study shows that personality compatibility with work is the main factor that has a critical role. The more united one’s character with his career, the more productive and optimistic one’s work performance will be, therefore the selection of a job that suits the individual’s personality becomes very essential. In this study, a system has been created that can help job seekers find out what type of work matches the person’s personality so that each worker can work productively and achieves. The personality factors used are the Big Five, namely Extraversion, Agreeableness, Conscientiousness, Emotional Stability, and Intellect. This personality factor is mapped using C4.5 to get a job that matches your personality. The work fields based on the 20 Job Families are taken from the O*NET database. The system runs according to its purpose with accuracy of 99.99%. For further research, the development will be combined with other personality tests, such as the Myers-Briggs Type Indicator so that personality assessment has a broader scope.
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References
Friedman, H.S., Schustack, M.W.: Personality: Classic Theories and Modern Research. Pearson Education, Inc., New York City (2016)
Ziegler, M., Bensch, D., Maaß, U., Schult, V., Vogel, M., Bühner, M.: Big five facets as predictor of job training performance: the role of specific job demands. Learn. Individ. Differ. 29, 1–7 (2014)
Seibert, S.E., Kraimer, L.M.: The five-factor model of personality and career success. J. Vocat. Behav. 58, 1–21 (2001)
Mar’i, F., Mahmudy, W.F., Yusainy, C.: Sistem Rekomendasi Profesi Berdasarkan Dimensi Big Five Personality Menggunakan Fuzzy Inference System Tsukamoto. Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) 6, 456–466 (2019)
Tamin, F., Iswari, N.: Implementation of C4.5 algorithm to determine hospital readmission rate of diabetes patient. In: 2017 4th International Conference on New Media Studies (CONMEDIA) (2017). https://doi.org/10.1109/conmedia.2017.8266024
Hssina, B., Merbouha, A., Ezzikouri, H., Erritali, M.: A comparative study of decision tree ID3 and C4.5. Int. J. Adv. Comput. Sci. Appl. 4(2) (2014). https://doi.org/10.14569/specialissue.2014.040203
Cervone, D., Pervin, A.L.: Personality: Theory and Research. Wiley, Hoboken (2013)
Sackett, R.P., Walmsley, T.P.: Which personality attributes are most important in the workplace? Perspect. Psychol. Sci. 9, 538–551 (2014)
Akhtar, H., Saifuddin, A.: Indonesian adaptation and psychometric properties evaluation of the big five personality inventory: IPIP-BFM-50. Jurnal Psikologi 46, 32–44 (2019)
Larose, D.T., Larose, C.D.: Discovering Knowledge in Data. Wiley, Hoboken (2014)
Mardi, Y.: Data mining: Klasifikasi Menggunakan Algoritma C4.5. Jurnal Edik Informatika 2, 213–219 (2017)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo (1993)
Bramer, M.: Principles of Data Mining. Springer, London (2020)
Rahim, R., et al.: C4.5 classification data mining for inventory control. Int. J. Eng. Technol. 7, 68–72 (2018)
Take a personality test - open source psychometrics project. Take a personality test - Open Source Psychometrics Project. https://openpsychometrics.org/. Accessed 24 Aug 2021
Build your future WITH O*net online. O*NET OnLine. https://www.onetonline.org/. Accessed 24 Aug 2021
Jadhav, D., Bakade, T., Deshpande, S., Pethe, O., Kale, S., Madane, Y.: Big five personality prediction using machine learning algorithms. Math. Stat. Eng. Appl. 71(3), 1128–1133 (2022)
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Wulandari, R.S., Setianingsih, C., Kusuma, P.D. (2023). Analysis of Big Five Personality Factors to Determine the Appropriate Type of Career Using the C4.5 Algorithm. In: Wah, Y.B., Berry, M.W., Mohamed, A., Al-Jumeily, D. (eds) Data Science and Emerging Technologies. DaSET 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 165. Springer, Singapore. https://doi.org/10.1007/978-981-99-0741-0_2
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