Expert System For Career Early Determination Based On Howard Gardner's Multiple Intelligence

Rizky Ema Wulansari; RH Sakti; Ambiyar Ambiyar; M. Giatman; N. Syah; W.  Wakhinuddin

doi:10.37385/jaets.v3i2.568

Authors

Rizky Ema Wulansari Universitas Negeri Padang
RH Sakti Universitas Negeri Padang
Ambiyar Ambiyar Universitas Negeri Padang
M. Giatman Universitas Negeri Padang
N. Syah Universitas Negeri Padang
W. Wakhinuddin Universitas Negeri Padang

DOI:

https://doi.org/10.37385/jaets.v3i2.568

Keywords:

Expert system, Career, Multiple intelligence, Forward chaining method

Abstract

The problem that exists is how to design a tool to help students recognize their potential and abilities so that they can recognize the right potential in higher education based on their potential and abilities, with the influence of technological changes that have penetrated into life and even the world of education, then the purpose of this research is to develop software in the form of an expert system as a technology that can be used by students to be able to recognize their potential. The development of this expert system uses the Software Development Life Cycle (SDLC) method, the design of an expert system to determine the potential in higher education based on Multiple Intelligence. This expert system is designed using the Unified Modeling Language (UML).

Downloads

Download data is not yet available.

References

Andryukhina, LM, Dneprov, S. ., Sumina, TG, Yu, E., Utkina, SN, & Mantulenko, VV (2016). Vocational Pedagogical Competencies of a Professor in the Secondary Vocational Education System : Approbation of Monitoring Model. INTERNATIONAL JOURNAL OF ENVIRONMENTAL & SCIENCE EDUCATION, 11(14), 7045–7065.

Baird, J. A., Meadows, M., Leckie, G., & Caro, D. (2017). Rater accuracy and training group effects in Expert- and Supervisor-based monitoring systems. Assessment in Education: Principles, Policy and Practice, 24(1), 44–59. https://doi.org/10.1080/0969594X.2015.1108283

Baygin, M., Yetis, H., Karakose, M., & Akin, E. (2016). An effect analysis of industry 4.0 to higher education. 2016 15th International Conference on Information Technology Based Higher Education and Training (ITHET), 1–4. https://doi.org/10.1109/ITHET.2016.7760744

Collins, GW, & Knoetze, JG (2014). Information communication technology in the form of an expert system shell as a cognitive tool to facilitate higher-order thinking. Australasian Journal of Educational Technology, 30(4), 455–471. https://doi.org/10.14742/ajet.v30i4.189

Debebe, K., & Rajagopalan, V. (1995). A Learning Aid for Power Electronics with Knowledge Based Components. IEEE Transactions on Education, 38(2), 171–176. https://doi.org/10.1109/13.387220

Ghufron, MA (2018). Industrial Revolution 4.0: Challenges, Opportunities and Solutions for the World of Education. National Seminar and Multidisciplinary Panel Discussion on Research Results and Community Service, 332–337.

Hayadi, BH, Rukun, K., Wulansari, RE, & Herawan, T. (2017). Expert System of Quail Disease Diagnosis Using Forward Chaining Method. 5(1), 207–214. https://doi.org/10.11591/ijeecs.v5.i1.pp

Hung, YH, Lin, CF, & Chang, RI (2015). Developing a dynamic inference expert system to support individual learning at work. British Journal of Educational Technology, 46(6), 1378–1391. https://doi.org/10.1111/bjet.12214

Kiselev, NN, & Kiseleva, EV (2015). Expert Review of Pedagogical Activities at Therapeutic Recreation Camps. Russian Education and Society, 57(10), 830–837. https://doi.org/10.1080/10609393.2015.1148952

Kvesko, S., Kornienko, A., Kvesko, B., & Chicherina, N. (2018). Expert Systems as the Basis of Decisions in the Knowledge Society. MATEC Web of Conferences, 155, 1–7. https://doi.org/10.1051/matecconf/201815501009

Pavlekovic, M., Zekic-Susac, M., & Djurdjevic, I. (2009). Comparison of intelligent systems in detecting a child's mathematical gift. Computers and Education, 53(1), 142–154. https://doi.org/10.1016/j.compedu.2009.01.007

Rahimova Ali, N., & Abdullayev Hacimahmud, V. (2020). Methodology of expert system building. Technium: Romanian Journal of Applied Sciences and Technology, 2(3), 140–146. https://doi.org/10.47577/technium.v2i3.583

Ró?ewski, P., Kieruzel, M., Lipczy?ski, T., Prys, M., Sicilia, MA, García-Barriocanal, E., Sánchez-Alonso, S., Hamill, C., Royo, C., & Uras , F. (2019). Concept of expert system for creation of personalized, digital skills learning pathway. Procedia Computer Science, 159, 2304–2312. https://doi.org/10.1016/j.procs.2019.09.405

Rukun, K., Hayadi, BH, Mouludi, I., Lubis, A., Safril, & Jufri. (2017). Diagnosis of toddler digestive disorder using forward chaining method. 2017 5th International Conference on Cyber and IT Service Management, CITSM 2017. https://doi.org/101.1109/CITSM.2017.8089230

Sakti, RH, Sukardi, S., Giatman, M., Nazar, E., Wakhinuddin, W., & Waskito, W. (2020). Flipped Classroom-Computer Based Instruction for Learning Industrial Revolution 4.0: Design and Needs Analysis. Edumatic : Journal of Informatics Education, 4(1), 63–72. https://doi.org/10.29408/edumatic.v4i1.2074

Sánchez, LE, Santos-Olmo, A., lvarez, E., Huerta, M., Camacho, S., & Fernández-Medina, E. (2016a). Development of an expert system for the evaluation of students' curriculum on the basis of competencies. Future Internet, 8(2), 1–18. https://doi.org/10.3390/fi8020022

Sánchez, LE, Santos-Olmo, A., lvarez, E., Huerta, M., Camacho, S., & Fernández-Medina, E. (2016b). Development of an expert system for the evaluation of students' curriculum on the basis of competencies. Future Internet, 8(2). https://doi.org/10.3390/fi8020022

van Hecke, T. (2011). Fuzzy expert system to characterize students. Primus, 21(7), 651–658. https://doi.org/10.1080/10511971003688416

Williamson, K., & Cox, R. (2014). Distributed Cognition in Sports Teams: Explaining successful and expert performance. Educational Philosophy and Theory, 46(6), 640–654. https://doi.org/10.1080/00131857.2013.779215

Yoon, VY, & Adya, M. (2003). Encyclopedia of Information Systems. Elsevier Ltd.