Pengembangan Sistem Informasi Cerdas Career Guidance Berbasis Minat Di Perguruan Tinggi
Keywords:
Intelligent Information Systems, Career Guidance, Interest, Higher Education
Abstract
The development of an intelligent information system career guidance based on interests is designed to address the difficulties faced by high school graduates in determining their major in higher education. Difficulties often arise due to confusion caused by a lack of guidance and information. To help address this issue, an intelligent interest- based major recommendation information system was developed using the breadth-first search (BFS) method, which consists of 8 interest categories based on the Rothwell-Miller Interest Blank theory (RMIB). This intelligent information system can provide direction and guidance (career guidance) to students in determining the right major according to their interests. Career guidance application services are highly needed by students who are currently in their unstable teenage years, struggling to determine their paths. This system generates output in the form of major recommendations along with related information. The system is built with PHP and MySQL and tested using the user acceptance test (UAT).
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References
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[18] A. S. S. S. E. Ginting, “Comparison of Breadth First Search(BFS) and Dept-First Search(DFS) Methods on File Search in Structur Directory Windows,” J. Teknol. Komput., pp. 26–31, 2019.
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[2] D. K. Sukardi, Analisis Tes Psikologis. Jakarta: Rineka Cipta, 2003.
[3] R. S. A. R. A. Rahman, N. Othman, and N. B. M. Talkis, “The influence of attitude, interest, teachers and peers on entrepreneurial career intention,” Univers. J. Educ. Res., 2020, doi: 10.13189/ujer.2020.082110.
[4] N. Jansen van Vuuren, S. Rabie, and A. V. Naidoo, “Enhancing Career Interest Assessment in South Africa: Lessons Learned From the Development of the South African Career Interest Inventory-IsiXhosa Version,” Front. Psychol., 2022, doi: 10.3389/fpsyg.2022.854351.
[5] S. Panthee, S. Rajkarnikar, and R. Begum, “Career Guidance System Using Machine Learning,” J. Adv. Coll. Eng. Manag., 2023, doi: 10.3126/jacem.v8i2.55947.
[6] Y. Ayriza, A. Triyanto, F. A. Setiawati, and N. E. Gunawan, “Exploring children’s career interests and knowledge based on holland’s theory,” Int. J. Instr., 2020, doi: 10.29333/iji.2020.13440a.
[7] R. Yusof, M. Mokhtar, S. N. Ain Sulaiman, S. Syafril, and M. Mohtar, “Consistency between personality career interest with sciences field among gifted and talented students,” J. Educ. Gift. Young Sci., 2020, doi: 10.17478/JEGYS.667323.
[8] H. Hsin Chang, “Task-technology fit and user acceptance of online auction,” Int. J. Hum. Comput. Stud., 2010, doi: 10.1016/j.ijhcs.2009.09.010.
[9] W. Nurasih, A. Latifah, and A. H. I. Mohamed, “Spirituality transformation from metaphysical to metaverse.,” IAS J. Localities, 2023, [Online]. Available: https://doi.org/10.62033/iasjol.v1i2.17
[10] A. Chadzynski et al., “Semantic 3D City Agents—An intelligent automation for dynamic geospatial knowledge graphs,” Energy AI, 2022, doi: 10.1016/j.egyai.2022.100137.
[11] T. Lalwani, S. Bhalotia, A. Pal, S. Bisen, and V. Rathod, “Implementation of a Chat Bot System using AI and NLP,” Int. J. Innov. Res. Comput. Sci. Technol., 2018, doi: 10.21276/ijircst.2018.6.3.2.
[12] T. Zhang, Y. Zhang, A. Wang, R. Wang, H. Chen, and P. Liu, “Intelligent Analysis Cloud Platform for Soil Moisture-Nutrients-Salinity Content Based on Quantitative Remote Sensing,” Atmosphere (Basel)., 2023, doi: 10.3390/atmos14010023.
[13] H. Xing, J. Chen, H. Wu, and D. Hou, “A web service-oriented geoprocessing system for supporting intelligent land cover change detection,” ISPRS Int. J. Geo-Information, 2019, doi: 10.3390/ijgi8010050.
[14] Y. Chen, Y. Chen, K. Chen, and M. Liu, “Research Progress and Hotspot Analysis of Residential Carbon Emissions Based on CiteSpace Software,” International Journal of Environmental Research and Public Health. 2023. doi: 10.3390/ijerph20031706.
[15] H. B. S. B. D. Zai, “Simulasi Rute Terpendek Lokasi Pariwisata di Nias Dengan Metode BFS,” J. InFact, pp. 30–41, 2016.
[16] E. Wijaya, “Analisis Penggunaan Algoritma Breadth First Search Dalam Konsep Artificial Intellegencia,” J. TIME, vol. 2, no. 2, pp. 18–26, 2013.
[17] M. H. M. Q. B. Nurdin, “Sistem Pengecekan Toko Online Asli atau Dropship pada Shopee Menggunakan Algoritma Breath First Search,” J. Resti(Rekayasa Sist. dan Teknol. Informasi), vol. 4, no. 6, pp. 1117–1123, 2020.
[18] A. S. S. S. E. Ginting, “Comparison of Breadth First Search(BFS) and Dept-First Search(DFS) Methods on File Search in Structur Directory Windows,” J. Teknol. Komput., pp. 26–31, 2019.
[19] A. Mustaqim, D. B. Dinova, M. S. Fadhilah, R. Seivany, B. Prasetiyo, and M. A. Muslim, “Optimizing the Implementation of the BFS and DFS algorithms using the web crawler method on the kumparan site,” J. Soft Comput. Explor, vol. 5, no. 2, pp. 200–206, 2024.
Published
2024-12-20
How to Cite
Haerani, E., Syafria, F., & Muhammad Yusuf Fadhillah. (2024). Pengembangan Sistem Informasi Cerdas Career Guidance Berbasis Minat Di Perguruan Tinggi. Jurnal CoSciTech (Computer Science and Information Technology), 5(3), 580-588. Retrieved from https://ejurnal.umri.ac.id/index.php/coscitech/article/view/8254
Section
Articles
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