Model Sistem Rekomendasi Guna Peningkatan Kesesuaian Kebutuhan Program Kampus Merdeka Belajar

Dwi Agus Diartono(1*), R. Soelistijadi(2), Herny Februariyanti(3), Eri Zuliarso(4),

(1) Universitas Stikubank
(2) Universitas Stikubank
(3) Universitas Stikubank
(4) Universitas Stikubank
(*) Corresponding Author

Abstract


This paper discusses the automatic matching of students applying for the Internship and Independent Study (MSIB) program with partner companies. Many companies offer MSIB programs. This makes it difficult for students to register according to their competence. For this reason, a system is needed that will help students recommend vacancies according to their competence. This research will build a MSIB recruitment recommendation system. The research will begin by building a database of activity details for apprentice and independent study program partners. Details of partner activities contain program descriptions, Developed Competencies and Participant Criteria. This data will be used to build a MSIB vacancy recommendation system. Matching is done by comparing the Company's needs with the portfolio. At the beginning of the research, notes will be made based on students who are accepted into the MSIB program. Next, build a matching system between the MSIB vacancies offered and the work portfolios made by students. This system is expected to help students to be accepted into the MSIB program. The model used is content-based recommendation system. A content-based recommendation system will provide a list of vacancies that best match the student portfolio. The content-based recommendation system will use the cosine similarity algorithm and K-Nearest Neighbor (K-NN).

The output of this study is a recommendation model for recruiting apprenticeship programs and independent studies. It is hoped that this system will help students determine internship programs and independent studies that suit their portfolios

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References


Neni Herlina, 2021, Delapan Kegiatan Diluar Program Studi, dikti.kemdikbud, https://dikti.kemdikbud.go.id/epustaka/delapan-kegiatan-diluar-program-studi/

Saputro, Bagus Ardi, et al. "Partisipasi Program Studi Di Universitas Pgri Semarang Dalam Implementasi Program Merdeka Belajar Kampus Merdeka (Mbkm)." Dimensi Pendidikan 17.3 (2021).

Rochana, Rochana, R. M. Darajatun, and Muhamad Arief Ramdhany. "Pengaruh implementasi kebijakan kampus merdeka terhadap minat dan keterlibatan mahasiswa." Journal of Business Management Education (JBME) 6.3 (2021): 11-21.

Al Idrus, Shofiyah, et al. "An Automated Portfolio for Job Opportunities." 2021 7th International Conference on Electrical, Electronics and Information Engineering (ICEEIE). IEEE, 2021.

Lorenzo, George, and John Ittelson. "An overview of e-portfolios." Educause learning initiative 1.1 (2005): 1-27..

Shaha T Al-Otaibi and Mourad Ykhlef. A survey of job recommender systems. International Journal of the Physical Sciences, 7(29):5127–5142, 2012.

Rémy Kessler, Nicolas Béchet, Mathieu Roche, Juan-Manuel Torres-Moreno, and Marc El-Bèze. A hybrid approach to managing job offers and candidates. Inf. Process. Manage., 48(6).

V. Senthil Kumaran and A. Sankar. Towards an automated system for intelligent screening of candidates for recruitment using ontology mapping expert. Int. J. Metadata Semant. Ontologies, 8(1):56–64, 2013.

Yu, Ti. "E‐portfolio, a valuable job search tool for college students." Campus-Wide Information Systems (2012).

Yancey, K.B. “Digitized student portfolios”, in Cambridge, B.L. et al. (Eds), Electronic Portfolio: Emerging Practices in Student, Faculty, and Institutional Learning, American Association for Higher Education,

Washington, DC, pp. 15-30.(2001)

Ward, C. and Moser, C. , “E-portfolios as a hiring tool: do employers really care?”, EDUCAUSE Quarterly, Vol. 4, pp. 13-14.(2008)

Kessler, Rémy, et al. "A hybrid approach to managing job offers and candidates." Information processing & management 48.6 (2012): 1124-1135.

V. Senthil Kumaran and A. Sankar. Towards an automated system for intelligent screening of candidates for recruitment using ontology mapping expert. Int. J. Metadata Semant. Ontologies, 8(1):56–64, 2013.

Ioannis Paparrizos, B. Barla Cambazoglu, and Aristides Gionis. Machine learned job recommendation. In Proc. ACM Conference on Recommender Systems, RecSys ’11, 2011.

Xing Yi, James Allan, and W. Bruce Croft. Matching resumes and jobs based on relevance models. In Proc. SIGIR Conference on Research and Development in Information Retrieval, pages 809–810. ACM, 2007.

Breiman, Leo. "Random forests." Machine learning 45.1 (2001): 5-32.

Rish,I.,etal.,.Anempirical study of the naïve bayes classifier, in:IJCAI2001 workshop on empirical methods in artificial intelligence,pp.41–46. 2001.

Nasrabadi,N.M.,2007.Pattern recognition and machine learning. Journal ofelectronic imaging 16,049901

Sch¨olkopf,B.,Smola,A.J.,Bach,F.,etal.,2002.Learningwithkernels:supportvectormachines,re gularization,optimization,andbeyond.MITpress

Sak H, Senior A, Beaufays F (2014) Long short-term memory recurrent neural network architectures for large scale acoustic modeling. In: Fifteenth annual conference of the international speech communication association.




DOI: https://doi.org/10.30645/kesatria.v4i3.209

DOI (PDF): https://doi.org/10.30645/kesatria.v4i3.209.g208

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