FALAH, ZULFA FAJRUL and , Fajar Suryawan, S.T, M.Eng.Sc.,Ph.D. (2021) Sistem Rekomendasi Pemilihan Dosen Pembimbing Tugas Akhir Dengan Metrik Cosine Similarity. Skripsi thesis, Universitas Muhammadiyah Surakarta.
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Abstract
The selection of a supervisor is an important thing and is one of the determinants of whether or not a student's final project research is successful. At this time the selection of supervisors at the location of this research is done manually. Students themselves make the selection of supervisors based on research sourced from existing data. Some come from classmates, some come from seniors who have graduated, some even choose a supervisor without any reason whether the chosen lecturer is suitable or not with interests and with the topic of the final project to be taken. The selection of the right supervisor will have a big impact on students, students will be more enthusiastic in doing the final project and it can be facilitated in conducting research because student interest and lecturer concentration are matched. In this study, the student's interest with the lecturer's interest was determined based on the data processing entered by the student in the form of title, abstract and keywords. This data is matched with the titles, abstracts and keywords of articles for prospective supervisors that have been published on Google Scholar. This recommendation system uses the content-based filtering method to produce a list of recommendations for the final project supervisor. Then use the cosine similarity algorithm to calculate how similar the topic proposed by students is to the lecturer's research. In building a website-based recommendation system, the author uses two web frameworks django as the backend and ReactJs as the frontend. This recommendation system is expected to produce recommendations for final project supervisors who have interests and expertise that match the topic of the final project that will be submitted by students.
| Item Type: | Karya ilmiah (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Cosine Similarity, sistem rekomendasi, web scraping, content-based filtering. |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General) |
| Divisions: | Fakultas Ilmu Komunikasi dan Informatika > Teknik Informatika |
| Depositing User: | ZULFA FAJRUL FALAH |
| Date Deposited: | 18 Nov 2021 02:38 |
| Last Modified: | 18 Nov 2021 02:38 |
| URI: | http://eprints.ums.ac.id/id/eprint/95928 |
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