SISTEM REKOMENDASI KONVERSI PROGRAM MSIB DENGAN MATA KULIAH PRODI INFORMATIKA ITN MALANG MENGGUNAKAN COSINE SIMILARITY
DOI:
https://doi.org/10.36080/skanika.v8i1.3325Keywords:
Sistem Rekomendasi, Pemrosesan Bahasa Alami, Cosine SimilarityAbstract
The Certified Independent Study and Internship Program (MSIB) is part of the Merdeka Belajar Kampus Merdeka (MBKM) initiative, allowing students to convert up to 20 credits from their activities. However, this process is often challenging as universities must match the MSIB syllabus with the curriculum syllabus of the Informatics Engineering program at ITN Malang. Differences in terminology and specific rules between the two syllabi make the process time-consuming and confusing. This study aims to develop a recommendation system to simplify the course conversion process. The system employs a Natural Language Processing (NLP) model based on Transformers to capture textual context and a cosine similarity algorithm to measure the similarity between syllabi. The system evaluation using classification metrics achieved an accuracy of 67%. The precision score reached 71% for the majority class and 50% for the minority class, while recall was 83% and 33%, respectively. The weighted average produced an f1-score of 0.65, indicating satisfactory performance despite class imbalance. These results demonstrate the system's potential to provide reliable recommendations, although further optimization is required to improve performance for the minority class.
Downloads
Download data is not yet available.
References
[1] Y. Januzaj and A. Luma, “Cosine Similarity – A Computing Approach to Match Similarity Between Higher Education Programs and Job Market Demands Based on Maximum Number of Common Words,” International Journal of Emerging Technologies in Learning, vol. 17, no. 12, pp. 258–268, 2022.
[2] T. P. Rinjeni, A. Indriawan, and N. A. Rakhmawati, “Matching Scientific Article Titles using Cosine Similarity and Jaccard Similarity Algorithm,” Procedia Computer Science, vol. 234, no. 2023, pp. 553–560, 2024.
[3] N. Febriyanti, D. P. Rini, and O. Arsalan, “Text Similarity Detection Between Documents Using Case Based Reasoning Method with Cosine Similarity Measure (Case Study SIMNG LPPM Universitas Sriwijaya),” Sriwijaya Journal of Informatics and Applications, vol. 3, no. 2, pp. 85–94, 2022.
[4] Rio Feriangga Kurniawan, “Implementasi Text Mining Menggunakan Metode Cosine Similarity Untuk Klasifikasi Konten Berita Di Postingan Grup Facebook Info Lantas Dan Kriminal Pasuruan,” JAMI: Jurnal Ahli Muda Indonesia, vol. 3, no. 1, pp. 9–17, 2022.
[5] H. S. Sutikno, “Implementasi Algoritma Cosine Similarity Untuk Mendeteksi Kemiripan Topik Judul,” Journal of Engineering, Computer Science and Information Technology (JECSIT), vol. 1, no. 1, pp. 51–61, 2021.
[6] M. J. Farrell, L. Brierley, A. Willoughby, A. Yates, and N. Mideo, “Past and future uses of text mining in ecology and evolution,” Proceedings of the Royal Society B: Biological Sciences, vol. 289, no. 1975, 2022, pp. 1-19.
[7] M. A. Julyananda, T. Yulianti, and D. Pasha, “Rancang Bangun Media Pembelajaran Matematika Menggunakan Metode Demonstrasi Untuk Kelas 1 Sekolah Dasar,” Jurnal Informatika dan Rekayasa Perangkat Lunak, vol. 3, no. 3, pp. 366–375, 2022.
[8] A. Sutanti, M. Komaruddin, P. Damayanti, and P. U. Studi Sistem Informasi Metro, “Rancang Bangun Aplikasi Perpustakaan Keliling Menggunakan Pendekatan Terstruktur,” Jurnal Ilmiah Komputer dan Informatika (KOMPUTA), vol. 9, no. 1, pp.366-375, 2022.
[9] A. Q. Surbakti, R. Hayami, and J. A. Amien, “Analisa Tanggapan Terhadap Psbb Di Indonesia Dengan Algoritma Decision Tree Pada Twitter,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 2, no. 2, pp. 91–97, 2021.
[10] S. Khairunnisa, A. Adiwijaya, and S. Al Faraby, “Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19),” Jurnal Media Informatika Budidarma, vol. 5, no. 2, pp. 406-416, 2021.
[11] J. Mantik, Y. R. Saputri, and H. Februariyanti, “Sentiment Analysis on Shopee E-Commerce Using the Naïve Bayes Classifier Algorithm,” Jurnal Mantik, vol. 6, no. 2, pp. 1349–1357, 2022.
[12] F. Amin, E. Nur Wahyudi, and B. Hartono, “Penerapan Kemiripan Dokumen pada Mesin Pencari Menggunakan Metode Hellinger,” Jurnal Rekayasa Industri (JRI), vol. 5, no. 2, pp. 118–125, 2023.
[13] M. D. Putri, A. Rahmat, and Y. Sanjaya, “The Use of Chunking Technique Combined with the Writing Is Thinking Technique to Control Students’ Cognitive Load When Learning About the Human Reproductive System,” KnE Social Sciences: International Conference on Matematics and Science Education (ICMScE 2022): Learning Materials and Modules, 2024, pp. 83–90.
[14] J. Risakotta, “Penerapan Chunking Strategy Untuk Meningkatkan Kemampuan Memahami Teks Dalam Bahasa Inggris Pada Smk Kesehatan Nusaniwe Ambon,” VOCATIONAL: Jurnal Inovasi Pendidikan Kejuruan, vol. 2, no. 4, pp. 327–334, 2023.
[15] D. Soyusiawaty, “Buku Ajar Pemrosesan Bahasa Alami,” Universitas Ahmad Dahlan, pp. 1–99, 2023.
[16] A. N. Oktavia, at al., “Implementasi Metode Natural Language Processing Dalam Studi Analisis,” Jurnal Ilmiah Ilmu Komputer dan Multimedia, vol. 2, no. 1, pp. 154–159, 2024.
[17] S. Islam et al., “A comprehensive survey on applications of transformers for deep learning tasks,” Expert Syst Appl, vol. 241, 2024.
[18] D. H. Putra, and G. W. I. Noto, “Implementasi Generative Pre-Trained Transformers 2 Untuk Mengoreksi Kesalahan Penulisan Bahasa Indonesia Pada Dokumen Jurnal,” Seminar Nasional Technopex-2023, Institute Teknologi Indonesia, 2023, pp. 318–323.
[19] H. Steck, C. Ekanadham, and N. Kallus, “Is Cosine-Similarity of Embeddings Really About Similarity?,” WWW 2024 Companion-Companion Proceedings of the ACM Web Conference, no. Llm, pp. 887–890, 2024.
[20] L. Meilina, I. N. S. Kumara, and I. N. Setiawan, “Literature Review Klasifikasi Data Menggunakan Metode Cosine Similarity dan Artificial Neural Network,” Majalah Ilmiah Teknologi Elektro, vol. 20, no. 2, pp. 307-314, 2021.
[21] D. G. S. Gogahu and T. Prasetyo, “Pengembangan Media Pembelajaran Berbasis E-Bookstory untuk Meningkatkan Literasi Membaca Siswa Sekolah Dasar,” Jurnal Basicedu, vol. 4, no. 4, pp. 1004–1015, 2020.
[22] S. A. Hicks et al., “On evaluation metrics for medical applications of artificial intelligence,” Sci Rep, vol. 12, no. 1, pp. 1–9, 2022.
[2] T. P. Rinjeni, A. Indriawan, and N. A. Rakhmawati, “Matching Scientific Article Titles using Cosine Similarity and Jaccard Similarity Algorithm,” Procedia Computer Science, vol. 234, no. 2023, pp. 553–560, 2024.
[3] N. Febriyanti, D. P. Rini, and O. Arsalan, “Text Similarity Detection Between Documents Using Case Based Reasoning Method with Cosine Similarity Measure (Case Study SIMNG LPPM Universitas Sriwijaya),” Sriwijaya Journal of Informatics and Applications, vol. 3, no. 2, pp. 85–94, 2022.
[4] Rio Feriangga Kurniawan, “Implementasi Text Mining Menggunakan Metode Cosine Similarity Untuk Klasifikasi Konten Berita Di Postingan Grup Facebook Info Lantas Dan Kriminal Pasuruan,” JAMI: Jurnal Ahli Muda Indonesia, vol. 3, no. 1, pp. 9–17, 2022.
[5] H. S. Sutikno, “Implementasi Algoritma Cosine Similarity Untuk Mendeteksi Kemiripan Topik Judul,” Journal of Engineering, Computer Science and Information Technology (JECSIT), vol. 1, no. 1, pp. 51–61, 2021.
[6] M. J. Farrell, L. Brierley, A. Willoughby, A. Yates, and N. Mideo, “Past and future uses of text mining in ecology and evolution,” Proceedings of the Royal Society B: Biological Sciences, vol. 289, no. 1975, 2022, pp. 1-19.
[7] M. A. Julyananda, T. Yulianti, and D. Pasha, “Rancang Bangun Media Pembelajaran Matematika Menggunakan Metode Demonstrasi Untuk Kelas 1 Sekolah Dasar,” Jurnal Informatika dan Rekayasa Perangkat Lunak, vol. 3, no. 3, pp. 366–375, 2022.
[8] A. Sutanti, M. Komaruddin, P. Damayanti, and P. U. Studi Sistem Informasi Metro, “Rancang Bangun Aplikasi Perpustakaan Keliling Menggunakan Pendekatan Terstruktur,” Jurnal Ilmiah Komputer dan Informatika (KOMPUTA), vol. 9, no. 1, pp.366-375, 2022.
[9] A. Q. Surbakti, R. Hayami, and J. A. Amien, “Analisa Tanggapan Terhadap Psbb Di Indonesia Dengan Algoritma Decision Tree Pada Twitter,” Jurnal CoSciTech (Computer Science and Information Technology), vol. 2, no. 2, pp. 91–97, 2021.
[10] S. Khairunnisa, A. Adiwijaya, and S. Al Faraby, “Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19),” Jurnal Media Informatika Budidarma, vol. 5, no. 2, pp. 406-416, 2021.
[11] J. Mantik, Y. R. Saputri, and H. Februariyanti, “Sentiment Analysis on Shopee E-Commerce Using the Naïve Bayes Classifier Algorithm,” Jurnal Mantik, vol. 6, no. 2, pp. 1349–1357, 2022.
[12] F. Amin, E. Nur Wahyudi, and B. Hartono, “Penerapan Kemiripan Dokumen pada Mesin Pencari Menggunakan Metode Hellinger,” Jurnal Rekayasa Industri (JRI), vol. 5, no. 2, pp. 118–125, 2023.
[13] M. D. Putri, A. Rahmat, and Y. Sanjaya, “The Use of Chunking Technique Combined with the Writing Is Thinking Technique to Control Students’ Cognitive Load When Learning About the Human Reproductive System,” KnE Social Sciences: International Conference on Matematics and Science Education (ICMScE 2022): Learning Materials and Modules, 2024, pp. 83–90.
[14] J. Risakotta, “Penerapan Chunking Strategy Untuk Meningkatkan Kemampuan Memahami Teks Dalam Bahasa Inggris Pada Smk Kesehatan Nusaniwe Ambon,” VOCATIONAL: Jurnal Inovasi Pendidikan Kejuruan, vol. 2, no. 4, pp. 327–334, 2023.
[15] D. Soyusiawaty, “Buku Ajar Pemrosesan Bahasa Alami,” Universitas Ahmad Dahlan, pp. 1–99, 2023.
[16] A. N. Oktavia, at al., “Implementasi Metode Natural Language Processing Dalam Studi Analisis,” Jurnal Ilmiah Ilmu Komputer dan Multimedia, vol. 2, no. 1, pp. 154–159, 2024.
[17] S. Islam et al., “A comprehensive survey on applications of transformers for deep learning tasks,” Expert Syst Appl, vol. 241, 2024.
[18] D. H. Putra, and G. W. I. Noto, “Implementasi Generative Pre-Trained Transformers 2 Untuk Mengoreksi Kesalahan Penulisan Bahasa Indonesia Pada Dokumen Jurnal,” Seminar Nasional Technopex-2023, Institute Teknologi Indonesia, 2023, pp. 318–323.
[19] H. Steck, C. Ekanadham, and N. Kallus, “Is Cosine-Similarity of Embeddings Really About Similarity?,” WWW 2024 Companion-Companion Proceedings of the ACM Web Conference, no. Llm, pp. 887–890, 2024.
[20] L. Meilina, I. N. S. Kumara, and I. N. Setiawan, “Literature Review Klasifikasi Data Menggunakan Metode Cosine Similarity dan Artificial Neural Network,” Majalah Ilmiah Teknologi Elektro, vol. 20, no. 2, pp. 307-314, 2021.
[21] D. G. S. Gogahu and T. Prasetyo, “Pengembangan Media Pembelajaran Berbasis E-Bookstory untuk Meningkatkan Literasi Membaca Siswa Sekolah Dasar,” Jurnal Basicedu, vol. 4, no. 4, pp. 1004–1015, 2020.
[22] S. A. Hicks et al., “On evaluation metrics for medical applications of artificial intelligence,” Sci Rep, vol. 12, no. 1, pp. 1–9, 2022.
Downloads
Published
2025-01-30
How to Cite
[1]
D. Fisabilillah, K. Auliasari, and Y. A. Pranoto, “SISTEM REKOMENDASI KONVERSI PROGRAM MSIB DENGAN MATA KULIAH PRODI INFORMATIKA ITN MALANG MENGGUNAKAN COSINE SIMILARITY”, SKANIKA, vol. 8, no. 1, pp. 83–94, Jan. 2025.
Issue
Section
Articles
