Machine Learning Journal Article Recommendation System Using Content Based Filtering

Afika Rianti, Nuur Wachid Abdul Majid, Ahmad Fauzi

Abstract


Indonesia is a country that hasn’t studied much about artificial intelligence. This has resulted in a small number of publications related to that field including areas within such as machine learning. For that reason, it caused difficulties in finding relevant journal articles. The purpose of this study is to know the performance of the Content Based Filtering method in providing machine learning journal article recommendations. The research procedure used is CRISP-DM with algorithms used are TF-IDF and Cosine Similarity. The dataset used consists of 100 machine learning journal articles. Based on the research that has been done, it’s concluded that the performance of the Content Based Filtering method in providing machine learning journal article recommendations as measured using the precision evaluation matrix showed a score of 76%, which means the result is quite good. However, the model couldn’t be used properly for some data due to the small number of datasets which affects the limited recommendations. 


Full Text:

PDF

References


Y. Devianto and S. Dwiasnati, "Kerangka Kerja Sistem Kecerdasan Buatan dalam Meningkatkan Kompetensi Sumber Daya Manusia Indonesia," Jurnal Telekomunikasi dan Komputer, vol. 10, no. 1, pp. 19–24, 2020. Accessed: Mar. 20, 2023. [Online]. Available: https://doi.org/10.22441/ incomtech.v10i1.7460

R. S. Santos and L. Qin, "Risk Capital and Emerging Technologies: Innovation and Investment Patterns Based on Artificial Intelligence Patent Data Analysis," Risk Financial Manage., vol. 12, no. 4, 2019. Accessed: Mar. 20, 2023. [Online]. Available: https://doi.org/ 10.3390/jrfm12040189

R. I. Harbani. "3 Jurusan Ini Langka, tapi Bagaimana Prospek Kerjanya?" detikedu. https://www.detik.com/edu/perguruan-tinggi/d-5755063/3-jurusan-ini-langka-tapi-bagaimana-prospek-kerjanya (Accessed: Mar. 20, 2023)

V. Natasha. "Jurusan Teknik Robotika dan Kecerdasan Buatan di Indonesia," myskill. https://blog.myskill.id/masa-kuliah/fakta-jurusan-robotika-kecerdasan-buatan/ (Accessed: Mar. 21, 2023).

PDDikti. "Mekatronika dan Kecerdasan Buatan Kampus Purwakarta," https://pddikti.kemdikbud. go.id/data_prodi/MDVFODM1N0YtOUZEMi00NzIyLUE2QTctOTc4MTVERUYyRkJF/20211 (Accessed: Mar. 20, 2023)

A. Rianti, S. Widodo, A. D. Ayuningtyas, and F. B. Hermawan, "Next Word Prediction Using LSTM," Inf. Technol. Its Utilization, vol. 5, no. 1, 2022. Accessed: Mar. 20, 2023. [Online]. Available: https://doi.org/10.30818/jitu.5.1.4748

“SINTA - Science and Technology Index,” https://sinta.kemdikbud.go.id/journals/index/?q=machine+learning (: Jan. 24, 2024)

P. M. Alamdari, N. J. Navimipour, M. Hosseinzadeh, A. A. Safaei and A. Darwesh, "A Systematic Study on the Recommender Systems in the E-Commerce," in IEEE Access, vol. 8, pp. 115694-115716, 2020, doi: 10.1109/ ACCESS.2020.3002803

A. H. Khan, J. Siddqui, and S. S. Sohail, “A Survey of Recommender Systems Based on Semi-Supervised Learning,” in Advances in Intelligent Systems and Computing, 2021, pp. 319–327. doi: 10.1007/978-981-16-3071-2_27. Available: https://doi.org/10.1007/978-981-16-3071-2_27

S. K. Jaiswal and S. Agarwal, "Recommendation Systems: A Deep Survey for New Insights and Directions," Dogo Rangsang, vol. 12, no. 10, pp. 154–160, Oct. 2022. Accessed: Mar. 20, 2023. [Online]. Available: https://www.journal- dogorangsang.in/no_2_Online_22/45_oct.pdf

M. Chiny, M. Chihab, O. Bencharef, and Y. Chihab, “Netflix Recommendation System based on TF-IDF and Cosine Similarity Algorithms,” Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning (BML 2021), pp. 15–20, Jan. 2021, doi: 10.5220/0010727500003101

C. Channarong, C. Paosirikul, S. Maneeroj and A. Takasu, "HybridBERT4Rec: A Hybrid (Content-Based Filtering and Collaborative Filtering) Recommender System Based on BERT," in IEEE Access, vol. 10, pp. 56193-56206, 2022, doi: 10.1109/ACCESS.2022.3177610

A. Pramarta and Z. K. A. Baizal, “Hybrid Recommender System Using Singular Value Decomposition and Support Vector Machine in Bali Tourism,” JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), vol. 7, no. 2, pp. 408–418, May 2022, doi: 10.29100/jipi.v7i2.2770. Available: https://doi.org/10.29100/jipi.v7i2.2770

P. Nastiti, “Penerapan Metode Content Based Filtering Dalam Implementasi Sistem Rekomendasi Tanaman Pangan”, teknika, vol. 8, no. 1, pp. 1-10, Jun. 2019

F. B. A. Larasati and H. Februariyanti, “Sistem Rekomendasi Produk EMINA Cosmetics dengan Menggunakan Metode Content-Based Filtering,” MISI (Jurnal Manajemen Informatika dan Sistem Informasi), vol. 4, no. 1, p. 45, Jan. 2021, doi: 10.36595/misi.v4i1.250. Available: https://doi.org/10.36595/misi.v4i1.250

R. Andriani, “Fitur Rekomendasi Artikel Ilmiah pada Open Journal System Menggunakan Content Based Filtering,” Undergraduate Dissertation, Universitas Sebelas Maret, 2019

M. Alkaff, H. Khatimi, and A. Eriadi, “Sistem Rekomendasi Buku pada Perpustakaan Daerah Provinsi Kalimantan Selatan Menggunakan Metode Content-Based Filtering”, MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 20, no. 1, pp. 193-202, Sep. 2020

M. R. A. Zayyad, “Sistem Rekomendasi Buku Menggunakan Metode Content Based Filtering,” Undergraduate Dissertation, Universitas Islam Indonesia, 2021

S. Sharma, R. Vijay, and M. Malhotra, “Automatic Recommendation System based on Hybrid Filtering Algorithm,” Education and Information Technologies, vol. 27, no. 2, pp. 1523–1538, Jul. 2021, doi: 10.1007/s10639-021-10643-8. Available: https://doi.org/10.1007/s10639-021-10643-8

M. M. Najafabadi, F. Villanustre, T. M. Khoshgoftaar, N. Seliya, R. Wald, and E. Muharemagic, “Deep Learning Applications and Challenges in Big Data nalytics,” Journal of Big Data, vol. 2, no. 1, Feb. 2015, doi: 10.1186/s40537-014-0007-7. Available: https://doi.org/10.1186/s40537-014-0007-7

J. A. Solano, D. J. L. Cuesta, S. F. U. Ibanez, and J. R. Coronado-Hernandez, "Predictive Models Assessment on CRISP-DM Methodology for Students Performance in Colombia - Saber 11 Test," Procedia Computer Science, vol. 198, pp. 512–517, 2022. Accessed: Mar. 20, 2023. [Online]. Available: https://doi.org/10.1016/j.procs. 2021.12.278

A. Rianti, N. W. A. majid, and A. Fauzi, “CRISP-DM: Metodologi Proyek Data Science,” Jul. 25, 2023. Available: https://ojs.udb.ac.id/index.php/Senatib/article/view/3015

A. Zernig, A. Pandeshwar, R. Kern, and M. Rauch, "Machine Learning and Automated Decision Making," in SemI40 Project Prospective: Industry 4.0 Evolution Revolution, Austria. SemI40 Consortium, 2019, pp. 58–75. Accessed: Mar. 20, 2023. [Online]. Available: https://www. researchgate.net/publication/337592264_A_SemI40_Project_ Prospective_-_Industry40_from_Evolution_to_Revolution

N. T. M. Sagala and F. Y. Aryatama, "Exploratory Data Analysis (EDA): A Study of Olympic Medallist," Sistemasi: Jurnal Sistem Informasi, vol. 13, no. 3, pp. 578–587, 2022. Accessed: Mar. 20, 2023. [Online]. Available: http://sistemasi. ftik.unisi.ac.id/index.php/stmsi/article/view/1857

Z. L. Chia, M. Ptaszynski, F. Masui, G. Leliwa, and M. Wroczynski, "Machine Learning and Feature Engineering-based Study Into Sarcasm and Irony Classification with Application to Cyberbullying Detection," Inf. Process. & Manage., vol. 58, no. 4, 2021. Accessed: Mar. 20, 2023. [Online]. Available: https://www. sciencedirect.com /science/article/abs/pii/ S0306457321000984

C. Schröer, F. Kruse, and J. M. Gómez, "A Systematic Literature Review on Applying CRISP-DM Process Model," Procedia Computer Science, vol. 181, pp. 526–534, 2021. Accessed: Mar. 20, 2023. [Online]. Available: https://doi.org/10.1016/j.procs.2021.01.199

C. A. Melyani, "Sistem Rekomendasi Hotel dengan Pendekatan Content Based Filtering," bachelor's thesis, Universitas Islam Indonesia, 2022. Accessed: Mar. 20, 2023. [Online]. Available: https://dspace.uii.ac.id/handle/ 123456789/39737

M. Alkaff, H. Khatimi, and A. Eriadi, “Sistem Rekomendasi Buku pada Perpustakaan Daerah Provinsi Kalimantan Selatan Menggunakan Metode Content-Based Filtering”, MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 20, no. 1, pp. 193-202, Sep. 2020

J. A. Septian, T. M. Fachrudin, and A. Nugroho, “Analisis Sentimen Pengguna Twitter Terhadap Polemik Persepakbolaan Indonesia Menggunakan Pembobotan TF-IDF dan K-Nearest Neighbor”, INSYST, vol. 1, no. 1, pp. 43–49, Aug. 2019

F. A. Nugroho, F. Septian, D. A. Pungkastyo, and J. Riyanto, "Penerapan Algoritma Cosine Similarity untuk Deteksi Kesamaan Konten pada Sistem Informasi Penelitian dan Pengabdian Kepada Masyarakat," Jurnal Informatika Universitas Pamulang, vol. 5, no. 4, pp. 529–536, 2020. Accessed: Mar. 20, 2023. [Online]. Available: https://doi.org/10.32493/informatika. v5i4.7126

A. L. Rihani, A. Maksum, and N. Nurhasanah, "Studi Literatur : Media Interaktif Terhadap Hasil Belajar Peserta Didik Kelas V Sekolah Dasar," Jurnal Kajian Pendidikan dasar, vol. 7, no. 2, pp. 123–131, 2022. Accessed: Mar. 20, 2023. [Online]. Available: https://journal.unismuh.ac.id/index.php/ jkpd/article/view/7702/5030

M. Canesche, L. Bragança, O. P. V. Neto, J. A. Nacif and R. Ferreira, "Google Colab CAD4U: Hands-On Cloud Laboratories for Digital Design," 2021 IEEE International Symposium on Circuits and Systems (ISCAS), Daegu, Korea, 2021, pp. 1-5, doi: 10.1109/ISCAS51556.2021.9401151

J. Enterprise, Python untuk Programmer Pemula. Jakarta: PT Elex Media Komputindo, 2019. Accessed: Mar. 20, 2023.

Z. Fayyaz, M. Ebrahimian, D. Nawara, A. Ibrahim, and R. Kashef, “Recommendation Systems: Algorithms, Challenges, Metrics, and Business Opportunities,” Applied Sciences, vol. 10, no. 21, p. 7748, Nov. 2020, doi: 10.3390/app10217748




DOI: http://dx.doi.org/10.12962/j24068535.v22i1.a1193

Refbacks

  • There are currently no refbacks.