Utilization Of TF-IDF Weighting In Song Search System  Based On Spotify Lyrics

Nelti Juliana Sahera; Eviriawan; Hikma; Syaban Barokah Nur Ilahi

doi:10.59934/jaiea.v4i3.1079

Authors

Nelti Juliana Sahera Universitas Halu Oleo
Eviriawan Universitas Halu Oleo
Hikma Universitas Halu Oleo
Syaban Barokah Nur Ilahi Universitas Halu Oleo

DOI:

https://doi.org/10.59934/jaiea.v4i3.1079

Keywords:

relevance, search system, song lyrics, song title, spotify, TF-IDF

Abstract

In the rapidly developing digital era, the need for an efficient information retrieval system is increasing. Spotify, as one of the largest music streaming platforms, faces challenges in providing a fast and accurate song search system. Improving user experience in searching for song titles based on lyrics is the main focus in developing a search system on the music streaming platform. like Spotify. Study This explore use method weighting using TF-IDF (Term Frequency- Inverse Document Frequency) to optimize the search for song titles through lyrics. By applying TF-IDF, system can assess and weighting words in lyrics based on the frequency in One song and its uniqueness in gathering song data in overall. As for the data that used in this study totaling 30 entries. The methods used include system design, preprocessing (data cleaning, tokenization, filtering, and stemming), and TF-IDF weighting. The test results show that this approach significantly improves the relevance and accuracy of search results, making it easier for users to find the appropriate song title. with lyrics Which they remember. System Which proposed This expected can repair quality search services on Spotify and provide a more satisfying experience for users.

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References

G. Widianto Aldiansyah, P. Pandu Adikara, and R. Cahya Wihandika, “Cross Language Song Recommendation Based on Lyrics Using Word2VEC,” Journal of Information Technology and Computer Science Development , vol. 3, no. 8, pp. 8036–8041, 2019, [Online]. Available: http://j-ptiik.ub.ac.id

TF Keita Nakamura, “Music recommendation system using lyric network,” Global Conference on Consumer Electronics , 2017.

A. Tirtana, A. Zulkarnain, YD Listio, and S. Malang, “Creating a Job Search System Using TF-IDF,” Asian Information Technology Scientific Journal , vol. 13, no. 2, 2019.

IFA Arif Amrulloh, “Final Project Title Similarity Search System Using TF-IDF Method,” CoreIT Journal: Journal of Computer Science and Information Technology Research Results , vol. 7, no. 2, p. 58, Dec. 2021, doi: 10.24014/coreit.v7i2.15338.

F. Pribadi and R. Munir, “Implementation of Graph Vertex Coloring with Welch Powell Algorithm and Depth First Search Algorithm on Angklung Playing Turn Distribution,” CoreIT Journal: Journal of Computer Science and Information Technology Research Results , vol. 7, no. 2, p. 58, Dec. 2021, doi: 10.24014/coreit.v7i2.15338.

ANR Adhimas Yanto Timur, “ Indonesian Song Recommendation System Using Content-Based Filtering and Cosine Similarity Methods,” Journal of Informatics and Applied Electrical Engineering , vol. 13, no. 1, Jan. 2025, doi: 10.23960/jitet.v13i1.5949.

I. Tri Hapsari, B. Satria Andoko, and C. Rahmad, “ Information Retrieval Application for Research Report Document Search,” Polinema Informatics Journal , vol. 1, no. 3, pp. 2407–070, 2015.

F. Sarito Sinaga and B. Rahayudi, “Song Lyrics Emotion Classification using Improved K-Nearest Neighbor with Feature Selection and BM25,” Journal of Information Technology and Computer Science Development , vol. 3, no. 6, pp. 5697–5702, 2019, [Online]. Available: http://j-ptiik.ub.ac.id

MA Lestari, PP Adikara, and S. Adinugroho, “Song Recommendation Based on Lyrics and Song Genre Using Word Embedding Method (Word2Vec),” Journal of Information Technology and Computer Science Development , vol. 3, no. 8, pp. 2548–964, 2019, [Online]. Available: http://j-ptiik.ub.ac.id

IP Sari, F. Febriyanti, TA Ujung, and FL Barus, “Analysis of Connotative Meaning in the Lyrics of the Song Bertaut by Nadin Amizah,” Diksa: Indonesian Language and Literature Education , vol. 7, no. 1, pp. 22–32, Jun. 2021, doi: 10.33369/diksa.v7i1.15891.

B. Hakim, “ Sentiment Analysis of Text Data Preprocessing in Data Mining with Using Machine Learning," JBASE - Journal of Business and Audit Information Systems , vol. 4, no. 2, Aug. 2021, doi : 10.30813/ jbase.v 4i2.3000.

NP Yunita and P. Correspondence , “ Application Hadith Search Using Vector Space Model With Weighting Tf-Idf Dan Confix -Stripping Stemmer Hadith Search Application Using The Vector Space Model With Tf-Idf Weighting And Confix -Stripping Stemmer,” Journal Technology Information and Knowledge Computer (JTIIK) , vol. 10, no. 3, pp. 665–676, 2023, doi : 10.25126/jtiik.2023106736.

M. Noveanto, H. Sastypratiwi, and H. Muhardi, “Test of Emotion Classification Accuracy in Indonesian Song Lyrics,” Journal of Information Systems and Technology (JustIN) , vol. 10, no. 3, p. 311, Nov. 2022, doi: 10.26418/justin.v10i3.56804.

Q. Qi, DJ Hessen, T. Deoskar , and PGM Van Der Heijden, “A comparison of latent semantic analysis and correspondence analysis of document-term matrices,” Nat Lang Eng , vol. 8, no. 10, May 2023, doi : 10.1017/S1351324923000244.

SAN Alexandropoulos, SB Kotsiantis , and MN Vrahatis , “Data preprocessing in predictive data mining,” Knowledge Engineering Review , vol. 34, 2019, doi : 10.1017/S026988891800036X.

F. Rahutomo, F. Rozi, PN Mirzha, T. Informatika, and PN Malang, “ Evaluation of the Implementation of the Improved K-Nearest Neighbor Algorithm in Categorizing Indonesian Song Lyrics According to Age,” JIP (Polinema Informatics Journal) , 2020.

F. Amin, “ Implementation of Search Engine Using Vector Space Model Method,” Engineering Dynamics , pp. 45–58, Jan. 2011.

LW Astuti, A. Rachmat C., and Y. Lukito, “ Implementation of Naïve Bayes Algorithm Using Isear for Classification of Emotions in English Song Lyrics,” Jurnal Informatika , vol. 14, no. 1, May 2017, doi: 10.9744/informatika.14.1.16-21.