Utilization Of TF-IDF Weighting In Song Search System Based On Spotify Lyrics
Nelti Juliana Sahera, Eviriawan, Hikma, Syaban Barokah Nur Ilahi · Journal of Artificial Intelligence and Engineering Applications (JAIEA) · 2025
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.