Clustering Musik Rock Menggunakan Algoritma K-Means dan K- Medoids

Clustering is a data analysis technique used to group objects with similar attributes or characteristics. The goal of clustering is to uncover hidden structures or patterns in data without prior label or classification information. This study implements K-Means and KMedoids algorithms to analyze the "Top Hits Spotify from 2000-2019" dataset, clustering rock music based on audio track attributes to produce clusters and compare the results with high, medium, and low comparisons for each audio track feature. The analysis reveals significant variations in music characteristics and genres across different clusters. The KMeans algorithm generates two clusters: Cluster 1 (142 members) is dominated by rock, pop, and dance/electronic genres with high popularity and danceability, while Cluster 2 (83 members) includes rock, pop, and metal genres with prominent energy attributes. The KMedoids algorithm produces five clusters with higher diversification, where Cluster 5 (77 members) is dominated by rock, pop, and metal genres with high loudness, and Cluster 1 features rock, pop, hip-hop, and metal genres with the highest mode values, indicating consistent use of major or minor tones. These results reveal differences in genre preferences and music attributes, reflecting the complexity and diversity of the analyzed music data

Inventaire bibliographique des algues benthiques du littoral marocain. I. Chlorophyceae et Phaeophyceae

nventaire préliminaire des algues benthiques du littoral marocain. I. Chlorophyceae et Phaeophyceae. L'inventaire bibliographique des Chlorophyceae et Phaeophyceae marines benthiques du littoral marocain a révélé 213 espèces dont 93 Chlorophyceae (6 ordres, 15 familles et 31 genres) et 110 Phaeophyceae (11 ordres, 20 familles et 50 genres

Genreanalyse und Film : eine Arbeitsbibliographie

Die Bibliographie listet Artikel zur allgemeinen Problematik der Genres in Filmtheorie und -geschichte auf. Dabei werden auch einige allgemeine poetologische Arbeiten zum Generischen aufgeführt. Studien zu einzelnen Genres sind nur dann aufgeführt, wenn sie von allgemeinerem Interesse sind. Für Hinweise danke ich Ludger Kaczmarek, Angela Keppler und Jörg Schweinitz

From the mountains to the prairies and beyond the pale : American yodeling on early recordings

This sound review surveys yodeling in North American popular music, beginning with some of the earliest recordings on which it is featured. In order to better contextualize the recordings, I will also mention a few examples of sheet music with yodeling—items which are generally overlooked. My intention is to question why yodeling became attached to particular genres and how it functions in the construction of those genres. Indeed, two popular music genres—so-called hillbilly music and cowboy or Western music—made yodeling an important, if not identifying, component. The focus here is on yodeling’s connotations and associations and how these established expressive relationships between the moods, personae, and images of the songs

On the genre-fication of Music: a percolation approach (long version)

In this paper, we analyze web-downloaded data on people sharing their music library. By attributing to each music group usual music genres (Rock, Pop...), and analysing correlations between music groups of different genres with percolation-idea based methods, we probe the reality of these subdivisions and construct a music genre cartography, with a tree representation. We also show the diversity of music genres with Shannon entropy arguments, and discuss an alternative objective way to classify music, that is based on the complex structure of the groups audience. Finally, a link is drawn with the theory of hidden variables in complex networks.Comment: 7 pages, 5 figures, submitted to the proceedings of the 3rd International Conference NEXT-SigmaPh