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"placement": 9, "docid": 328212, "security": "staffonly", "format": "text", "rev_number": 2, "uri": "http:\/\/eprints.amikom.ac.id\/id\/document\/328212", "main": "Publikasi.pdf", "pos": 9 } ], "divisions": [ "sch_phy" ], "full_text_status": "restricted", "thesis_name": "skripsi", "corp_creators": [ "Universitas AMIKOM Yogyakarta" ], "metadata_visibility": "show", "title": "KLASIFIKASI PREFERENSI MUSIK GENERASI Z\r\nBERDASARKAN FITUR AUDIO SPOTIFY\r\nMENGGUNAKAN ALGORITMA\r\nRANDOM FOREST", "ispublished": "pub", "creators": [ { "nim": "22.12.2479", "name": { "given": "Ni Made", "honourific": null, "lineage": null, "family": "Supartini" } } ], "date_type": "published", "type": "thesis", "eprint_status": "archive", "userid": 12, "eprintid": 32932, "status_changed": "2026-09-23 02:21:24", "subjects": [ "000.000.006" ], "date": "2026-02-25", "abstract": "Transformasi digital mengubah masyarakat dalam mengakses dan\r\nmenikmati musik melalui platform streaming seperti Spotify yang menyediakan\r\nberbagai fitur audio sebagai representasi karakteristik lagu. Ketersediaan data\r\nberbasis fitur audio seperti danceability, tempo, energy, dan speechiness\r\nmendukung proses analisis musik dilakukan secara lebih sistematis dan objektif.\r\nPada Generasi Z, preferensi musik tidak hanya dipengaruhi oleh label genre, tetapi\r\njuga oleh karakteristik audio suasana dan pola konsumsi musik yang dinamis. \r\n Penelitian ini bertujuan untuk mengklasifikasi preferensi musik Generasi Z\r\nberdasarkan fitur audio menggunakan algoritma Random Forest. Dataset yang\r\ndigunakan merupakan data lagu yang diperoleh dari Spotify Track Dataset dan\r\nSpotify Web API dengan rentang tahun 2015 hingga 2025 dan difokuskan pada\r\nempat genre utama, yaitu Pop, K-pop, Hip-hop dan R&B. Proses penelitian meliputi\r\ntahapan penelitian pengumpulan data, Exploratory Data Analysis (EDA), prapemrosesan,\r\n\r\nanalisis data pembangunan model, serta evaluasi model. Algoritma\r\nRandom Forest dipilih karena kemampuannya dalam mengolah data dengan\r\njumlah variabel yang cukup besar serta menghasilkan model klasifikasi yang stabil. \r\nHasil penelitian ini menunjukkan bahwa model Random Forest memiliki\r\nperforma yang sangat baik dalam mengklasifikasi preferensi musik Generasi Z.\r\nModel baseline memperoleh akurasi sebesar 94% dan meningkatkan menjadi 95%\r\nsetelah dilakukan proses hyperparameter tuning. Nilai precision, recall, dan F1score\r\n\r\nyang tinggi menunjukkan bahwa model memiliki kemampuan klasifikasi\r\ndengan tingkat kekeliruan antar kelas rendah. Dengan demikian, model yang\r\ndihasilkan dapat digunakan secara efektif dalam mengklasifikasi preferensi musik\r\nberbasis fitur audio.", "lastmod": "2026-09-23 02:21:24" }