Yuliana, Shinta Triya (2020) ANALISIS SENTIMEN LIRIK LAGU INDONESIA DENGAN METODE K-NEAREST NEIGHBOR. Undergraduate thesis, Universitas Stikubank.
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Abstract
Lirik lagu merupakan ekspresi sesorang mengenai sesuatu hal yang telah dilihat, didengar maupun dialaminya. Lirik lagu sendiri mengandung dua sentimen, yaitu diantaranya sentimen positif dan sentimen negatif. Adanya penelitian ini bertujuan untuk mengklasifikan lirik lagu Indonesia kedalam sentimen positif maupun sentimen negatif. Data yang diperoleh dari berbagai website yang menyediakan lirik lagu Indonesia dengan jumlah 150 data lirik lagu yang kemudian data tersebut disimpan dalam format csv dan diimport dengan menggunakan Github agar mempermudah proses klasifikasi. Klasifikasi sendiri merupakan suatu proses untuk memprediksi suatu objek yang akan diteliti. Tahap preprocessing yang dilakukan adalah Case Folding, Tokenizing, Stopword Removal dan Stemming. Algoritma klasifikasi yang digunakan dalam penelitian ini yaitu K-Nearest Neighbor. Hasil akurasi yang didapatkan dengan menggunakan algoritma ini sebesar 0.60 atau 60% dengan data test berjumlah 30 data lirik lagu. Dalam penelitian ini menggunakan bahasa pemrograman Python serta Google Colabs sebagaitools. Song lyrics are an expression of someone about something that has been seen, heard or experienced. The song lyrics themselves contain two sentiments, including positive and negative sentiments. The existence of this study aims to classify the lyrics of Indonesian songs into positive sentiments and negative sentiments. Data obtained from various websites that provide Indonesian song lyrics with 150 song lyric data are then stored in CSV format and imported using Github to facilitate the classification process. Classification itself is a process for predicting an object that will be examined. The preprocessing stage is Case Folding, Tokenizing, Stopword Removal and Stemming. The classification algorithm used in this study is K-Nearest Neighbor. Accuracy results obtainedbyxvii Using this algorithm are 0.06 or 60% with 30 test data of song lyrics.In this study using the Python programming language and Google Colabs as tools
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | NIM.16.01.53.0085 SKR.I.05.01.1906 |
| Uncontrolled Keywords: | Klasifikasi, Lirik Lagu, K-Nearest Neighbor, Python. Classification,Song Lyrics,K-Neighbor,Python |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Faculty / Institution: | Fakultas Teknologi Informasi > Program Studi Teknik Informatika |
| Depositing User: | H Hayati |
| Date Deposited: | 10 Sep 2020 07:59 |
| Last Modified: | 10 Sep 2020 07:59 |
| URI: | https://eprints.unisbank.ac.id/id/eprint/7074 |
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