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All Journal Repertoar Journal eProceedings of Engineering
Ilham Maulana, Muhammad
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Arts Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Music Sampling On A Keyboard Arranger For A Solo Organ Player Of Dangdut Music In Lumajang Ilham Maulana, Muhammad
Repertoar Vol 6 No 1 (2025)
Publisher : Universitas Negeri Surabaya

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Abstract

This study aims to: (1) analyze the sampling production process on arranger keyboards for single organ players of dangdut music in Lumajang Regency and (2) analyze the application of sampling on arranger keyboards. This study uses a descriptive qualitative method with data collection techniques through interviews, observation, and documentation. The results show that (1) the sampling production process consists of three main stages, namely pre-production (technical preparation and sound setting), production (recording, editing, mixing, and multisampling), and post-production (mastering and format conversion). These stages ensure optimal sound quality and provide flexibility for musicians in creating distinctive musical characters; (2) sampling is applied by converting the sampling results into a format recognized by the keyboard system, such as .WAV and .KMP. Sampling is applied through two methods: looping to produce style and sequencer for song play. With the features available on Korg Pa 600, musicians can apply sampling more easily and remix to harmonize with other instruments.
Klasifikasi Komentar Toxic Pada Sosial Media Menggunakan SVM, Information Gain dan TF-IDF Ilham Maulana, Muhammad; Muslim Lhaksmana, Kemas; Dwifebri, Mahendra
eProceedings of Engineering Vol. 10 No. 5 (2023): Oktober 2023
Publisher : eProceedings of Engineering

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Abstrak — Sosial media merupakan suatu bentuk perantara interaksi sosial secara online. Aplikasi media sosial pun sudah dalam banyak bentuk dan di dalam sosial media ini meskipun banyak hal positif yang dapat diambil, ada beberapa juga halhal negatif contoh nya toxic comment. Toxic comment sendiri tidaklah mudah untuk dideteksi secara manual, maka penelitian berencana untuk mengklasifikasikan toxic comment tersebut menggunakan machine learning. Beberapa penelitian untuk klasifikasi toxic comment sudah dilakukan, dalam beberapa penelitian tersebut digunakan metode Support Vector Machine. Dalam penelitian ini metode yang digunakan adalah Support Vector Machine (SVM) sebagai classifier, Information Gain sebagai feature selection dan TF- IDF sebagai feature extraction. Data-data yang dikumpulkan adalah melalui cuitan twitter beberapa pengguna di media sosial tersebut. Komentarkomentar tersebut dikumpulkan menjadi satu lalu diklasifikasikan menggunakan metode-metode yang sudah disebutkan.Kata kunci— Sosial media, Klasifikasi teks, Toxic comment, SVM
Co-Authors Dwifebri, Mahendra Muslim Lhaksmana, Kemas