Implementasi Pipeline ETL Otomatis Berbasis Container untuk Pengelolaan Data Komentar YouTube Kasus Gagal Ginjal di Indonesia

Authors

  • rafita kusuma University of Aisyiyah Yogyakarta
  • Tikaridha Hardiani University of ‘Aisyiyah Yogyakarta

DOI:

https://doi.org/10.32493/jtsi.v9i2.59043

Keywords:

ETL, Apache NiFi, YouTube API, container, gagal ginjal

Abstract

Data dari media sosial seperti YouTube memiliki potensi untuk mendukung analisis isu kesehatan, termasuk gagal ginjal, namun umumnya data masih tidak terstruktur dan memerlukan proses pengolahan. Penelitian ini bertujuan membangun pipeline Extract, Transform, Load (ETL) otomatis berbasis container menggunakan Apache NiFi untuk mengelola data komentar YouTube terkait isu gagal ginjal. Pipeline terdiri dari Apache NiFi sebagai pengelola aliran data, Python_processor untuk transformasi, MySQL sebagai basis data, dan phpMyAdmin sebagai antarmuka pengelolaan. Proses ETL meliputi pengambilan data melalui YouTube API, pembersihan dan normalisasi teks, serta penyimpanan ke dalam database terstruktur. Hasil implementasi menunjukkan bahwa pipeline mampu memproses data dengan waktu kurang dari satu detik dan throughput sebesar 0,1972 MB/s. Evaluasi penggunaan sumber daya menunjukkan bahwa Apache NiFi menggunakan CPU sebesar 38,27% dan memori 1,03 GB, sedangkan container lain menggunakan sumber daya lebih rendah. Meskipun masih terdapat keterbatasan pada normalisasi teks di tahap transformasi, pipeline ETL yang dibangun mampu menghasilkan data yang lebih rapi dan terstruktur untuk analisis lanjutan.

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Published

2026-04-30

How to Cite

kusuma, rafita, & Hardiani, T. (2026). Implementasi Pipeline ETL Otomatis Berbasis Container untuk Pengelolaan Data Komentar YouTube Kasus Gagal Ginjal di Indonesia. Jurnal Teknologi Sistem Informasi Dan Aplikasi, 9(2), 149–159. https://doi.org/10.32493/jtsi.v9i2.59043

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Vol. 9 No. 2 (2026): Jurnal Teknologi Sistem Informasi dan Aplikasi

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