Optimasi Rekomendasi Sustainable Development Goals (SDGs) di Indonesia menggunakan Content-Based Filtering dan Algoritma Machine Learning


  • Alfajri Hulvi * Mail Universitas Amikom Yogyakarta, Indonesia
  • Kusrini Kusrini Universitas Amikom Yogyakarta, Indonesia
  • (*) Corresponding Author
Keywords: SDGs; Content-Based Filtering; Machine Learning; Deep Learning

Abstract

AbstrakLahirnya program tentang Tujuan Pembangunan Berkelanjutan atau Sustainable Development Goals (SDGs) pada tahun 2015 membuat masyarakat di semua negara mulai memandang penting pembangunan berkelanjutan untuk diimplementasikan. Indonesia, sebagai bagian dari komunitas global, juga telah mengadopsi SDGs ini sebagai kerangka kerja dalam upaya mencapai Indonesia Emas 2045. Dengan visi ini, Indonesia bercita-cita menjadi negara maju yang berdaulat, adil, dan makmur tepat pada peringatan 100 tahun kemerdekaannya. Untuk mencapai tujuan secara efektif, penting untuk menerapkan sistem rekomendasi berbasis Artificial Intelligence (AI) yang mempertimbangkan tantangan sosial, ekonomi, dan lingkungan hidup yang dihadapi oleh negara Indonesia di masa mendatang. Content-Based Filtering (CBF) adalah teknik yang populer untuk membangun sistem tersebut.  Penelitian ini membahas teknik untuk optimasi CBF menggunakan beberapa algoritma machine learning tradisional yaitu SVM, KNN, DT dan algoritma Deep Learning yaitu MLP. Teknik pengambilan sample dan penyetelan hiperparameter juga diperhatikan dalam penelitian ini. Algoritma Deep Learning MLP menghasilkan akurasi tertinggi yaitu 84%.

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Article History
Submitted: 2024-08-17
Published: 2024-09-12
Abstract View: 40 times
PDF Download: 23 times
How to Cite
Hulvi, A., & Kusrini, K. (2024). Optimasi Rekomendasi Sustainable Development Goals (SDGs) di Indonesia menggunakan Content-Based Filtering dan Algoritma Machine Learning. Building of Informatics, Technology and Science (BITS), 6(2), 1045-1058. https://doi.org/10.47065/bits.v6i2.5807
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