Literatur Review: Penerapan Deep Reinforcement Learning  Dalam Business Intelligence

Muhammat Rasid Ridho; Nofriani Fajrah; Fifi Fifi

doi:10.58520/jddat.v3i2.58

Authors

Muhammat Rasid Ridho Universitas Putera Batam
Nofriani Fajrah Universitas Putera Batam
Fifi Fifi Universitas Putera Batam

DOI:

https://doi.org/10.58520/jddat.v3i2.58

Keywords:

Deep Reinforcement Learning, Business Intelligence

Abstract

Business Intelligence merupakan kombinasi alat, seperti gudang data, pemrosesan analitis online (OLAP), dan dasbor. Gudang data mengumpulkan data yang akurat, bersih, dan terperinci dari berbagai sumber untuk analisis mendalam, sementara pemrosesan analitis online (OLAP) mendukung analisis multidimensi secara real-time dan memungkinkan pengguna menerapkan operasi seperti agregasi, pemfilteran, pengguliran, dan penelusuran. Peneliti mencoba menerapkan Deep Reinforcement Learning (DRL). DRL merupakan teknik yang menjanjikan untuk memecahkan masalah dunia nyata. Hal ini dapat digunakan untuk mengatasi tantangan yang biasa dihadapi dalam tugas pengambilan keputusan berurutan, seperti ketidakpastian dan dimensi variabel. Metode deep learning yang dapat digunakan untuk Business Intelligence antara lain deep neural network (DNN). Model DNN ini menjanjikan kinerja prediksi yang melampaui model pembelajaran mesin tradisional. Adapun temuannya Double Deep Q Learning dapat digunakan untuk meningkatkan kecerdasan bisnis dengan mengoptimalkan pemanfaatan sumber daya dan mengurangi waktu kalkulasi dalam masalah pengemasan persegi panjang skala besar. Ini juga dapat digunakan untuk pemodelan lawan dalam sistem multi-agen, yang memungkinkan identifikasi berbagai pola strategi lawan.

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