PEMODELAN SISTEM REKOMENDASI CERDAS MENGGUNAKAN HYBRID DEEP LEARNING

Dewi, Kadek Cahya and Ciptayani, Putu Indah (2022) PEMODELAN SISTEM REKOMENDASI CERDAS MENGGUNAKAN HYBRID DEEP LEARNING. Jurnal Sistem Informasi dan Sains Teknologi, 4 (2). pp. 1-7. ISSN 2684-8260

[img] Text
PLT-Ac5-Pemodelan Sistem Reomendasi Cerdas.pdf

Download (527kB)
Official URL: https://trilogi.ac.id/journal/ks/index.php/SISTEK/...

Abstract

The current trend of technological development is intelligent systems. However, there is no research that combines the two deep learning methods on recommendation algorithms. It is important to model intelligent recommendation systems using hybrid deep learning This study aimed to obtain an optimal hybrid deep learning model on an intelligent recommendation system. This study used an experimental research approach. Data collection techniques included observation, online search and record datasets. The research stages consisted of: (a) literature review, (b) observation and online search, (c) modeling (d) prototyping and (e) testing. The model was a hybrid deep learning model consisting of two layers, namely the Self Organizing Map (SOM) layer and the Recurrent Neural Network (RNN) layer. This research used the Python programming language in the prototyping stage. Some libraries modules in python namely numpy, pandas, tensorflow, hard, torch, sklearn were used. Program tested with dataset from kaggle.com. The test results managed to improve performance by increasing the accuracy to 100%. It can be concluded that the SOM-RNN model can improve the performance of the intelligent recommendation system

Item Type: Article
Subjects: Matematika Dan Ilmu Pengetahuan Alam (MIPA) > Matematika > Ilmu Komputer
Ilmu Teknik > Teknik Elektro Dan Informatika > Teknik Informatika
Ilmu Teknik > Teknik Elektro Dan Informatika > Sistem Informasi
Ilmu Teknik > Teknik Elektro Dan Informatika > Teknologi Informasi
Divisions: Jurusan Administrasi Bisnis > Prodi Manajemen Bisnis Internasional > Publikasi
Depositing User: Kadek Cahya Dewi
Date Deposited: 30 Apr 2023 05:39
Last Modified: 30 Apr 2023 05:39
URI: http://repository.pnb.ac.id/id/eprint/5294

Actions (login required)

View Item View Item