PEMODELAN SISTEM REKOMENDASI CERDAS MENGGUNAKAN HYBRID DEEP LEARNING

Kadek Cahya Dewi, Putu Indah Ciptayani

Abstract


Trend perkembangan teknologi saat ini adalah mengarah ke sistem cerdas. Namun saat ini belum ada yang menggabungkan dua metode deep learning pada algoritma rekomendasi, sehingga penting untuk melakukan pemodelan sistem rekomendasi cerdas menggunakan hybrid deep learning. Penelitian ini bertujuan untuk mendapatkan model hybrid deep learning yang optimal pada sistem rekomendasi cerdas. Penelitian ini menggunakan pendekatan penelitian eksperimen. Teknik pengumpulan data yang digunakan meliputi observasi, penelusuran online dan pencatatan dataset. Tahapan penelitian terdiri dari: (a) literature review, (b) observasi dan pencarian online, (c) modeling (d) prototyping dan (e) testing. Model yang dihasilkan merupakan model hybrid deep learning yang terdiri dari dua layer yaitu layer Self Organizing Map (SOM) dan layer Recurrent Neural Network (RNN). Penelitian ini menggunakan bahasa pemrograman Python pada tahap pembuatan prototipe. Beberapa modul library dalam python yang digunakan antara lain numpy, pandas, tensorflow, hard, torch, sklearn. Program diuji dengan dataset dari kaggle.com. Hasil pengujian berhasil meningkatkan kinerja dengan meningkatkan akurasi hingga 100%. Dapat disimpulkan bahwa model SOM-RNN dapat meningkatkan kinerja sistem rekomendasi cerdas.

Keywords


Deep Learning; Hybrid Deep Learning; Intelligent Recommendation Systems; Recommendation Systems

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References


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DOI: https://doi.org/10.31326/sistek.v4i2.1157

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