PERANCANGAN MODEL TWO-TOWER PADA SISTEM REKOMENDASI APLIKASI MARKETPLACE PASAR HASIL BUMI

M. Naufaldi Fadhlirrahman, . (2025) PERANCANGAN MODEL TWO-TOWER PADA SISTEM REKOMENDASI APLIKASI MARKETPLACE PASAR HASIL BUMI. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

[img] Text
ABSTRAK.pdf

Download (2MB)
[img] Text
AWAL.pdf

Download (2MB)
[img] Text
BAB 1.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
BAB 2.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
BAB 3.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
BAB 4.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
BAB 5.pdf

Download (1MB)
[img] Text
DAFTAR PUSTAKA.pdf

Download (1MB)
[img] Text
RIWAYAT HIDUP.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
LAMPIRAN.pdf
Restricted to Repository UPNVJ Only

Download (2MB)
[img] Text
HASIL PLAGIARISME.pdf
Restricted to Repository staff only

Download (12MB)
[img] Text
ARTIKEL KI.pdf
Restricted to Repository staff only

Download (411kB)

Abstract

Pasar Hasil Bumi is a marketplace platform focused on the sale of agricultural products by women farmer groups (Kelompok Wanita Tani) in the Tangerang area. As a newly developed platform, it has not yet implemented a recommendation system to enhance user experience and boost sales performance. This study aims to design and evaluate a recommendation system for the platform using a deep learning approach based on the two-tower model architecture. The model is designed to learn user and product representations separately in the form of embeddings, which are then used in the retrieval process to identify relevant product recommendations. Evaluation was carried out using Recall@K and Precision@K metrics at various values of K. The results show that the model achieved relatively high Recall@10 and Precision@1 scores, at 0.547099 and 0.195868 respectively. Precision values decrease as K increases, reflecting the trade-off between recommendation breadth and accuracy. Based on these results, the model is considered feasible for implementation on the Pasar Hasil Bumi platform, with the recommendation that performance should be monitored periodically to adapt to changes in user preferences.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2110511054] [Pembimbing: Neny Rosmawarni] [Penguji 1: Musthofa Galih Pradana] [Penguji 2: Nurul Afifah Arifuddin]
Uncontrolled Keywords: Recommendation System, Two-Tower Model, Deep Learning, Embedding, Marketplace
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User: M. NAUFALDI FADHLIRRAHMAN
Date Deposited: 12 Jul 2025 22:08
Last Modified: 18 Jul 2025 03:43
URI: http://repository.upnvj.ac.id/id/eprint/37341

Actions (login required)

View Item View Item