Skripsi/Tugas Akhir

Implementasi Machine Learning pada Sistem Rekomendasi E-Commerce UMKM Kerajinan Tangan

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ABSTRAK
Usaha Mikro, Kecil, dan Menengah (UMKM) berperan penting dalam pertumbuhan ekonomi Indonesia, termasuk di Kota Makassar, yang merupakan pusat perdagangan di Indonesia Timur. Sektor UMKM kerajinan tangan di Makassar memberikan kontribusi signifikan dalam menciptakan lapangan kerja dan meningkatkan kesejahteraan. Namun, banyak UMKM kesulitan menjangkau konsumen dan mempromosikan produk secara efektif di era digital. Penelitian ini bertujuan mengimplementasikan sistem rekomendasi berbasis Machine Learning untuk meningkatkan penjualan UMKM kerajinan tangan di Makassar. Metode yang digunakan adalah Item-Based Collaborative Filtering untuk menganalisis perilaku konsumen dan preferensi produk. Hasil penelitian menunjukkan bahwa sistem rekomendasi berbasis Machine Learning berhasil diterapkan pada platform e-commerce yang dikembangkan. Implementasi sistem rekomendasi diharapkan dapat menjadi solusi dalam mengatasi tantangan digitalisasi dan meningkatkan daya saing UMKM di pasar e-commerce.
Kata Kunci: UMKM, Kerajinan Tangan, Sistem Rekomendasi, Machine Learning, Item Based Collaborative Filtering, E-Commerce

ABSTRACT
Micro, Small, and Medium Enterprises (MSMEs) play a vital role in Indonesia's economic growth, including in Makassar City, which serves as a major trade center in Eastern Indonesia. The handicraft MSME sector in Makassar significantly contributes to job creation and the improvement of community welfare. However, many MSMEs face challenges in reaching consumers and promoting their products effectively in the digital era. This study aims to implement a Machine Learning-based recommendation system to increase the sales of handicraft MSMEs in Makassar. The method employed is Item-Based Collaborative Filtering, which analyzes consumer behavior and product preferences. The results show that the Machine Learning-based recommendation system was successfully implemented on the developed e-commerce platform. This system helps MSMEs reach the right consumers, expand market reach, and optimize data-driven marketing strategies. The implementation of this recommendation system is expected to be a viable solution to address digitalization challenges and enhance the competitiveness of MSMEs in the e commerce market.
Keywords: UMKM, Handicrafts, Recommendation System, Machine Learning, Item-Based Collaborative Filtering, E-Commerce

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Ketersediaan

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Informasi Detail

Judul Seri

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No. Panggil

SKR 25-51 ABB i - 0478SI

Penerbit

Makassar : Universitas DIPA., 2025

Deskripsi Fisik

xv + 77 hlm.; 20,5 x 28,5 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

SKR 25-51

Tipe Isi

Text dan Gambar

Edisi/Cetakan

Edisi/Cetakan 28 Februari 2025

Subjek

Skripsi/Tugas Akhir
Machine Learning
e-Commerce
Algoritma Item Based Collaborative Filtering

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