Artjuna : E-Commerce for Custom Made Heritage Art

Wardianto, Aditya (2022) Artjuna : E-Commerce for Custom Made Heritage Art. Project Report. [s.n.], [s.l.]. (Unpublished)

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Abstract

Pandemi COVID-19 telah mentransformasi cara hidup manusia menjadi “normal yang baru” atau new normal. Transformasi tersebut memberi efek yang cukup signifikan, salah satunya pada industri perdagangan. Transisi dari pembelian luring menjadi daring menghilangkan jarak antara pedagang dan pembeli. Hal ini memiliki keuntungan dan kerugian pada pedagang, di satu sisi lebih mudah untuk menjual barang, akan tetapi karena tren yang sangat cepat, menyulitkan pedagang untuk beradaptasi, khususnya pedagang kerajinan tangan yang memerlukan waktu untuk menyesuaikan dengan tren. Diperlukan sebuah platform bagi pedagang kerajinan tangan yang memudahkan proses penyesuaian dengan tren. Oleh karena itu penulis mengangkat judul “Artjuna: E-Commerce for Custom Made Heritage Art” sebagai bentuk kontribusi penulis sebagai mahasiswa untuk memajukan pedagang kerajinan tangan di Indonesia.
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The COVID-19 pandemic has transformed the way humans live into a "new normal". This transformation has had significant effects, one of which is on the trading industry. The transition from offline to online purchasing eliminates the distance between traders and buyers. This has advantages and disadvantages for traders. On one hand, it is easier to sell goods, but because trends change quickly, it is challenging for traders to adapt, especially for handicraft traders who need time to adjust to trends. A platform is needed for handicraft traders to facilitate the adjustment process to trends. Therefore, the author chose the title "Artjuna: E-Commerce for Custom Made Heritage Art" as a contribution as a student to advance handicraft traders in Indonesia.

Item Type:	Monograph (Project Report)
Uncontrolled Keywords:	CNN, Recommendation System, CNN, Sistem Rekomendasi
Subjects:	Q Science > Q Science (General) > Q325.5 Machine learning. R Medicine > R Medicine (General) > R858 Deep Learning T Technology > T Technology (General) > T174 Technological forecasting
Divisions:	Faculty of Electrical Technology > Biomedical Engineering > 11410-(S1) Undergraduate Thesis
Depositing User:	Aditya Wardianto
Date Deposited:	04 Aug 2023 08:15
Last Modified:	04 Aug 2023 08:15
URI:	http://repository.its.ac.id/id/eprint/103791

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