SHS Web Conf.
Volume 86, 2020ICORE 2019 – The International Conference on Rural Development and Entrepreneurship
|Number of page(s)||8|
|Published online||20 November 2020|
DiTenun, Smart Application Producing Ulos Motif
1,3 Teknik Informatika, Institut Teknologi Del, Laguboti Sumatera Utara
2 Management Rekayasa, Institut Teknologi Del, Laguboti Sumatera Utara
* Corresponding author: email@example.com
Indonesia is a country which is rich of various traditional cultures and values. One of its representation is traditional woven clothes (well known in Indonesian as kain tenun) which is wide spread throughout Indonesian regions. To support the traditional woven industry, as a relevancy to the industry 4.0 era, we develop DiTenun which is a multiplatform application that is able to produce new motifs of traditional woven intelligently using machine learning approach. The presence of the apps aims to support the growth of traditional weaving industry particularly the small and medium scale ones. The dissemination of the apps is very challenging as traditional woven centers are mostly located in rural area where the digital world has been rarely accessed. In this paper, we present “Ulos” as a case study in the utilization of DiTenun. The implementation of the sustainability of the Ulos industry by DiTenun needs to be adjusted to the development of the industrial era 4.0. Ulos is a traditional woven cloth from Batak tribe, which is located in several rural regions surrounding Toba highland in North Sumatera Utara province. The workflow for producing an item that is marketable is to produce woven fabrics with motifs that have been produced by smart devices. The results of DiTenun can have an impact on the technology produced and on the social life and culture of the weavers. The study shows how DiTenun is designed to support Ulos weavers in creating new motifs of Ulos and to support the economy of relevant small and medium scale industry of Ulos.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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