PROPAGASI BALIK MENENTUKAN PREDIKSI PRODUKSI USAHA SONGKET SILUNGKANG KOTA SAWAHLUNTO

Kartika, Devia and Gema, Rima Liana (2018) PROPAGASI BALIK MENENTUKAN PREDIKSI PRODUKSI USAHA SONGKET SILUNGKANG KOTA SAWAHLUNTO. Computer Based Information System Journal, 6 (2). p. 69. ISSN 2337-8794

[img]
Preview
Text
PROPAGASI BALIK MENENTUKAN PREDIKSI PRODUKSI USAHA SONGKET SILUNGKANG KOTA SAWAHLUNTO.pdf

Download (882kB) | Preview
Official URL/ URL Asal/ URL DOI: http://doi.org/10.33884/cbis.v6i2.698

Abstract

Artificial Neural Networks is a computational paradigm in which the way it works mimics the biological nerve cell system based on the characteristics of the function of the human brain. One method used in Artificial Neural Networks is a backpropagation algorithm that is widely used, especially in dealing with the problem of identification, prediction, recognition of complex patterns because this method is able to predict what will happen in the future based on patterns that existed in the past. Songket is one of the works of skilled hands of the original Silungkang craftsmen, Sawahlunto City, West Sumatra who have varied and unique patterns and motifs. Sawahlunto City Government, West Sumatra prioritizes the development of Silungkang songket craft business, which is a regional specialty, to enter the export market. At the initial stage, the regional government's priority is to increase the production of crafters by facilitating the development of micro, small and medium enterprises (MSMEs), especially those engaged in songket, to continue to be developed by improving quality and creativity. The city of Sawahlunto can help several parties such as the government, micro, small and medium enterprises in making good handling and decision making efforts to increase the production of Songket Silungkang MSMEs in Sawahlunto City.

Item Type: Article
Subjects: 0 Research > Ilmu Komputer > Algoritma
Divisions/ Fakultas/ Prodi: Fakultas Ilmu Komputer
Depositing User: Administrator 2
Date Deposited: 21 Sep 2021 07:51
Last Modified: 21 Sep 2021 07:51
URI: http://repository.upiyptk.ac.id/id/eprint/3300

Actions (login required)

View Item View Item